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Publisher: Elsevier   (Total: 3155 journals)

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Showing 1 - 200 of 3155 Journals sorted alphabetically
A Practical Logic of Cognitive Systems     Full-text available via subscription   (Followers: 9)
AASRI Procedia     Open Access   (Followers: 15)
Academic Pediatrics     Hybrid Journal   (Followers: 34, SJR: 1.655, CiteScore: 2)
Academic Radiology     Hybrid Journal   (Followers: 23, SJR: 1.015, CiteScore: 2)
Accident Analysis & Prevention     Partially Free   (Followers: 96, SJR: 1.462, CiteScore: 3)
Accounting Forum     Hybrid Journal   (Followers: 27, SJR: 0.932, CiteScore: 2)
Accounting, Organizations and Society     Hybrid Journal   (Followers: 38, SJR: 1.771, CiteScore: 3)
Achievements in the Life Sciences     Open Access   (Followers: 5)
Acta Anaesthesiologica Taiwanica     Open Access   (Followers: 7)
Acta Astronautica     Hybrid Journal   (Followers: 411, SJR: 0.758, CiteScore: 2)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 2)
Acta Biomaterialia     Hybrid Journal   (Followers: 27, SJR: 1.967, CiteScore: 7)
Acta Colombiana de Cuidado Intensivo     Full-text available via subscription   (Followers: 2)
Acta de Investigación Psicológica     Open Access   (Followers: 3)
Acta Ecologica Sinica     Open Access   (Followers: 10, SJR: 0.18, CiteScore: 1)
Acta Haematologica Polonica     Free   (Followers: 1, SJR: 0.128, CiteScore: 0)
Acta Histochemica     Hybrid Journal   (Followers: 3, SJR: 0.661, CiteScore: 2)
Acta Materialia     Hybrid Journal   (Followers: 258, SJR: 3.263, CiteScore: 6)
Acta Mathematica Scientia     Full-text available via subscription   (Followers: 5, SJR: 0.504, CiteScore: 1)
Acta Mechanica Solida Sinica     Full-text available via subscription   (Followers: 9, SJR: 0.542, CiteScore: 1)
Acta Oecologica     Hybrid Journal   (Followers: 12, SJR: 0.834, CiteScore: 2)
Acta Otorrinolaringologica (English Edition)     Full-text available via subscription  
Acta Otorrinolaringológica Española     Full-text available via subscription   (Followers: 3, SJR: 0.307, CiteScore: 0)
Acta Pharmaceutica Sinica B     Open Access   (Followers: 1, SJR: 1.793, CiteScore: 6)
Acta Poética     Open Access   (Followers: 4, SJR: 0.101, CiteScore: 0)
Acta Psychologica     Hybrid Journal   (Followers: 28, SJR: 1.331, CiteScore: 2)
Acta Sociológica     Open Access   (Followers: 1)
Acta Tropica     Hybrid Journal   (Followers: 6, SJR: 1.052, CiteScore: 2)
Acta Urológica Portuguesa     Open Access  
Actas Dermo-Sifiliograficas     Full-text available via subscription   (Followers: 3, SJR: 0.374, CiteScore: 1)
Actas Dermo-Sifiliográficas (English Edition)     Full-text available via subscription   (Followers: 2)
Actas Urológicas Españolas     Full-text available via subscription   (Followers: 3, SJR: 0.344, CiteScore: 1)
Actas Urológicas Españolas (English Edition)     Full-text available via subscription   (Followers: 1)
Actualites Pharmaceutiques     Full-text available via subscription   (Followers: 6, SJR: 0.19, CiteScore: 0)
Actualites Pharmaceutiques Hospitalieres     Full-text available via subscription   (Followers: 3)
Acupuncture and Related Therapies     Hybrid Journal   (Followers: 6)
Acute Pain     Full-text available via subscription   (Followers: 14, SJR: 2.671, CiteScore: 5)
Ad Hoc Networks     Hybrid Journal   (Followers: 11, SJR: 0.53, CiteScore: 4)
Addictive Behaviors     Hybrid Journal   (Followers: 17, SJR: 1.29, CiteScore: 3)
Addictive Behaviors Reports     Open Access   (Followers: 8, SJR: 0.755, CiteScore: 2)
Additive Manufacturing     Hybrid Journal   (Followers: 10, SJR: 2.611, CiteScore: 8)
Additives for Polymers     Full-text available via subscription   (Followers: 22)
Advanced Drug Delivery Reviews     Hybrid Journal   (Followers: 154, SJR: 4.09, CiteScore: 13)
Advanced Engineering Informatics     Hybrid Journal   (Followers: 11, SJR: 1.167, CiteScore: 4)
Advanced Powder Technology     Hybrid Journal   (Followers: 17, SJR: 0.694, CiteScore: 3)
Advances in Accounting     Hybrid Journal   (Followers: 8, SJR: 0.277, CiteScore: 1)
Advances in Agronomy     Full-text available via subscription   (Followers: 14, SJR: 2.384, CiteScore: 5)
Advances in Anesthesia     Full-text available via subscription   (Followers: 28, SJR: 0.126, CiteScore: 0)
Advances in Antiviral Drug Design     Full-text available via subscription   (Followers: 2)
Advances in Applied Mathematics     Full-text available via subscription   (Followers: 10, SJR: 0.992, CiteScore: 1)
Advances in Applied Mechanics     Full-text available via subscription   (Followers: 11, SJR: 1.551, CiteScore: 4)
Advances in Applied Microbiology     Full-text available via subscription   (Followers: 24, SJR: 2.089, CiteScore: 5)
Advances In Atomic, Molecular, and Optical Physics     Full-text available via subscription   (Followers: 14, SJR: 0.572, CiteScore: 2)
Advances in Biological Regulation     Hybrid Journal   (Followers: 4, SJR: 2.61, CiteScore: 7)
Advances in Botanical Research     Full-text available via subscription   (Followers: 2, SJR: 0.686, CiteScore: 2)
Advances in Cancer Research     Full-text available via subscription   (Followers: 33, SJR: 3.043, CiteScore: 6)
Advances in Carbohydrate Chemistry and Biochemistry     Full-text available via subscription   (Followers: 9, SJR: 1.453, CiteScore: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5, SJR: 1.992, CiteScore: 5)
Advances in Cell Aging and Gerontology     Full-text available via subscription   (Followers: 4)
Advances in Cellular and Molecular Biology of Membranes and Organelles     Full-text available via subscription   (Followers: 12)
Advances in Chemical Engineering     Full-text available via subscription   (Followers: 27, SJR: 0.156, CiteScore: 1)
Advances in Child Development and Behavior     Full-text available via subscription   (Followers: 10, SJR: 0.713, CiteScore: 1)
Advances in Chronic Kidney Disease     Full-text available via subscription   (Followers: 10, SJR: 1.316, CiteScore: 2)
Advances in Clinical Chemistry     Full-text available via subscription   (Followers: 29, SJR: 1.562, CiteScore: 3)
Advances in Colloid and Interface Science     Full-text available via subscription   (Followers: 19, SJR: 1.977, CiteScore: 8)
Advances in Computers     Full-text available via subscription   (Followers: 14, SJR: 0.205, CiteScore: 1)
Advances in Dermatology     Full-text available via subscription   (Followers: 14)
Advances in Developmental Biology     Full-text available via subscription   (Followers: 12)
Advances in Digestive Medicine     Open Access   (Followers: 9)
Advances in DNA Sequence-Specific Agents     Full-text available via subscription   (Followers: 5)
Advances in Drug Research     Full-text available via subscription   (Followers: 25)
Advances in Ecological Research     Full-text available via subscription   (Followers: 44, SJR: 2.524, CiteScore: 4)
Advances in Engineering Software     Hybrid Journal   (Followers: 28, SJR: 1.159, CiteScore: 4)
Advances in Experimental Biology     Full-text available via subscription   (Followers: 8)
Advances in Experimental Social Psychology     Full-text available via subscription   (Followers: 46, SJR: 5.39, CiteScore: 8)
Advances in Exploration Geophysics     Full-text available via subscription   (Followers: 1)
Advances in Fluorine Science     Full-text available via subscription   (Followers: 9)
Advances in Food and Nutrition Research     Full-text available via subscription   (Followers: 58, SJR: 0.591, CiteScore: 2)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 16)
Advances in Genetics     Full-text available via subscription   (Followers: 16, SJR: 1.354, CiteScore: 4)
Advances in Genome Biology     Full-text available via subscription   (Followers: 8, SJR: 12.74, CiteScore: 13)
Advances in Geophysics     Full-text available via subscription   (Followers: 6, SJR: 1.193, CiteScore: 3)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 23, SJR: 0.368, CiteScore: 1)
Advances in Heterocyclic Chemistry     Full-text available via subscription   (Followers: 12, SJR: 0.749, CiteScore: 3)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 22)
Advances in Imaging and Electron Physics     Full-text available via subscription   (Followers: 2, SJR: 0.193, CiteScore: 0)
Advances in Immunology     Full-text available via subscription   (Followers: 35, SJR: 4.433, CiteScore: 6)
Advances in Inorganic Chemistry     Full-text available via subscription   (Followers: 8, SJR: 1.163, CiteScore: 2)
Advances in Insect Physiology     Full-text available via subscription   (Followers: 2, SJR: 1.938, CiteScore: 3)
Advances in Integrative Medicine     Hybrid Journal   (Followers: 7, SJR: 0.176, CiteScore: 0)
Advances in Intl. Accounting     Full-text available via subscription   (Followers: 3)
Advances in Life Course Research     Hybrid Journal   (Followers: 8, SJR: 0.682, CiteScore: 2)
Advances in Lipobiology     Full-text available via subscription   (Followers: 1)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 8)
Advances in Marine Biology     Full-text available via subscription   (Followers: 18, SJR: 0.88, CiteScore: 2)
Advances in Mathematics     Full-text available via subscription   (Followers: 11, SJR: 3.027, CiteScore: 2)
Advances in Medical Sciences     Hybrid Journal   (Followers: 6, SJR: 0.694, CiteScore: 2)
Advances in Medicinal Chemistry     Full-text available via subscription   (Followers: 5)
Advances in Microbial Physiology     Full-text available via subscription   (Followers: 4, SJR: 1.158, CiteScore: 3)
Advances in Molecular and Cell Biology     Full-text available via subscription   (Followers: 23)
Advances in Molecular and Cellular Endocrinology     Full-text available via subscription   (Followers: 8)
Advances in Molecular Toxicology     Full-text available via subscription   (Followers: 7, SJR: 0.182, CiteScore: 0)
Advances in Nanoporous Materials     Full-text available via subscription   (Followers: 3)
Advances in Oncobiology     Full-text available via subscription   (Followers: 1)
Advances in Organ Biology     Full-text available via subscription   (Followers: 1)
Advances in Organometallic Chemistry     Full-text available via subscription   (Followers: 17, SJR: 1.875, CiteScore: 4)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7, SJR: 0.174, CiteScore: 0)
Advances in Parasitology     Full-text available via subscription   (Followers: 5, SJR: 1.579, CiteScore: 4)
Advances in Pediatrics     Full-text available via subscription   (Followers: 24, SJR: 0.461, CiteScore: 1)
Advances in Pharmaceutical Sciences     Full-text available via subscription   (Followers: 12)
Advances in Pharmacology     Full-text available via subscription   (Followers: 16, SJR: 1.536, CiteScore: 3)
Advances in Physical Organic Chemistry     Full-text available via subscription   (Followers: 8, SJR: 0.574, CiteScore: 1)
Advances in Phytomedicine     Full-text available via subscription  
Advances in Planar Lipid Bilayers and Liposomes     Full-text available via subscription   (Followers: 3, SJR: 0.109, CiteScore: 1)
Advances in Plant Biochemistry and Molecular Biology     Full-text available via subscription   (Followers: 10)
Advances in Plant Pathology     Full-text available via subscription   (Followers: 5)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Protein Chemistry     Full-text available via subscription   (Followers: 18)
Advances in Protein Chemistry and Structural Biology     Full-text available via subscription   (Followers: 20, SJR: 0.791, CiteScore: 2)
Advances in Psychology     Full-text available via subscription   (Followers: 64)
Advances in Quantum Chemistry     Full-text available via subscription   (Followers: 6, SJR: 0.371, CiteScore: 1)
Advances in Radiation Oncology     Open Access   (SJR: 0.263, CiteScore: 1)
Advances in Small Animal Medicine and Surgery     Hybrid Journal   (Followers: 3, SJR: 0.101, CiteScore: 0)
Advances in Space Biology and Medicine     Full-text available via subscription   (Followers: 6)
Advances in Space Research     Full-text available via subscription   (Followers: 399, SJR: 0.569, CiteScore: 2)
Advances in Structural Biology     Full-text available via subscription   (Followers: 5)
Advances in Surgery     Full-text available via subscription   (Followers: 11, SJR: 0.555, CiteScore: 2)
Advances in the Study of Behavior     Full-text available via subscription   (Followers: 34, SJR: 2.208, CiteScore: 4)
Advances in Veterinary Medicine     Full-text available via subscription   (Followers: 17)
Advances in Veterinary Science and Comparative Medicine     Full-text available via subscription   (Followers: 13)
Advances in Virus Research     Full-text available via subscription   (Followers: 5, SJR: 2.262, CiteScore: 5)
Advances in Water Resources     Hybrid Journal   (Followers: 46, SJR: 1.551, CiteScore: 3)
Aeolian Research     Hybrid Journal   (Followers: 6, SJR: 1.117, CiteScore: 3)
Aerospace Science and Technology     Hybrid Journal   (Followers: 345, SJR: 0.796, CiteScore: 3)
AEU - Intl. J. of Electronics and Communications     Hybrid Journal   (Followers: 8, SJR: 0.42, CiteScore: 2)
African J. of Emergency Medicine     Open Access   (Followers: 6, SJR: 0.296, CiteScore: 0)
Ageing Research Reviews     Hybrid Journal   (Followers: 11, SJR: 3.671, CiteScore: 9)
Aggression and Violent Behavior     Hybrid Journal   (Followers: 456, SJR: 1.238, CiteScore: 3)
Agri Gene     Hybrid Journal   (Followers: 1, SJR: 0.13, CiteScore: 0)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 17, SJR: 1.818, CiteScore: 5)
Agricultural Systems     Hybrid Journal   (Followers: 31, SJR: 1.156, CiteScore: 4)
Agricultural Water Management     Hybrid Journal   (Followers: 41, SJR: 1.272, CiteScore: 3)
Agriculture and Agricultural Science Procedia     Open Access   (Followers: 3)
Agriculture and Natural Resources     Open Access   (Followers: 3)
Agriculture, Ecosystems & Environment     Hybrid Journal   (Followers: 57, SJR: 1.747, CiteScore: 4)
Ain Shams Engineering J.     Open Access   (Followers: 5, SJR: 0.589, CiteScore: 3)
Air Medical J.     Hybrid Journal   (Followers: 6, SJR: 0.26, CiteScore: 0)
AKCE Intl. J. of Graphs and Combinatorics     Open Access   (SJR: 0.19, CiteScore: 0)
Alcohol     Hybrid Journal   (Followers: 11, SJR: 1.153, CiteScore: 3)
Alcoholism and Drug Addiction     Open Access   (Followers: 10)
Alergologia Polska : Polish J. of Allergology     Full-text available via subscription   (Followers: 1)
Alexandria Engineering J.     Open Access   (Followers: 1, SJR: 0.604, CiteScore: 3)
Alexandria J. of Medicine     Open Access   (Followers: 1, SJR: 0.191, CiteScore: 1)
Algal Research     Partially Free   (Followers: 11, SJR: 1.142, CiteScore: 4)
Alkaloids: Chemical and Biological Perspectives     Full-text available via subscription   (Followers: 2)
Allergologia et Immunopathologia     Full-text available via subscription   (Followers: 1, SJR: 0.504, CiteScore: 1)
Allergology Intl.     Open Access   (Followers: 5, SJR: 1.148, CiteScore: 2)
Alpha Omegan     Full-text available via subscription   (SJR: 3.521, CiteScore: 6)
ALTER - European J. of Disability Research / Revue Européenne de Recherche sur le Handicap     Full-text available via subscription   (Followers: 9, SJR: 0.201, CiteScore: 1)
Alzheimer's & Dementia     Hybrid Journal   (Followers: 51, SJR: 4.66, CiteScore: 10)
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring     Open Access   (Followers: 4, SJR: 1.796, CiteScore: 4)
Alzheimer's & Dementia: Translational Research & Clinical Interventions     Open Access   (Followers: 4, SJR: 1.108, CiteScore: 3)
Ambulatory Pediatrics     Hybrid Journal   (Followers: 6)
American Heart J.     Hybrid Journal   (Followers: 50, SJR: 3.267, CiteScore: 4)
American J. of Cardiology     Hybrid Journal   (Followers: 54, SJR: 1.93, CiteScore: 3)
American J. of Emergency Medicine     Hybrid Journal   (Followers: 45, SJR: 0.604, CiteScore: 1)
American J. of Geriatric Pharmacotherapy     Full-text available via subscription   (Followers: 10)
American J. of Geriatric Psychiatry     Hybrid Journal   (Followers: 14, SJR: 1.524, CiteScore: 3)
American J. of Human Genetics     Hybrid Journal   (Followers: 34, SJR: 7.45, CiteScore: 8)
American J. of Infection Control     Hybrid Journal   (Followers: 28, SJR: 1.062, CiteScore: 2)
American J. of Kidney Diseases     Hybrid Journal   (Followers: 35, SJR: 2.973, CiteScore: 4)
American J. of Medicine     Hybrid Journal   (Followers: 47)
American J. of Medicine Supplements     Full-text available via subscription   (Followers: 3, SJR: 1.967, CiteScore: 2)
American J. of Obstetrics and Gynecology     Hybrid Journal   (Followers: 215, SJR: 2.7, CiteScore: 4)
American J. of Ophthalmology     Hybrid Journal   (Followers: 66, SJR: 3.184, CiteScore: 4)
American J. of Ophthalmology Case Reports     Open Access   (Followers: 5, SJR: 0.265, CiteScore: 0)
American J. of Orthodontics and Dentofacial Orthopedics     Full-text available via subscription   (Followers: 6, SJR: 1.289, CiteScore: 1)
American J. of Otolaryngology     Hybrid Journal   (Followers: 25, SJR: 0.59, CiteScore: 1)
American J. of Pathology     Hybrid Journal   (Followers: 28, SJR: 2.139, CiteScore: 4)
American J. of Preventive Medicine     Hybrid Journal   (Followers: 28, SJR: 2.164, CiteScore: 4)
American J. of Surgery     Hybrid Journal   (Followers: 38, SJR: 1.141, CiteScore: 2)
American J. of the Medical Sciences     Hybrid Journal   (Followers: 12, SJR: 0.767, CiteScore: 1)
Ampersand : An Intl. J. of General and Applied Linguistics     Open Access   (Followers: 7)
Anaerobe     Hybrid Journal   (Followers: 4, SJR: 1.144, CiteScore: 3)
Anaesthesia & Intensive Care Medicine     Full-text available via subscription   (Followers: 62, SJR: 0.138, CiteScore: 0)
Anaesthesia Critical Care & Pain Medicine     Full-text available via subscription   (Followers: 17, SJR: 0.411, CiteScore: 1)
Anales de Cirugia Vascular     Full-text available via subscription  
Anales de Pediatría     Full-text available via subscription   (Followers: 3, SJR: 0.277, CiteScore: 0)
Anales de Pediatría (English Edition)     Full-text available via subscription  
Anales de Pediatría Continuada     Full-text available via subscription  
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 5, SJR: 4.849, CiteScore: 10)
Analytica Chimica Acta     Hybrid Journal   (Followers: 42, SJR: 1.512, CiteScore: 5)
Analytical Biochemistry     Hybrid Journal   (Followers: 180, SJR: 0.633, CiteScore: 2)
Analytical Chemistry Research     Open Access   (Followers: 12, SJR: 0.411, CiteScore: 2)
Analytical Spectroscopy Library     Full-text available via subscription   (Followers: 11)
Anesthésie & Réanimation     Full-text available via subscription   (Followers: 2)
Anesthesiology Clinics     Full-text available via subscription   (Followers: 23, SJR: 0.683, CiteScore: 2)
Angiología     Full-text available via subscription   (SJR: 0.121, CiteScore: 0)
Angiologia e Cirurgia Vascular     Open Access   (Followers: 1, SJR: 0.111, CiteScore: 0)
Animal Behaviour     Hybrid Journal   (Followers: 201, SJR: 1.58, CiteScore: 3)

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Journal Cover
Accident Analysis & Prevention
Journal Prestige (SJR): 1.462
Citation Impact (citeScore): 3
Number of Followers: 96  
  Partially Free Journal Partially Free Journal
ISSN (Print) 0001-4575
Published by Elsevier Homepage  [3155 journals]
  • The factors shaping car drivers’ attitudes towards cyclist and their
           impact on behaviour
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Laura S. Fruhen, Isabel Rossen, Mark A. Griffin Cycling for transportation has multiple benefits to both individuals and societies. However, in many countries, cycling rates are very low. One major deterrent is hostile or aggressive behaviours directed towards cyclists. Past research has established that negative attitudes towards cyclist are a major driver of aggressive behaviour. However, the attitudinal roots that motivate these negative attitudes are currently not well understood. This study investigates to what extent negative attitudes towards cyclists are rooted in a sense of attachment to cars, and environmental attitudes. Furthermore, the study examines whether the distinctiveness of group-membership of cyclists, as signalled by cycling attire, influences the link between attitudes and aggressive behaviours directed at cyclists. An online survey of 308 car drivers measured automobility and environmental attitudes, attitudes towards cyclist, and aggressive behaviour addressed at two groups of cyclists (lycra-clad or casually dressed cyclists). Hierarchical regression analyses showed that automobility attitudes, but not environmental attitudes, were associated with negative car driver attitudes towards cyclists. A significant link between negative attitudes towards cyclists and aggressive behaviour addressed at cyclists was not moderated by the type of cyclist shown. These findings provide a more refined understanding of the basis in which negative attitudes towards cyclists are rooted and how they affect driver behaviour. This research may inform campaigns and initiatives aimed at changing attitudes towards cyclists.
  • The association between sensation seeking and driving outcomes: A
           systematic review and meta-analysis
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Xiaoyan Zhang, Xingda Qu, Da Tao, Hongjun Xue The purpose of this study was to evaluate the association between sensation seeking (SS) and driving outcomes (including four aberrant driving behaviors, accident involvement and tickets received) through a systematic review and meta-analysis. Forty-four eligible studies, representing 48 individual trials, were identified from a systematic literature search of four electronic databases, and included in the meta-analysis. Overall, the meta-analysis results showed that SS yielded significant positive correlations with risky driving (pooled r = 0.24, p 
  • Observing the observation of (vulnerable) road user behaviour and traffic
           safety: A scoping review
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Wouter van Haperen, Malik Sarmad Riaz, Stijn Daniels, Nicolas Saunier, Tom Brijs, Geert Wets Behavioural observation studies in road safety research collect naturalistic data of road users that are not informed (beforehand) of their participation in a research project. It enables the observation of behavioural and situational processes that contribute to unsafe traffic events, while possible behavioural adaptations due to the road users’ recognition of being observed are minimized. The literature in this field is vast and diverse, with studies dating back to the 1930s. The aim of this paper is to summarize the research efforts in the domain of road user behavioural observation research to examine trends and developments of this type of research, using a scoping review. After the definition of certain selection criteria, 600 journal articles found in three major online databases were retrieved and included in this review.The number of publications regarding road user behavioural observation studies has increased rapidly during recent years, indicating the importance of behavioural observation studies to study traffic safety. Most studies collected data on car drivers (81%), while vulnerable road users have been observed in 32% of all studies, with pedestrians and (motor)cyclists as the most common road user types. The results showed that the main goal of behavioural observation is to monitor (51%), followed by the evaluation of a specific safety improving measure (38%) and the development of behavioural models (10%). Most topics relate to traffic events where interactions with other road users are necessary, indicating that the examination of behavioural processes underlying single-vehicle crashes has received little attention. The ongoing developments of automated video analysis software tools can be the next methodological step forward in video-based behavioural observation studies, since it enables a more objective data collection and data analysis process.
  • Using horizontal curve speed reduction extracted from the naturalistic
           driving study to predict curve collision frequency
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Bashar Dhahir, Yasser Hassan Many models have been developed to predict collision frequency and evaluate safety performance on horizontal curves. The approach used in data collection or some assumptions made in the analysis methodology might lead to inaccurate results. For example, manual data collection, equipment limitations, and field experiments involving monitoring driving behavior for a specific region for a short-term are potential sources of errors in data collection. This paper aims at overcoming some of these issues in developing models to evaluate safety performance of horizontal curves and predict the curve collision frequency. The developed models relate expected collision frequency on horizontal curves to the speed reduction from the approach tangent to the curve, which is commonly used as a major geometric design consistency measure. The methodology to achieve this objective included three tasks; data collection, evaluating and modeling the viable speed reduction parameters, and developing safety performance models to estimate collision frequency on horizontal curves. Individual drivers’ trips on 49 horizontal curves on rural two-lane highways in rolling and mountainous terrains in Washington State were extracted from the Naturalistic Driving Study (NDS) database. Models were developed to relate different speed reduction parameters to curve characteristics. These models were then applied to 1430 horizontal curves in Washington State to estimate the speed reduction parameters and relate them to collision frequency. Several safety performance models were developed which show that speed reduction, as a design consistency measure, is directly related to collision frequency on horizontal curves. Furthermore, the speed reduction parameters are more significant variables in predicting collision frequency than all curve geometric parameters.
  • Probabilistic, safety-explicit design of horizontal curves on two-lane
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Bashar Dhahir, Yasser Hassan The high collision rates on horizontal curves compared to other roadway elements make them one of the most critical elements in a transportation network. In this regard, it is important to develop models to predict the safety performance of the horizontal curves. A considerable number of studies have been conducted to develop safety performance functions based on several concepts such as geometric characteristics, design consistency, reliability analysis, and comfort threshold. However, these models do not account for all horizontal curve design criteria or consider several cases such as driving in adverse weather conditions or on pavement of low available friction. This paper develops a probabilistic, safety explicit approach of horizontal curve design using reliability analysis of four design criteria: vehicle stability, driver comfort, sight distance, and vehicle rollover. Two situations were considered in the analysis: driving in clear weather (dry pavement) and raining weather (wet pavement) to develop safety performance functions for annual and five-year collision frequency. Four types of regression models, Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial, were used in the analysis. The AIC, BIC, and Vuong test were used in evaluating the developed models.
  • Private and public willingness to pay for safety: A validity test
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Henrik Andersson, Elodie Levivier, Gunnar Lindberg Stated preference (SP) methods are often used to elicit an affected population’s preferences for, e.g., increased safety or better environmental quality. SP methods are based on hypothetical market scenarios which have advantages, since decision alternatives are known to the analysis, but also necessitate thorough validity tests of the results, since decisions are hypothetical. This study suggests a validity test based on theoretical predictions and empirical findings for private and public safety measures. According to the test, willingness to pay (WTP) for a public safety measure should exceed or be equal to the private one. Based on a rich data set eliciting both private and public WTP the results show that private WTP exceeds public WTP. Hence, the findings in this study highlight the importance of validity tests of preference estimates for safety, and suggest that WTP also for a private safety measure should be elicited in studies eliciting WTP for public safety measures, to allow for the validity test.
  • Utilizing UAV video data for in-depth analysis of drivers’ crash risk at
           interchange merging areas
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Xin Gu, Mohamed Abdel-Aty, Qiaojun Xiang, Qing Cai, Jinghui Yuan The interchange merging area suffers a high crash risk in the freeway system, which is greatly related to the intense mandatory merging maneuvers. Ignoring such correlation may result in limited and biased conclusions and inefficient countermeasures. Recently, the availability of unmanned aerial vehicle (UAV) provides us an opportunity to collect individual vehicle’s data to conduct traffic analysis at the microscopic level. Hence, this paper contributes to the literature by proposing a new framework to analyze crash risk at freeway interchange merging areas considering drivers’ merging behavior. The analysis framework is conducted based on individual vehicle data from UAV videos. A multilevel random parameters logistic regression model is proposed to investigate each driver’s merging behavior in the acceleration lane. The model could identify the impact of different factors related to traffic and drivers on the merging behavior. Then, the crash risk between the merging vehicle and surrounding vehicles is calculated by incorporating the time-to-collision (TTC) and the output of the estimated merging behavior’s model. The results suggest that the proposed method provides more valuable insights about the crash risk at interchange merging areas by simultaneously considering the merging behavior and the safety measure. It is concluded that the merging speed, driving ability (e.g., lane change confidence, lane-keeping instability), and the merging location can affect the crash risk. These results can help traffic engineers propose efficient countermeasures to enhance the safety of the interchange merging area. The results also have implications to the design of merging areas and the advent of connected vehicles’ technology.
  • The effects of takeover request modalities on highly automated car control
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Sol Hee Yoon, Young Woo Kim, Yong Gu Ji This study investigated the influences of takeover request (TOR) modalities on a drivers’ takeover performance after they engaged in non-driving related (NDR) tasks in highly automated driving (HAD). Visual, vibrotactile, and auditory modalities were varied in the design of the experiment under four conditions: no-task, phone conversation, smartphone interaction, and video watching tasks. Driving simulator experiments were conducted to analyze the drivers’ take-over performance by collecting data during the transition time of re-engaging control of the vehicle, the time taken to be on the loop, and time taken to be physically ready to drive. Data were gathered on the perceived usefulness, safety, satisfaction, and effectiveness for each TOR based on a self-reported questionnaire. Takeover and hands-on times varied considerably, as shown by high standard deviation values between modalities, especially for phone conversations and smartphone interaction tasks. Moreover, it was found that participants failed to take over control of the vehicle when they were given visual TORs for phone conversation and smartphone interaction tasks. The perceived safety and satisfaction varied for the NDR task. Results from the statistical analysis showed that the NDR task significantly influenced the takeover time, but there was no significant interaction effect between the TOR modalities and the NDR task. The results could potentially be applied to the design of safe and efficient transitions of highly controlled, automated driving, where drivers are enabled to engage in NDR tasks.
  • Evaluating individual risk proneness with vehicle dynamics and self-report
           data ˗ toward the efficient detection of At-risk drivers
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Blazej Palat, Guillaume Saint Pierre, Patricia Delhomme Vehicle-dynamics data, now more readily available thanks to moderate-cost, embedded data logging solutions, have been used to study drivers' behavior (acceleration, braking, and yaw rate) through naturalistic driving research aimed at detecting critical safety events. In addition, self-reported measures have been developed to describe these events and to assess various individual risk factors such as sensation seeking, lack of experience, anger expression while driving, and sensitivity to distraction. In the present study, we apply both of these methods of gathering driving data in order to assess risk proneness as accurately as possible. Data were obtained from 131 drivers, who filled in an introductory questionnaire pertaining to their driving habits. Their vehicles were equipped with an external, automatic data-capture device for approximately two months. During that period, the participants reported critical safety events that occurred behind the wheel by (a) pressing a button connected to the device and (b) describing the events in logbooks. They also filled in weekly questionnaires, and at the end of the participation period, a final questionnaire with various self-reported measures pertaining to their driving activity. We processed the data by (a) performing a multiple correspondence analysis of the characteristics assessed via the automatic data capture and self-reports, and (b) categorizing the participants via hierarchical clustering of their coordinates on the dimensions obtained from the correspondence analysis. This allowed us to identify a group of drivers (n = 43) at risk, based on several self-reported measures, in particular, their recent crash involvement, and the frequency of critical acceleration/deceleration events as an objective measure. However, the at-risk drivers did not themselves report more critical safety events than the other two groups.
  • Self-reported violations, errors and lapses for older drivers: Measuring
           the change in frequency of aberrant driving behaviours across five
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Sjaan Koppel, Amanda N. Stephens, Michel Bédard, Judith L. Charlton, Peteris Darzins, Marilyn Di Stefano, Sylvain Gagnon, Isabelle Gélinas, Phuong Hua, Lynn MacLeay, Malcolm Man-Son-Hing, Barbara Mazer, Anita Myers, Gary Naglie, Morris Odell, Michelle M. Porter, Mark J. Rapoport, Arne Stinchcombe, Holly Tuokko, Brenda Vrkjlan The current study aimed to: 1. to confirm the 21-item, three-factor Driver Behaviour Questionnaire (DBQ) structure suggested by Koppel et al. (2018) within an independent sample of Canadian older drivers; 2. to examine whether the structure of the DBQ remained stable over a four-year period; 3. to conduct a latent growth analysis to determine whether older drivers’ DBQ scores changed across time. Five hundred and sixty Canadian older drivers (males = 61.3%) from the Candrive/Ozcandrive longitudinal study completed the DBQ yearly for four years across five time-points that were approximately 12 months apart. In Year 1, the average age of the older drivers was 76.0 years (SD = 4.5 years; Range = 70–92 years). Findings from the study support the 21-item, three-factor DBQ structure suggested by Koppel and colleagues for an Australian sample of older drivers as being acceptable in an independent sample of Canadian older drivers. In addition, Canadian older drivers’ responses to this version of the DBQ were stable across the five time-points. More specifically, there was very little change in older drivers’ self-reported violations, and no significant change for self-reported errors or lapses. The findings from the current study add further support for this version of the DBQ as being a suitable tool for examining self-reported aberrant driving behaviours in older drivers. Future research should investigate the relationship between older drivers’ self-reported aberrant driving behaviours and their performance on functional measures, their responses to other driving-related abilities and practice scales and/or questionnaires, as well their usual (or naturalistic) driving practices and/or performance on on-road driving tasks.
  • Updated estimates of the relationship between speed and road safety at the
           aggregate and individual levels
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Rune Elvik, Anna Vadeby, Tove Hels, Ingrid van Schagen Recent studies of the relationship between the speed of traffic and road safety, stated as the number of fatalities and the number of injury accidents, are reviewed and their results synthesised by means of meta-analysis. All studies were based on data fully or partly for years after 2000. Previously proposed models of the relationship between the speed of traffic and road safety, including the Power Model and an Exponential Model, are supported. Summary estimates of coefficients show that the relationship between speed and road safety remains strong. The Power Model and the Exponential Model both fit the data very well. The relationship between speed and road safety is the same at the individual driver level as at the aggregate level referring to the mean speed of traffic.
  • Semi-autonomous vehicles: Usage-based data evidences of what could be
           expected from eliminating speed limit violations
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Ana M. Pérez-Marín, Montserrat Guillen The use of advanced driver assistance systems and the transition towards semi-autonomous vehicles are expected to contribute to a lower frequency of motor accidents and to have a significant impact for the automobile insurance industry, as rating methods must be revised to ensure that risks are correctly measured. Telematics information and usage-based insurance research are analyzed to identify the effect of driving patterns on the risk of accident. This is used as a starting point for addressing risk quantification and safety for vehicles that can control speed. The effect of excess speed on the risk of accidents is estimated with a real telematics data set. Scenarios for a reduction of speed limit violations and the consequent decrease in the expected number of accident claims are shown. If excess speed could be eliminated, then the expected number of accident claims could be reduced to half of its initial value, applying the average conditions of the data used in this study. As a consequence, insurance premiums also diminish.
  • Modeling and mitigating fatigue-related accident risk of taxi drivers
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Musen Kingsley Li, Jiayi Joey Yu, Liang Ma, Wei Zhang Taxi drivers worldwide often have very long driving hours and experience frequent fatigue. These conditions are associated with a high prevalence of fatigue and accidents. However, the key factors that distinguish high/low fatigue-related accident risk (FRAR) taxi drivers are uncertain. By examining a series of potential factors related with fatigue or accident risk as discussed in previous research, the objective was to find out the most important factors that relate to taxi driver’s FRAR, and to investigate the association of these factors and taxi driver’s FRAR. Modeling methods were applied to questionnaire data collected from Beijing taxi drivers. A 269-sample dataset was analyzed to identify key factors related to FRAR and to fit FRAR prediction models. The model’s performance on high-risk driver prediction was then tested using another independently collected 100-sample dataset. High-risk taxi drivers had significantly longer driving hours per working day, lower rest ratios, less driving experience, and were more confident about their fatigue resistance. The FRAR model with only four major measurable predictors achieved a sensitivity of 91.9% and a specificity of 94.6% on predicting labeled data. Adjusting drive-rest habits and self-evaluation pertaining to these predictors is good for high-risk drivers to mitigate their accident risk. It was concluded that taxi drivers’ drive-rest habits, experience, and intention for fatigue driving are crucial, and to a large degree determine their FRAR, and the prediction model can satisfactorily identify high-risk taxi drivers.
  • Bicycle helmet wearing is associated with closer overtaking by drivers: A
           response to Olivier and Walter, 2013
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Ian Walker, Dorothy L. Robinson There is a body of research on how driver behaviour might change in response to bicyclists’ appearance. In 2007, Walker published a study suggesting motorists drove closer on average when passing a bicyclist if the rider wore a helmet, potentially increasing the risk of a collision. Olivier and Walter re-analysed the same data in 2013 and claimed helmet wearing was not associated with close vehicle passing. Here we show how Olivier and Walter’s analysis addressed a subtly, but importantly, different question than Walker’s. Their conclusion was based on omitting information about variability in driver behaviour and instead dividing overtakes into two binary categories of ‘close’ and ‘not close’; we demonstrate that they did not justify or address the implications of this choice, did not have sufficient statistical power for their approach, and moreover show that slightly adjusting their definition of ‘close’ would reverse their conclusions. We then present a new analysis of the original dataset, measuring directly the extent to which drivers changed their behaviour in response to helmet wearing. This analysis confirms that drivers did, overall, get closer when the rider wore a helmet. The distribution of overtaking events shifted just over one-fifth of a standard deviation closer to the rider – a potentially important behaviour if, as theoretical frameworks suggest, near-misses and collisions lie on a continuum. The paper ends by considering wider issues surrounding this topic and suggests public health research might be best served by shifting focus to risk elimination rather than harm mitigation.
  • A meta-analysis of the crash risk of cannabis-positive drivers in
           culpability studies—Avoiding interpretational bias
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Ole Rogeberg Background: Culpability studies, a common study design in the cannabis crash risk literature, typically report odds-ratios (OR) indicating the raised risks of a culpable accident. This parameter is of unclear policy relevance, and is frequently misinterpreted as an estimate of the increased crash risk, a practice that introduces a substantial “interpretational bias”.Methods: A Bayesian statistical model for culpability study counts is developed to provide inference for both culpable and total crash risks, with a hierarchical effect specification to allow for meta-analysis across studies with potentially heterogeneous risk parameter values. The model is assessed in a bootstrap study and applied to data from 13 published culpability studies.Results: The model outperforms the culpability OR in bootstrap analyses. Used on actual study data, the average increase in crash risk is estimated at 1.28 (1.16–1.40). The pooled increased risk of a culpable crash is estimated as 1.42 (95% credibility interval 1.11–1.75), which is similar to pooled estimates using traditional ORs (1.46, 95% CI: 1.24–1.72). The attributable risk fraction of cannabis impaired driving is estimated to lie below 2% for all but two of the included studies.Conclusions: Culpability ORs exaggerate risk increases and parameter uncertainty when misinterpreted as total crash ORs. The increased crash risk associated with THC-positive drivers in culpability studies is low.
  • Assessment of the disaster medical response system through an
           investigation of a 43-vehicle mass collision on Jung-ang expressway
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Hee Young Lee, Jeong IL Lee, Oh Hyun Kim, Kang Hyun Lee, Hyeong Tae Kim, Hyun Youk PurposeIt was considered the challenges of the actual response and the potential for improvement, including the activities of the disaster response system, national emergency medical center, and the regional base hospital for the treatment of multiple traffic accident victims. The purpose of this study was to analyze the accident management system through real investigating the multiple collision over 10 vehicles with mass casualty events as a disaster situation.MethodsThis study was retrospective study to analyze the disaster event with multiple collision traffic accident on the expressway in Korea. We visited five medical centers for eight days since the accident occurred and interviewed the injured patients in this accident to examine the health status and medical records. After that, we visited the sixteen car-repair shops in four cities for real investigate about damaged vehicles. According to the arrangement of the accident situation for the accident vehicles through real-world investigation, we reproduced all parts of the accident scene, which were real-world investigated, by the accident situation sketch program. The collected data were summarized by Collision Deformation Classification (CDC) codes, and the medical records of the occupants were assessed using the Injury Severity Score (ISS).ResultsThe cause of the accident was snow freezing of the road. The information about 72 injured patients on 31 damaged vehicles was collected by phone, visit, and actual accident investigation. Of the 72 patients who were examined, 4 were severely injured and 68 were mildly injured. The accident occurred in the order of Sedan 13 (41.9%), SUV 11 (35.5%), Truck 4 (12.9%), Van 2 (6.5%) and Bus 1 (3.2%). The median value of the age [lower quartile and upper quartile] was 43 [34.5–52] years old and the patients included 25 drivers, 11 passengers, 7 back seat passengers, and 29 bus passengers.ConclusionThe primary cause of this mass collision accident was road surface freezing, but the more serious secondary cause was a driver’s inability to avoid the accident scene after the first collision. The severely injured occupants were occurred on the roads outside and inside the vehicle. In the event of a disaster, various teams from the police team, firefighting team, DMAT, EMS, road management team are gathered, and communication and command system between each team is important in order to identify and solve the disaster situation. To do this, it is important to develop manuals and prepare for training through repeated simulations.
  • Safety sensitivity to roadway characteristics: A comparison across highway
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Sikai Chen, Tariq Usman Saeed, Majed Alinizzi, Steven Lavrenz, Samuel Labi This paper examined the accident risk factors associated with highway traffic and roadway design, for each of three highway classes in the United States using a bivariate modeling framework involving two levels of accident severity. With regard to the highest class (Interstates), the results suggest that, compared to no-casualty accidents, casualty accidents are more sensitive to traffic volume and average vertical grade, but less sensitive to the inside shoulder width and the median width. For US Roads, it was determined that, compared to no-casualty accidents, casualty accidents are more sensitive to traffic volume, outside shoulder width, pavement condition, and median width but less sensitive to the average vertical grade. For the relatively lowest-class roads (State Roads), it was determined that, compared to no-casualty accidents, casualty accidents are more sensitive to the traffic volume, lane width, outside shoulder width, and pavement condition. Compared to the relatively lower-class highways, accidents at higher-class highways are more sensitive to: changes in traffic volume, average vertical grade, median width, inside shoulder width, and the pavement condition (no-casualty accidents only); but less sensitive to changes in lane width, pavement condition (casualty accidents only), and the outside shoulder width. This variation in sensitivity across the different road classes could be attributed to the differences in road geometry standards across the road classes, as the results seem to support the hypothesis that these standards strongly influence accident occurrence. It is hoped that the developed bivariate negative binomial models can help highway engineers to evaluate their current design standards and policy, and to assess the safety consequences of changes in these standards in each road class.
  • Exploring the impacts of speed variances on safety performance of urban
           elevated expressways using GPS data
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Chuan Xu, Xuesong Wang, Hong Yang, Kun Xie, Xiaohong Chen Speed variation on urban expressways has been frequently noted as a key factor associated with high crash risk. However, it was often difficult to capture the safety impact of speed variance with spaced sensor measurements. As an alternative, this paper aims to leverage the use of the floating car data (FCD) to capture the speed variance in a morning rush hour on urban elevated expressways and examine its effect on safety. A semi-automatic filtering process was introduced to distinguish taxi GPS data points on the elevated expressways from the ones on the surface roads under the expressways. Subsequently, the standard deviation of the cross-sectional speed mean (SDCSM) and the cross-section speed standard deviation (MCSSD) were derived to capture the spatial and temporal speed variances, respectively. Together with other explanatory variables, both hierarchical and non-hierarchical Poisson-gamma measurement error models were developed to model the crash frequencies of the expressways. The modeling results showed that the hierarchical model performed better and both SDCSM and MCSSD were found to be positively related to the crash occurrence. This secures the need for addressing the impact of speed variation when modeling crashes occurred on the elevated expressways.
  • The association of self-regulation, habit, and mindfulness with texting
           while driving
    • Abstract: Publication date: February 2019Source: Accident Analysis & Prevention, Volume 123Author(s): Melanie M. Moore, Patricia M. Brown The saturation of mobile phones throughout Australia has led to some individuals being unable to regulate their use within situations that are inappropriate or risky. One of the most prevalent risky mobile phone use behaviours is texting while driving. Attempts to explain texting while driving suggest cognitive variables and personality characteristics are key factors. This study explored relationships between trait self-regulation, habitual text messaging, trait mindfulness, and texting while driving. One hundred and seventy participants comprising Australian undergraduate psychology students and members of the public completed an online survey measuring trait self-regulation, habitual text messaging behaviour, trait mindfulness, and frequency of texting while driving. It was found that habitual texting behaviour mediated the relationship between trait self-regulation and frequency of texting while driving. Additionally, trait mindfulness moderated the relationship between habit and texting while driving, such that habitual texting was significantly, positively related to texting while driving, but only for individuals with low to moderate trait mindfulness. These results suggest personality constructs related to attention, awareness, and control of behaviour play a significant role in counteracting the association that habitual texting behaviour has with the frequency of texting while driving. As these traits are considered malleable, this association may be applicable in future development of intervention programs aimed at increasing control over mobile phone use and reducing the frequency with which people text while driving.
  • Truck safety evaluation on Wyoming mountain passes
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Dick T. Apronti, Promothes Saha, Milhan Moomen, Khaled Ksaibati The Manual on Uniform Traffic Control Devices (MUTCD) for Streets and Highways recommends hill signs be placed in advance of downgrade descent of mountain passes. Mountain passes increase the risk of a runaway, or out of control trucks and so the advance warning signs inform the driver to take special precautions such as reducing speed or using lower gears during the descent. The Wyoming Department of Transportation has installed steep grade advance warning systems on Wyoming mountain passes. However, concerns for out of control trucks on the mountain passes persist. The objective of this study is to evaluate the safety effectiveness of steep grade advance warning signs for trucks on Wyoming mountain passes. The safety evaluation was carried out by implementing a zero-inflated negative binomial modeling technique for predicting truck crashes on mountain passes. The outcome was two models that showed the risk of runaway truck accidents were high at locations where either the grades were steep and long or the grades were long with multiple vertical curves. The analysis showed the current advance warning systems were not significantly impacting truck crash risks at the high risk locations. The study, therefore, recommends some improvements to the current advanced warning signs or implementing an improved Federal Highway Administration Grade Severity Rating System based warning system that will significantly improve truck safety at the hazardous locations. The study informs policy makers on the safety issues on Wyoming Mountain passes with regards to runaway trucks and makes recommendations for reducing the risk of runaway truck crashes on mountain passes.
  • An analysis of escalator-related injuries in metro stations in China,
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Yingying Xing, Sunanda Dissanayake, Jian Lu, Sijin Long, Yuexin Lou In order to reduce the probability and severity of escalator-related injuries and enhance the safety of passengers, this study analyzed 950 escalator-related injuries in Guangzhou metro stations to identify the characteristics and the risk factors associated with escalator-related injuries in China. The data extracted from Management Information System of Guangzhou Metro covers the site and time of the accident, age and gender of the victims, escalator condition and injury information. The results from the statistical analysis indicated that the majority of the escalator-related injuries was caused by failing to stand firm (287 cases, 30.2%), passengers carrying out other tasks (214 cases, 22.5%), not holding the handrail (168 cases, 17.7%) and unhealthy passengers (18 cases, 9.3%). Age was associated with all factors except for need for an ambulance and the distribution law of these factors differed with age groups. Elderly passengers (aged 66 years and above) accounted for the highest proportion of all injuries (49.1%), and failing to stand firm (18.63%) was the main cause of escalator-related injuries of elderly passengers. The most common mechanism of injury for all age groups was a fall, accounting for (51.0%) injuries. Proportion of injuries caused by a fall increased with age, whereas injuries attributed to entrapment decreased. Female passengers (65.9%) were more likely to be involved escalator-related injuries than male passengers (34.1%), while male passengers were more likely to have accidents caused by unhealthy physical condition than female passengers. These results based on the analysis of current accident data can be used to help metro operation corporation develop effective injury prevention measures and document the need for continued improvement of escalator safety in metro stations.
  • Characteristics of Single Vehicle Crashes with a Teen Driver in South
           Carolina, 2005–2008
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Ruth A. Shults, Gwen Bergen, Tracy J. Smith, Larry Cook, John Kindelberger, Bethany West ObjectiveTeens’ crash risk is highest in the first years of independent driving. Circumstances surrounding fatal crashes have been widely documented, but less is known about factors related to nonfatal teen driver crashes. This study describes single vehicle nonfatal crashes involving the youngest teen drivers (15–17 years), compares these crashes to single vehicle nonfatal crashes among adult drivers (35–44 years) and examines factors related to nonfatal injury producing crashes for teen drivers.MethodsPolice crash data linked to hospital inpatient and emergency department data for 2005–2008 from the South Carolina Crash Outcomes Data Evaluation System (CODES) were analyzed. Nonfatal, single vehicle crashes involving passenger vehicles occurring on public roadways for teen (15–17 years) drivers were compared with those for adult (35–44 years) drivers on temporal patterns and crash risk factors per licensed driver and per vehicle miles traveled. Vehicle miles traveled by age group was estimated using data from the 2009 National Household Travel Survey. Multivariable log-linear regression analysis was conducted for teen driver crashes to determine which characteristics were related to crashes resulting in a minor/moderate injury or serious injury to at least one vehicle occupant.ResultsCompared with adult drivers, teen drivers in South Carolina had 2.5 times the single vehicle nonfatal crash rate per licensed driver and 11 times the rate per vehicle mile traveled. Teen drivers were nearly twice as likely to be speeding at the time of the crash compared with adult drivers. Teen driver crashes per licensed driver were highest during the afternoon hours of 3:00–5:59 pm and crashes per mile driven were highest during the nighttime hours of 9:00–11:59 pm. In 66% of the teen driver crashes, the driver was the only occupant. Crashes were twice as likely to result in serious injury when teen passengers were present than when the teen driver was alone. When teen drivers crashed while transporting teen passengers, the passengers were>5 times more likely to all be restrained if the teen driver was restrained. Crashes in which the teen driver was unrestrained were 80% more likely to result in minor/moderate injury and 6 times more likely to result in serious injury compared with crashes in which the teen driver was restrained.ConclusionsDespite the reductions in teen driver crashes associated with Graduated Driver Licensing (GDL), South Carolina’s teen driver crash rates remain substantially higher than those for adult drivers. Established risk factors for fatal teen driver crashes, including restraint nonuse, transporting teen passengers, and speeding also increase the risk of nonfatal injury in single vehicle crashes. As South Carolina examines strategies to further reduce teen driver crashes and associated injuries, the state could consider updating its GDL passenger restriction to either none or one passenger
  • Analysis of real-time crash risk for expressway ramps using traffic,
           geometric, trip generation, and socio-demographic predictors
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Ling Wang, Mohamed Abdel-Aty, Jaeyoung Lee, Qi Shi There have been numerous studies on real-time crash prediction seeking to link real-time crash likelihood with traffic and environmental predictors. Nevertheless, none has explored the impact of socio-demographic and trip generation parameters on real-time crash risk. This study analyzed the real-time crash risk for expressway ramps using traffic, geometric, socio-demographic, and trip generation predictors. Two Bayesian logistic regression models were utilized to identify crash precursors and their impact on ramp crash risk. Meanwhile, four Support Vector Machines (SVM) were applied to predict crash occurrence. Bayesian logistic regression models and SVMs commonly showed that the models with the socio-demographic and trip generation variables outperform their counterparts without those parameters. It indicates that the socio-demographic and trip generation parameters have significant impact on the real-time crash risk. The Bayesian logistic regression model results showed that the logarithm of vehicle count, speed, and percentage of home-based-work production had positive impact on crash risk. Meanwhile, off-ramps or non-diamond-ramps experienced higher crash potential than on-ramps or diamond-ramps, respectively. Though the SVMs provided good model performance, the SVM model with all variables (i.e., all traffic, geometric, socio-demographic, and trip generation variables) had an overfitting problem. Therefore, it is recommended to build SVM models based on significant variables identified by other models, such as logistic regression.
  • Simulating uni- and bi-directional pedestrian movement on stairs by
           considering specifications of personal space
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): M.W. Liu, S.M. Wang, Y. Oeda, T.N. Sumi This paper presents an enhanced model that considers the specifications of personal space to describe uni- and bi-directional pedestrian movement on stairs. The shape of the personal space of each pedestrian is regarded as an oval shape, which is composed of four arcs, to precisely quantify movements. Specific models that facilitate the simulation of movement include adjustments to individual speeds based on the proximity of other members, conflict avoidance, overtaking, and direction finding. By implementing these parameters in the simulation, basic data concerning these movement behaviours were collected from the experiment, which was carried out at one a Shanghai subway station. Twenty-four young college students participated in this experiment. Numerical simulation results for a stochastic case under those parameters were obtained. The fundamental diagrams and moving behaviours according to different proportions of ascending and descending pedestrians are analysed and discussed. The results indicate that the simulation platform for personal space can serve as a useful tool to evaluate pedestrian movement on stairs.
  • Data and methods for studying commercial motor vehicle driver fatigue,
           highway safety and long-term driver health
    • Abstract: Publication date: Available online 9 March 2018Source: Accident Analysis & PreventionAuthor(s): Hal S. Stern, Daniel Blower, Michael L. Cohen, Charles A. Czeisler, David F. Dinges, Joel B. Greenhouse, Feng Guo, Richard J. Hanowski, Natalie P. Hartenbaum, Gerald P. Krueger, Melissa M. Mallis, Richard F. Pain, Matthew Rizzo, Esha Sinha, Dylan S. Small, Elizabeth A. Stuart, David H. Wegman This article summarizes the recommendations on data and methodology issues for studying commercial motor vehicle driver fatigue of a National Academies of Sciences, Engineering, and Medicine study. A framework is provided that identifies the various factors affecting driver fatigue and relating driver fatigue to crash risk and long-term driver health. The relevant factors include characteristics of the driver, vehicle, carrier and environment. Limitations of existing data are considered and potential sources of additional data described. Statistical methods that can be used to improve understanding of the relevant relationships from observational data are also described. The recommendations for enhanced data collection and the use of modern statistical methods for causal inference have the potential to enhance our understanding of the relationship of fatigue to highway safety and to long-term driver health.
  • Exploring the temporal stability of global road safety statistics
    • Abstract: Publication date: Available online 21 February 2018Source: Accident Analysis & PreventionAuthor(s): Loukas Dimitriou, Paraskevas Nikolaou, Constantinos Antoniou Given the importance of rigorous quantitative reasoning in supporting national, regional or global road safety policies, data quality, reliability, and stability are of the upmost importance. This study focuses on macroscopic properties of road safety statistics and the temporal stability of these statistics at a global level. A thorough investigation of two years of measurements was conducted to identify any unexpected gaps that could highlight the existence of inconsistent measurements. The database used in this research includes 121 member countries of the United Nation (UN-121) with a population of at least one million (smaller country data shows higher instability) and includes road safety and socioeconomic variables collected from a number of international databases (e.g. WHO and World Bank) for the years 2010 and 2013. For the fulfillment of the earlier stated goal, a number of data visualization and exploratory analyses (Hierarchical Clustering and Principal Component Analysis) were conducted. Furthermore, in order to provide a richer analysis of the data, we developed and compared the specification of a number of Structural Equation Models for the years 2010 and 2013. Different scenarios have been developed, with different endogenous variables (indicators of mortality rate and fatality risk) and structural forms. The findings of the current research indicate inconsistency phenomena in global statistics of different instances/years. Finally, the results of this research provide evidence on the importance of careful and systematic data collection for developing advanced statistical and econometric techniques and furthermore for developing road safety policies.
  • Fatigue as a mediator of the relationship between quality of life and
           mental health problems in hospital nurses
    • Abstract: Publication date: Available online 14 February 2018Source: Accident Analysis & PreventionAuthor(s): Ahmad Bazazan, Iman Dianat, Zohreh Mombeini, Aydin Aynehchi, Mohammad Asghari Jafarabadi The aims of this study were to investigate the relationships among quality of life (QoL), mental health problems and fatigue among hospital nurses, and to test whether fatigue and its multiple dimensions would mediate the effect of QoL on mental health problems. Data were collected using questionnaires (including the World Health Organization Quality of Life-BREF [WHOQOL-BREF], General Health Questionnaire [GHQ-12] and Multidimensional Fatigue Inventory [MFI-20] for evaluation of QoL, mental health problems and fatigue, respectively) from 990 Iranian hospital nurses, and analysed by generalized structural equation modelling (GSEM). The results indicated that QoL, mental health problems and fatigue were interrelated, and supported the direct and indirect (through fatigue) effects of QoL on mental health problems. All domains of the WHOQOL-BREF, and particularly physical (sleep problems), psychological (negative feelings) and environmental health (leisure activities) domains, were strongly related to the mental health status of the studied nurses. Fatigue and its multiple dimensions partially mediated the relationship between QoL and mental health problems. The results highlighted the importance of physical, psychological and environmental aspects of QoL and suggested the need for potential interventions to improve fatigue (particularly physical fatigue along with mental fatigue) and consequently mental health status of this working population. The findings have possible implications for nurses' health and patient safety outcomes.
  • Prevalence of operator fatigue in winter maintenance operations
    • Abstract: Publication date: Available online 3 February 2018Source: Accident Analysis & PreventionAuthor(s): Matthew C. Camden, Alejandra Medina-Flintsch, Jeffrey S. Hickman, James Bryce, Gerardo Flintsch, Richard J. Hanowski Similar to commercial motor vehicle drivers, winter maintenance operators are likely to be at an increased risk of becoming fatigued while driving due to long, inconsistent shifts, environmental stressors, and limited opportunities for sleep. Despite this risk, there is little research concerning the prevalence of winter maintenance operator fatigue during winter emergencies. The purpose of this research was to investigate the prevalence, sources, and countermeasures of fatigue in winter maintenance operations. Questionnaires from 1043 winter maintenance operators and 453 managers were received from 29 Clear Road member states. Results confirmed that fatigue was prevalent in winter maintenance operations. Over 70% of the operators and managers believed that fatigue has a moderate to significant impact on winter maintenance operations. Approximately 75% of winter maintenance operators reported to at least sometimes drive while fatigued, and 96% of managers believed their winter maintenance operators drove while fatigued at least some of the time. Furthermore, winter maintenance operators and managers identified fatigue countermeasures and sources of fatigue related to winter maintenance equipment. However, the countermeasures believed to be the most effective at reducing fatigue during winter emergencies (i.e., naps) were underutilized. For example, winter maintenance operators reported to never use naps to eliminate fatigue. These results indicated winter maintenance operations are impacted by operator fatigue. These results support the increased need for research and effective countermeasures targeting winter maintenance operator fatigue.
  • Modeling when and where a secondary accident occurs
    • Abstract: Publication date: Available online 2 February 2018Source: Accident Analysis & PreventionAuthor(s): Junhua Wang, Boya Liu, Ting Fu, Shuo Liu, Joshua Stipancic The occurrence of secondary accidents leads to traffic congestion and road safety issues. Secondary accident prevention has become a major consideration in traffic incident management. This paper investigates the location and time of a potential secondary accident after the occurrence of an initial traffic accident. With accident data and traffic loop data collected over three years from California interstate freeways, a shock wave-based method was introduced to identify secondary accidents. A linear regression model and two machine learning algorithms, including a back-propagation neural network (BPNN) and a least squares support vector machine (LSSVM), were implemented to explore the distance and time gap between the initial and secondary accidents using inputs of crash severity, violation category, weather condition, tow away, road surface condition, lighting, parties involved, traffic volume, duration, and shock wave speed generated by the primary accident. From the results, the linear regression model was inadequate in describing the effect of most variables and its goodness-of-fit and accuracy in prediction was relatively poor. In the training programs, the BPNN and LSSVM demonstrated adequate goodness-of-fit, though the BPNN was superior with a higher CORR and lower MSE. The BPNN model also outperformed the LSSVM in time prediction, while both failed to provide adequate distance prediction. Therefore, the BPNN model could be used to forecast the time gap between initial and secondary accidents, which could be used by decision makers and incident management agencies to prevent or reduce secondary collisions.
  • Impact of real-time traffic characteristics on crash occurrence:
           Preliminary results of the case of rare events
    • Abstract: Publication date: Available online 5 January 2018Source: Accident Analysis & PreventionAuthor(s): Athanasios Theofilatos, George Yannis, Pantelis Kopelias, Fanis Papadimitriou Considerable efforts have been made from researchers and policy makers in order to explain road crash occurrence and improve road safety performance of highways. However, there are cases when crashes are so few that they could be considered as rare events. In such cases, the binary dependent variable is characterized by dozens to thousands of times fewer events (crashes) than non-events (non-crashes). This paper attempts to add to the current knowledge by investigating crash likelihood by utilizing real-time traffic data and by proposing a framework driven by appropriate statistical models (Bias Correction and Firth method) in order to overcome the problems that arise when the number of crashes is very low. Under this approach instead of using traditional logistic regression methods, crashes are considered as rare events In order to demonstrate this approach, traffic data were collected from three random loop detectors in the Attica Tollway (“Attiki Odos”) located in Greater Athens Area in Greece for the 2008–2011 period. The traffic dataset consists of hourly aggregated traffic data such as flow, occupancy, mean time speed and percentage of trucks in traffic. This study demonstrates the application and findings of our approach and revealed a negative relationship between crash occurrence and speed in crash locations. The method and findings of the study attempt to provide insights on the mechanism of crash occurrence and also to overcome data considerations for the first time in safety evaluation of motorways.
  • Diagnostic analysis of the effects of weather condition on pedestrian
           crash severity
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Xiaoqi Zhai, Helai Huang, N.N. Sze, Ziqi Song, Kai Kwong Hon Pedestrians are vulnerable to severe injury and mortality in road crashes. Numerous studies have attempted to identify factors contributing to crashes and pedestrian injury risks. As an active transport mode, the act of walking is sensitive to changes in weather conditions. However, comprehensive real-time weather data are often unavailable for road safety analysis. In this study, we used a geographical information system approach to integrate high-resolution weather data, as well as their corresponding temporal and spatial distributions, with crash data. Then, we established a mixed logit model to determine the association between pedestrian crash severity and possible risk factors. The results indicate that high temperature and the presence of rain were associated with a higher likelihood of Killed and Severe Injury (KSI) crashes. Also, we found the interaction effects of weather condition (hot weather and presence of rain) on the association between pedestrian crash severity and pedestrian and driver behaviors to be significant. For instance, the effects of jaywalking and risky driving behavior on crash severity were more prevalent under rainy conditions. In addition, the effects of driver inattention and reckless crossing were more significant in hot weather conditions. This has critical policy implications for the development and implementation of proactive traffic management systems. For instance, real-time weather and traffic data should be incorporated into dynamic message signs and in-vehicle warning systems. Doing so will enhance the levels of safety awareness of drivers and pedestrians, especially in adverse weather conditions. As a result, pedestrian safety can be improved over the long term.
  • Y TXT N DRIVE' Predictors of texting while driving among a sample of
           Ontario youth and young adults
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Erin Berenbaum, Daniel Harrington, Sue Keller-Olaman, Heather Manson Background: Distracted driving is of particular concern among young drivers. According to the 2012 National Highway Traffic Safety Administration (NHTSA) survey, the greatest proportion of distraction prone drivers is within the 16–19 and 20–24 age groups. One relatively new distraction is texting while driving behaviour (TWD). TWD increases the amount of time drivers spend looking away from the road, slows reaction times and increases the risk of collisions by two-fold. To deter this behaviour many distracted driving campaigns focus on highlighting the risks and dangers of distracted driving; however, evidence suggests that youth and young adults continue to engage in TWD despite awareness of the related risks. Previous studies have examined constructs from the theory of planned behaviour as predictors of TWD (e.g., attitudes, intentions). Understanding the full range of factors that may influence this behaviour can inform the development of evidence-based public awareness campaigns and related interventions.Purpose: The purpose of this paper was to examine predictors of TWD behaviour among youth and young adults. We examined constructs from the theory of planned behaviour in addition to the role played by perceived TWD driving skills, experience with collisions due to TWD, descriptive norms (i.e., an individual’s beliefs about a behaviour that are gained as a result of observing the actions of others) and risk perceptions.Methods: An online survey was administered to 2001 Ontario youth and young adults examining potential predictors of TWD behaviour. Regression models were used to examine which key variables were associated with TWD (both reading and sending behaviour) among participants.Results: Overall, regression models had good predictability for reading and sending behaviours. Perceived TWD driving skills and ‘almost getting in a collision due to TWD’ were positively associated with TWD behaviour in the past week (both reading and sending behaviours). Descriptive norms were positively associated with sending text messages while driving in the past week, but were not significant for reading. In contrast, risk perceptions were positively associated with reading text messages in the past week but not sending.Discussion and conclusion: The results from this study highlight constructs that can be used to design interventions to deter young drivers from engaging in TWD. Interventions targeting perceived TWD driving skills and descriptive norms have the potential to be more effective than interventions emphasizing risk perceptions. Future studies are needed to better understand the relationships between these predictors and TWD behaviour among this population.
  • Pedestrian injuries due to collisions with cyclists Melbourne, Australia
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Steve O’Hern, Jennie Oxley Over the past decade in Melbourne the popularity of cycling has increased both as a mode of transport and a recreational activity, while at the same time walking has consistently been the most prevalent form of physical activity. Increasing levels of active transport use and physical activity are seen as important public health issues, particularly as the rate of urbanisation continues to grow throughout the world.To date there has been limited research conducted in Australia looking at the prevalence of pedestrian injuries resulting from collisions with cyclists. However there is a potential for the issues surrounding pedestrian and cyclist conflict to increase, given the growing uptake of these modes of transport, the continued densification of the urban environment and the lack of cycling specific infrastructure in many Australian capital cities. This study investigated the prevalence of pedestrian injuries resulting from collisions with cyclists in Melbourne, Australia. The intention was to quantify the extent of these collisions and identify if the rate of collisions was increasing, which may highlight a growing road safety issue. Furthermore the study sought to identify any unique characteristic and injury outcomes associated with this collision type.Aggregate analyses of two Victorian data sources were undertaken to enhance our understanding of pedestrian injuries resulting from collisions with cyclists, the Victorian Injury Surveillance Unit (VISU) and Victorian Police Report Crash Data (Crash Stats).The analysis demonstrated that over the past ten years there does not appear to have been a substantial increase in the number of pedestrian injuries resulting from collisions with cyclists. Furthermore the prevalence of injuries was small, especially when compared to injuries sustained by pedestrians from collisions with motor vehicles. The findings highlight that efforts to increase active transport participation should be encouraged and there may be situations where is it suitable to increase interaction and sharing of space between pedestrians and cyclists.
  • Use of multiple data sources to identify specific drugs and other factors
           associated with drug and alcohol screening of fatally injured motor
           vehicle drivers
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): T. Bunn, M. Singleton, I-Chen Chen ObjectiveDrugged driving crashes have significantly increased over the past two decades. The objectives of this study were to identify and characterize the drugs present in motor vehicle driver fatalities using multiple surveillance data sources; assess concordance of the data sources in identifying drug presence; and identify demographic and crash factors associated with drug and alcohol screening in fatally injured motor vehicle drivers.MethodsFatality Analysis Reporting System (FARS), Collision Report Analysis for Safer Highways (CRASH), and mortality data sets were linked; drug screening and positive drug screens were identified. Chi-square and conditional logistic regression were performed.ResultsThe use of FARS data identified the majority of positive drug screens in the linked data set. Supplementation of FARS data with death certificate and CRASH data increased identification of specific drugs and drug classes detected among fatally injured motor vehicle drivers, although there was a low concordance among the data sources. Alcohol and depressants such as alprazolam had the highest frequencies among fatally injured drivers. Speeding, lack of occupant restraints, young age, commercial truck drivers, and speeding were all factors associated with increased odds of the fatally injured driver being drug or alcohol screened.ConclusionsThese findings indicate that FARS drug information data may be strengthened through increased autopsy and consultation with medical examiners to better understand and interpret decedent toxicology testing results, and that states with low driver drug testing rates should consider mandatory driver drug testing in fatal crashes.
  • A spatiotemporal deep learning approach for citywide short-term crash risk
           prediction with multi-source data
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Jie Bao, Pan Liu, Satish V. Ukkusuri The primary objective of this study is to investigate how the deep learning approach contributes to citywide short-term crash risk prediction by leveraging multi-source datasets. This study uses data collected from Manhattan in New York City to illustrate the procedure. The following multiple datasets are collected: crash data, large-scale taxi GPS data, road network attributes, land use features, population data and weather data. A spatiotemporal convolutional long short-term memory network (STCL-Net) is proposed for predicting the citywide short-term crash risk. A total of nine prediction tasks are conducted and compared, including weekly, daily and hourly models with 8 × 3, 15 × 5 and 30 × 10 grids, respectively. The results suggest that the prediction performance of the proposed model decreases as the spatiotemporal resolution of prediction task increases. Moreover, four commonly-used econometric models, and four state-of-the-art machine-learning models are selected as benchmark methods to compare with the proposed STCL-Net for all the crash risk prediction tasks. The comparative analyses suggest that in general the proposed STCL-Net outperforms the benchmark methods for different crash risk prediction tasks in terms of higher prediction accuracy rate and lower false alarm rate. The results verify that the proposed spatiotemporal deep learning approach performs better at capturing the spatiotemporal characteristics for the citywide short-term crash risk prediction. In addition, the comparative analyses also reveal that econometric models perform better than machine-learning models in weekly crash risk prediction tasks, while they exhibit worse results than machine-learning models in daily crash risk prediction tasks. The results can potentially guide transportation safety engineers to select appropriate methods for different crash risk prediction tasks.
  • Crash injury severity analysis using a two-layer Stacking framework
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Jinjun Tang, Jian Liang, Chunyang Han, Zhibin Li, Helai Huang Crash injury severity analysis is useful for traffic management agency to further understand severity of crashes. A two-layer Stacking framework is proposed in this study to predict the crash injury severity: The fist layer integrates advantages of three base classification methods: RF (Random Forests), AdaBoost (Adaptive Boosting), and GBDT (Gradient Boosting Decision Tree); the second layer completes classification of crash injury severity based on a Logistic Regression model. A total of 5538 crashes were recorded at 326 freeway diverge areas. In the model calibration, several parameters including the number of trees in three base classification methods, learning rate, and regularization coefficient are optimized via a systematic grid search approach. In the model validation, the performance of the Stacking model is compared with several traditional models including the Support Vector Machine (SVM), Multi-Layer Perceptron (MLP) and Random Forests (RF) in the multi classification experiments. The prediction results show that Stacking model achieves superior performance evaluated by two indicators: accuracy and recall. Furthermore, all the factors used in severity prediction are classified into different categories according to their influence on the results, and sensitivity analysis of several significant factors is finally implemented to explore the impact of their value variation on the prediction accuracy.
  • Investigating proximity of crash locations to aging pedestrian residences
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Henrick J. Haule, Thobias Sando, Angela E. Kitali, Robert Richardson Many campaigns promote walking for recreation, work, and general-purpose trips for health and environmental benefits. This study investigated factors that influence the occurrence of crashes involving elderly pedestrians in relation to where they reside. Using actual pedestrian residential addresses, a Google integrated GIS-based method was developed for estimating distances from crash locations to pedestrian residences. A generalized linear mixed model (GLMM) was used to evaluate the effect of factors associated with residences, such as age group, roadway features, and demographic characteristics on the proximity of crash locations. Results indicated that the proximity of crash locations to pedestrian residences is influenced by the pedestrian age, gender, roadway traffic volume, seasons of the year, and pedestrian residence demographic characteristics. The findings of this study can be used by transportation agencies to develop plans that enhance aging pedestrian safety and improve livability.
  • Computer-based hazard perception test scores are associated with the
           frequency of heavy braking in everyday driving
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Andrew Hill, Mark S. Horswill, John Whiting, Marcus O. Watson Computer-based hazard perception tests are used in a number of countries as part of the driver licensing processes, and hence evaluating the validity of such tests is crucial. One strategy for assessing the validity of the scores generated by a hazard perception test is to determine whether they can predict on-road driving performance. Only a few prior studies have attempted this, all relying on the subjective ratings of an examiner who was present during a single brief drive and was not blind to the driver’s demographic characteristics, potentially contaminating the outcomes. Additionally, only one such study focused on the most relevant participant group with respect to the validity of tests used in licencing processes, namely young drivers. We sought to remedy this situation in the present project by measuring young drivers’ performance over an extended period of everyday driving via g-force triggered video cameras (“dashcams”) installed in their own vehicles. As a precursor to the dashcam study itself, we developed a new computerized hazard perception test and assessed the validity of its scores by more traditional means (Study 1). As expected, test scores distinguished between high-risk and lower-risk driver groups, and correlated with scores on an established hazard perception test previously shown to predict crash risk. In the subsequent dashcam study (Study 2), the frequency of heavy-braking events (controlling for distance driven) was used as a more objective measure of driving performance. Results indicated that drivers with higher rates of heavy braking had slower hazard perception response times, further supporting the use of these scores as a valid measure of drivers’ ability to exercise hazard perception skill during real driving. More generally, this study also demonstrates the viability of using low-cost off-the-shelf dashcams to measure real-world driving behaviour.
  • Are drivers ready for traffic enforcement drones'
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Ariel Rosenfeld Traffic enforcement drones reduce high-risk driving behavior which often leads to traffic crashes. However, the introduction of drones may face a public acceptance challenge which may severely hinder their potential impact. In this paper, we report and discuss the results of a drivers’ survey, administered both in the US and Israel, regarding the benefits, concerns and policy considerations for the deployment of traffic enforcement drones. The results show that drivers perceive traffic enforcement drones as significantly more efficient and deterring compared to current aerial traffic enforcement resources (i.e., police helicopters) and comparable in quality to speed cameras. Privacy and safety are the main concerns expressed with regards to such technology, yet these concerns have been shown to be significantly relieved if traffic enforcement drones are restricted to interurban spaces. Interestingly, only a few Israeli participants object to the introduction of traffic enforcement drones to the traffic police's arsenal compared to about half of American participants. These results combine to suggest several practical guidelines for decision-makers which can facilitate the deployment of this potentially life-saving technology in the field.
  • A multivariate spatial approach to model crash counts by injury severity
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Kun Xie, Kaan Ozbay, Hong Yang Conventional safety models rely on the assumption of independence of crash data, which is frequently violated. This study develops a novel multivariate conditional autoregressive (MVCAR) model to account for the spatial autocorrelation of neighboring sites and the inherent correlation across different crash types. Manhattan, which is the most densely populated urban area of New York City, is used as the study area. Census tracts are used as the basic geographic units to capture crash, transportation, land use, and demo-economic data. The specification of the proposed multivariate model allows for jointly modeling counts of various crash types that are classified according to injury severity. Results of Moran’s I tests show the ability of the MVCAR model to capture the multivariate spatial autocorrelation among different crash types. The MVCAR model is found to outperform the others by presenting the lowest deviance information criterion (DIC) value. It is also found that the unobserved heterogeneity was mostly attributed to spatial factors instead of non-spatial ones and there is a strong shared geographical pattern of risk among different crash types.
  • The effects of repetitive presentation of specific hazards on eye
           movements in hazard perception training, of experienced and
           young-inexperienced drivers
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Naomi Kahana-Levy, Sara Shavitzky-Golkin, Avinoam Borowsky, Eli Vakil Recent evidence shows that compared to experienced drivers, young-inexperienced drivers are more likely to be involved in a crash mainly due to their poor hazard perception (HP) abilities. This skill develops with experience and may be developed through training. We assumed that as any other skill, HP developed through implicit learning. Nevertheless, current training methods, rely on deliberate learning where young-inexperienced drivers are instructed what hazards that they should seek and where they might be located. In this exploratory study, we investigated the effectiveness of a novel training procedure, in which learners were repeatedly exposed to target video clips of driving scenarios embedded within filler scenarios. Each of the target videos included scenarios of either a visible hazard, a hidden materialized hazard or hidden unmaterialized hazard. Twenty-three young-inexperienced drivers and 35 experienced drivers participated in training session followed by a learning transference testing session and 24 additional young-inexperienced drivers participated only in the transference testing session with no training, during which participants were shown novel hazards video clips. Participants responded by pressing a button when they identified a hazard. Eye movement was also tracked using fixations patterns as a proxy to evaluate HP performance. During training, young-inexperienced drivers gradually increased their focus on visible materialized hazards but exhibited no learning curve with respect to hidden hazards. During the learning transference session, both trained groups focused on hazards earlier compared to untrained drivers. These results imply that repetitive training may facilitate HP acquisition among young-inexperienced drivers. Patterns concerning experienced drivers are also discussed.
  • A comparison of hazard perception and hazard prediction tests across
           China, Spain and the UK
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Petya Ventsislavova, David Crundall, Thom Baguley, Candida Castro, Andrés Gugliotta, Pedro Garcia-Fernandez, Wei Zhang, Yutao Ba, Qiucheng Li Hazard perception (HP) is the ability to spot on-road hazards in time to avoid a collision. This skill is traditionally measured by recording response times to hazards in video clips of driving, with safer, experienced drivers often out-performing inexperienced drivers. This study assessed whether HP test performance is culturally specific by comparing Chinese, Spanish and UK drivers who watched clips filmed in all three countries. Two test-variants were created: a traditional HP test (requiring timed hazard responses), and a hazard prediction test, where the film is occluded at hazard-onset and participants predict what happens next. More than 300 participants, across the 3 countries, were divided into experienced and inexperienced-driver groups. The traditional HP test did not discriminate between experienced and inexperienced drivers, though participant nationality influenced the results with UK drivers reporting more hazards than Chinese drivers. The hazard prediction test, however, found experienced drivers to out-perform inexperienced drivers. No differences were found for nationality, with all nationalities being equally skilled at predicting hazards. The results suggest that drivers’ criterion level for responding to hazards is culturally sensitive, though their ability to predict hazards is not. We argue that the more robust, culturally-agnostic, hazard prediction test appears better suited for global export.
  • Driven to succeed: Improving adolescents’ driving behaviors through a
           personal narrative-based psychosocial intervention in Serbia
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Rajiv N. Rimal, Hagere Yilma, Nargis Ryskulova, Sarah Geber Globally, more adolescents die from road traffic fatalities than from any other cause, and males are significantly more vulnerable than females. Driver education interventions directed at males are less likely to succeed than those directed at females, and stronger optimistic bias and overconfidence bias have been implicated as likely reasons. We report results from a quasi-experiment conducted in Serbia, targeting male and female adolescents. Stratified by size, forty schools were randomly assigned to either a personal-narrative intervention or a no-intervention control arm. Data were collected before the intervention (N = 1449) and again six months later (N = 1072). Risk perceptions improved for both males and females, and injunctive norms improved for females. Improvements in overconfidence bias and descriptive norms were predictive of improvements in high-risk driving behaviors. A significant interaction between improvements in injunctive norms and the intervention revealed that males whose injunctive norms improved were significantly more likely to be affected by the intervention, compared to the other groups. Implications for interventions are discussed.
  • Neighborhood-level factors affecting seat belt use
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Amin Mohamadi Hezaveh, Christopher R. Cherry Despite the well-known safety benefits of seat belt use, some vehicle occupants still do not use them. This is a challenge in Tennessee, which has a lower seat belt use rate compared to the United States national average. Roadside observations and interviews are the two main sources for estimating seat belt use rate and have several limitations (e.g., small sample size, social desirability bias). To address these limitations, we attributed seat belt use of individuals who were involved in traffic crashes (N = 542,776) to their corresponding home-addresses. Home-addresses were retrieved from police crash reports and were geocoded, and assigned to their corresponding census tract revealing added information about the spatial distribution of seat belt use and socioeconomics of the areas surrounding the crash victim’s home. The average seat belt use rate in the metropolitan area was 88% and for the non-metropolitan area was 87%. A Tobit model was used to evaluate the relationship between the seat belt use rate for both drivers and passengers over 16 years old, with neighborhood sociodemographic variables. Population, age cohorts, race, household vehicles’ ownership, household size, and education were among the predictors of the seat belt use rate. Results of this analysis could be used in safety campaign design to reach specific geographic areas and groups with a lower seat belt use rate.
  • Assessing the impacts of enriched information on crash prediction
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Monique Martins Gomes, Ali Pirdavani, Tom Brijs, Cira Souza Pitombo While high road safety performing countries base their effective strategies on reliable data, in developing countries the unavailability of essential information makes this task challenging. As a result, this drawback has led researchers and planners to face dilemmas of “doing nothing” or “doing ill”, therefore restricting models to data availability, often limited to socio-economic and demographic variables. Taking this into account, this study aims to demonstrate the potential improvements in spatial crash prediction model performance by enhancing the explanatory variables and modelling casualties as a function of a more comprehensive dataset, especially with an appropriate exposure variable. This includes experimental work, where models based on available information from São Paulo, Brazil, and Flanders, the Dutch speaking area of Belgium, are developed and compared with each other. Prediction models are developed within the framework of Geographically Weighted Regression with the Poisson distribution of errors. Moreover, casualties and fatalities as the response variables in the models developed for Flanders and São Paulo, respectively, are divided into two sets based on the transport mode, called active (i.e., pedestrians and cyclists) and motorized transport (i.e., motorized vehicle occupants). In order to assess the impacts of the enriched information on model performance, casualties are firstly associated with all available variables for São Paulo and the corresponding ones for Flanders. In the next step, prediction models are developed only for Flanders considering all the available information in the Flemish dataset. Findings showed that by adding the supplementary data, reductions of 20% and 25% for motorized transport, and 25% and 35% for active transport resulted in AICc and MSPE, respectively. Considering the practical aspects, results could help identify hotspots and relate most influential factors, suggesting sites and data, which should be prioritized in future local investigations. Besides minimizing costs with data collection, it could help policy makers to identify, implement and enforce appropriate countermeasures.
  • Effects of an in-vehicle eco-safe driving system on drivers’ glance
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Xiaomeng Li, Atiyeh Vaezipour, Andry Rakotonirainy, Sebastien Demmel We have designed a new in-vehicle eco-safe driving system and shown its effectiveness in prompting drivers to execute a fuel-saving and safe driving style (Vaezipour et al., 2018, submitted for publication). However, the system could also bring potential negative outcomes, i.e. driver distraction. This simulator study investigated drivers’ glance behaviours as indicators of driver distraction when using our Eco-Safe Human-Machine-Interface (HMI). Four types of eco-safe information display conditions (baseline, advice only, feedback only, both advice and feedback) were tested on different traffic situations with varied road traffic complexity. Results showed that the eco-safe HMI system did not cause visual distraction. In contrast, the advice only or feedback only information improved forward gazing on the roadway. In addition, drivers tended to adapt their visual scanning strategies according to the traffic situations. In the car-following situation they paid longer glances to the forward roadway, while in the intersections they spent more time to look at the HMI system. The findings indicated that our eco-safe driving system improved drivers’ eco-safe behaviours and meanwhile enhanced their visual attention on road while no evidence showed that drivers were distracted by it.
  • “Mate! I’m running 10 min late”: An investigation into the
           self-regulation of mobile phone tasks while driving
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Oscar Oviedo-Trespalacios, Md. Mazharul Haque, Mark King, Simon Washington The adaptive behaviour of mobile phone distracted drivers has been a topic of much discussion in the recent literature, but the mechanisms of behavioural adaptation are still unclear. This study investigated the influence of driving demands, secondary task characteristics, and personal characteristics on behavioural adaptation of mobile phone distracted drivers. In particular, distracted drivers’ self-regulation at strategic, tactical, and operational levels was investigated through a driving simulator experiment. In a high-fidelity driving simulator, participants driving through various driving conditions (e.g. interactions with pedestrian crossings, signalized intersections, merging ramps, roundabouts, etc.) needed to decide where and how to perform the following four mobile phone tasks: (a) ring a doctor and cancel an appointment, (b) text a friend and tell him/her that the participant will be arriving 10 min late, (c) share the doctor’s phone number with a friend, and (d) take a ‘selfie’. At a strategic level, the decision to pull over was modelled as a function of self-reported personal/attitudinal characteristics with a logistic regression model. Similarly, tactical self-regulation (decision to engage in a task while driving in a specific situation) and operational self-regulation (decision to temporarily stop the mobile phone task) were modelled as a function of driving demands and personal/attitudinal characteristics using a random-effects logistic regression model, which accounts for correlations resulting from multiple observations of a driver. Results suggest that tactical self-regulation is more common among distracted drivers followed by operational and strategic self-regulation. Personal beliefs regarding how safe it is to use the mobile phone for texting/browsing while driving were predictors of self-regulation for all levels. Drivers were observed to use the mobile phone more when the driving demands are low, e.g. while stopped at an intersection. This research suggests that distracted drivers engage in various levels of self-regulation, and future research could be focused on further theoretical refinement and development of technology-based interventions.
  • Investigating factors affecting riders’ behaviors of occupying motorized
           vehicle lanes on urban streets
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Weihua Zhang, Chang Zhou, Wenjuan Huang, Hu Tao, Kun Wang, Zhongxiang Feng, Zhe Hu The violation activity of non-motorized vehicles riding in motorized vehicle lanes interferes roadway traffic serious, as it can not only seriously depreciate the efficiency of motorized vehicle traffic, but also raise possibility of triggering traffic accidents. The primary purpose of this study was to investigate intrinsic features of unlawful non-motorized vehicles' violation behaviors of riding on motorized vehicle lanes. The binary logistic regression model was proposed to find inherent reasons of triggering such misbehaviors. The misbehaviors of non-motorized vehicles (including regular bicycles, electric bicycles and human-powered tricycles) at seven sections, located at Hefei, China, were collected and studied. The experimental results indicate that male traffic participants exhibit higher rates of traffic violations than females, and rainy days shows higher misbehaviors than sunny and cloudy days. Another finding is that morning peak violation rate is higher than the evening peak and non-peak hours due to the fact people are in hurry for work. The traffic density of motorized vehicles and the traffic density of non-motorized vehicles strongly affect illegal occupancy behavior. The effect of dividing strip type and non-motorized vehicle type on lane illegal occupancy behavior are significant. We find that the average lane illegal occupancy rate of non-motorized vehicle is 36.1% which suggests that over one-third of non-motorized riders violate traffic rules. The findings of this study can help traffic authorities, road construction departments and traffic participants perform effective and efficient measurements to improve road traffic safety.
  • Traffic climate, driver behaviour, and accidents involvement in China
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Wenhui Chu, Chaozhong Wu, Charles Atombo, Hui Zhang, Türker Özkan Traffic Climate Scale (TCS) and Positive Driver Behaviours Scale (PDBS) are new measurement tools. The study aims to translate the TCS and PDBS into Chinese and to assess their factor structures in a large sample of licensed motor vehicle drivers in China. A further aim is to investigate the effects of TCS factors on drivers’ behaviours and traffic accidents involvement. Data were collected using an online survey. Participants were 887 fully licensed motor vehicle drivers, including 531 males and 356 females who completed a Chinese translated questionnaire including the TCS, PDBS, Driver Behaviour Questionnaire (DBQ), items related to drivers’ driving records and demographic characteristics. The result of the exploratory factor analysis revealed clear three-factor solution (‘Functionality’, ‘External affective demand’ and ‘Internal requirement’) of TCS with high item loadings and acceptable internal consistency coefficients. The convergent validity of the Chinese TCS was supported by its relationship with driver behaviour factors (violations, errors, lapses and positive behaviours), the traffic accidents involvement and demographic characteristics. The results further show that the external affective demand consistently and positively relate to aberrant behaviours and negatively relate to positive behaviours with indirect positive significant effects on accidents involvement. Functionality is concurrently and negatively related to aberrant behaviours and positively related to positive behaviours with no effects on accidents involvement. The internal requirement is negatively related to aberrant behaviours but, positively related to positive behaviours with positive significant direct effects on accidents involvement.
  • The influence of shoulder characteristics on the safety level of two-lane
           roads: A case-study
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Victoria Gitelman, Etti Doveh, Roby Carmel, Shalom Hakkert Constructing proper shoulders may improve road safety on two-lane roads. Previous research reported crash reductions following shoulder widening. This study aimed to examine the relationship between shoulder characteristics and crash occurrences on two-lane rural roads in Israel. The study database combined information on crash numbers, traffic volumes and road infrastructure characteristics of 3594 road sections. To examine a relationship between shoulder characteristics and crashes, given other road characteristics, two types of statistical models were developed: case-control and negative-binomial regression models, for several crash types. We found that the impacts of shoulder width and other road characteristics on crashes were generally consistent across various models and crash types, where a non-monotonous link between the shoulder width and crashes was typically observed. For various crash types, the models showed an increase in crash risk with an initial extension of the total shoulder, up to 2.2 m, and a consequent decrease in crashes with a further shoulder widening, over 2.2 m, by 2–6% and 1–4%, respectively, for each 0.1 m of shoulder extension. An increase in the width of unpaved shoulders, over 0.9 m, was associated with increased crash risk, in injury and total crashes, by 5% for each 0.1 m of shoulder extension. Lowest crash risks were found for total shoulder widths of about 3 m or more, but also for narrow total shoulders, below 1 m. Conversely, medium total shoulders, of 1.8–2.4 m in width, and unpaved shoulders of over 1 m, were associated with an increase in crash risk and, hence, are not recommended for use. The tools developed in the study may assist in decision-making during the design stages of a new road or upgrading existing road sections, on two-lane local roads.
  • (E-)Cyclists running the red light – The influence of bicycle type and
           infrastructure characteristics on red light violations
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Katja Schleinitz, Tibor Petzoldt, Sophie Kröling, Tina Gehlert, Sebastian Mach Red light running is one of the most common traffic violations among cyclists. From different surveys, we know that about 40% of all cyclists run a red light at least occasionally. However, specific data on red light running of e-bike riders (pedelec and S-pedelec riders), a population of cyclists that has been growing steadily in the past few years in Germany and elsewhere, is largely missing. Similarly unclear is the role of the used infrastructure (e.g., carriageway or bike path) or the intersection type on the riders’ propensity to run the red light. The goal of this study was to investigate the red light running behaviour of three different bicycle types (bicycle, pedelec, S-pedelec) in Germany, with specific focus on various infrastructure characteristics. We reanalysed data obtained in a naturalistic cycling study, in which we observed 90 participants riding their own bicycles (conventional bicycles, pedelecs, S-pedelecs) on their daily trips over four weeks each. The video material of these trips was annotated and analysed with regard to red light running. Overall, our participants experienced nearly 8000 red light situations. In 16.3% of these situations, they ran the red light, with nearly identical rates for cyclists, pedelec and S-pedelec riders. Red light running rates were lowest when cyclists rode on the carriageway, while the complexity of the intersection appeared to play a role as well. In general, red light running was more common when riders were about to turn right instead of turning left or riding straight through the intersection. Interestingly, we also observed a considerable number of cases in which the riders changed their used infrastructure (e.g., from the carriageway onto the pavement) to avoid a red light.
  • Comparative analysis of multiple techniques for developing and
           transferring safety performance functions
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Ahmed Farid, Mohamed Abdel-Aty, Jaeyoung Lee Safety performance functions (SPFs) are crash count prediction models that are used for identifying high crash risk locations, evaluating road safety before and after countermeasure deployment and comparing the safety of alternative site designs. The traditional method of modeling crash counts is negative binomial (NB) regression. Furthermore, the Highway Safety Manual (HSM) provides analytical tools, including NB SPFs, to assess and improve road safety. Even though the HSM’s SPFs are restricted to NB models, the road safety literature is rich with a variety of different modeling techniques. Researchers have calibrated the HSM’s SPFs to local conditions using a calibration method prescribed by the HSM. However, studies in which SPFs are developed and transferred to other localities are uncommon. In this paper, we develop and transfer rural divided multilane highway segment SPFs of Florida, Ohio, Illinois, Minnesota, California, Washington and North Carolina to each state. For every state, NB, zero-inflated NB, Poisson lognormal (PLN), regression tree, random forest (RF), boosting and Tobit models are developed. A hybrid model that coalesces the predictions of both the Tobit and the NB model is proposed and developed as well. All SPFs are transferred to each state and their predictive performances are evaluated to discern which model type is the most transferable. According to the transferability results, there is no single superior model type. However, the Tobit, RF, tree, NB and hybrid models demonstrate better predictive performances than those of the other methods in a considerably large proportion of transferred SPFs.
  • Mind wandering during everyday driving: An on-road study
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Bridget R.D. Burdett, Samuel G. Charlton, Nicola J. Starkey This study was an investigation into mind wandering during everyday driving, and its association with crash patterns. We selected a 25 km route on urban roads for analysis of crashes, and an on-road study of mind wandering by a sample of drivers familiar with the route. We analysed reported crashes on the route over a five year period from New Zealand's crash database. For the on-road study a researcher accompanied 25 drivers on the route, asking them what they were thinking about at 15 predetermined road sections. The road sections were selected to include a range of different speed limits and traffic volumes as well as roundabouts, priority intersections and midblocks. Thought samples were categorised as either mind wandering or driving focus, and triggered by the senses, or internally. The frequencies of mind wandering at different road sections on the route were compared to the frequencies of reported crashes along the same route over the preceding five years. Results showed that although all drivers reported mind wandering, it was more likely to be reported at slower, quieter, less complex road sections. Overall, more crashes were reported at priority intersections and midblocks than at roundabouts, but the crash rate (per road section) was higher at roundabouts, where mind wandering was least likely to be reported. These findings suggest that although drivers' minds wander constantly, driving focus is commanded in demanding situations and in response to the actions of other road users. While mind wandering is ubiquitous, drivers are least likely to report mind wandering at locations showing the highest crash rates. More work is needed to test these findings and to provide direction for road safety interventions.
  • A comparison of bus passengers’ and car drivers’ valuation of casualty
           risk reductions in their routes
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Stefan Flügel, Knut Veisten, Luis I. Rizzi, Juan de Dios Ortúzar, Rune Elvik IntroductionThe economic value of safety represents an important guide to transport policy, and more studies on individuals’ valuation of road safety are called for. This paper presents a stated preference study of the value of preventing fatal and serious injuries involving bus passengers and car drivers in road accidents.ObjectivesFormer valuation studies based on travel behaviour and route choice have involved primarily car drivers. Our study also included bus passengers, thus providing a comparison of two types of transport mode users. Moreover, the comparison was based on two different valuation methods.MethodologyAbout 600 bus passengers and nearly 2300 car users from different areas of Norway reported a recent trip, described by its distance and travel cost. Then they answered stated choice tasks that took a reference in the reported trip and involved trade-offs among travel time, fatal and seriously injured victims and travel costs. Afterwards, they faced a simple trade-off between travel costs, and fatal and seriously injured victims.FindingsPooling the data from the two stated preference formats, we derived values of a statistical life and of a statistical seriously injured victim. Regarding the value of statistical life, our point estimates were NOK 45.5 million and NOK 58.3 million for bus users and car users respectively.DiscussionThe point estimates for bus passengers and car users were not statistically different given their confidence intervals. Thus, we recommend the use of a single value, identical for both modes of transport, for the prevention of a statistical fatality as well as for a statistical injury
  • Situational influences on response time and maneuver choice: Development
           of time-critical scenarios
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Matthias Powelleit, Mark Vollrath Findings concerning drivers’ response times to sudden events vary considerably across studies due to different experimental setups and situational characteristics, such as expectancy of an event and urgency to react. While response times are widely reported in the literature, understanding of drivers’ choice of maneuvers in time-critical situations is limited. Standardized test scenarios could enhance the comparability of studies and help in attaining a better understanding of driver behavior in these situations.In an effort to achieve these improvements, three driving simulator studies (N = 131) were conducted to investigate drivers’ response time and maneuver choice under a range of situational conditions. Each study took place in a specific environmental setting (urban, rural, and highway) and incorporated one unexpected and 12 subsequent events (increased expectancy). Four different time-critical scenarios were used to evoke different driver responses. In three scenarios, obstacles suddenly entered the roadway (braking, steering, or both possible). A fourth scenario comprised the sudden braking of a leading vehicle (only braking possible). Half of the drivers performed a cognitive secondary task. To validate the findings, results from an additional field test (N = 14) were compared to the results from the simulated urban environment.As expected, response choice was influenced by scenario characteristics (available braking distance and room for evasive maneuvers). Braking maneuvers were more frequent in settings with lower speed limits (urban) while steering maneuvers were found at higher speed limits (highway). Responses to suddenly appearing obstacles were fastest in the urban setting at 540–680 ms; these responses were 200–300 ms slower in the rural and highway settings. Response times increased by 100–200 ms when drivers responded to braking leading vehicles rather than obstacles. Braking responses were 200–350 ms slower and steering responses were 90–200 ms slower when drivers responded to an unexpected event rather than subsequent events. The cognitive secondary task had no significant effect. The simulated environment and the field test produced comparable response behavior.The current study provides reference numbers that help to establish a set of standardized test scenarios for future studies. On basis of this study, nine scenarios are recommended for the context of time-critical crash avoidance maneuvers. Such standardized test scenarios could improve the comparability of future studies on response time and maneuver choice.
  • Exploring patterns of child pedestrian behaviors at urban intersections
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Victoria Gitelman, Sharon Levi, Roby Carmel, Anna Korchatov, Shalom Hakkert Children are more vulnerable as pedestrians due to their cognitive, physical and behavioral traits. However, walking is one of the main forms of travel for children, particularly during leisure hours. Child pedestrian injury primarily occurs in urban areas, with a significant share at crosswalks. This study observed child pedestrian behaviors at crosswalks of urban intersections aiming to characterize their behavior patterns and identify risk factors that may lead to injury. Crossing behaviors of children and adolescents up to age 18, during leisure hours, were video-recorded at 29 crosswalks, on signalized and un-signalized intersections situated on collector roads. Some children used pedestrian crosswalks while riding a bicycle or other non-motorized means; they were also included in the sample. Behaviors of 2930 young road users were encoded and compared by age groups. Multivariate logistic regression models were adjusted to identify factors associated with crossing on red and with non-checking vehicle traffic at un-signalized crosswalks. The findings pointed to different behavior patterns for the various child age groups. Risk-taking behaviors are higher for older children; adolescents aged 14–17 cross more on red, without checking traffic, outside crosswalk boundaries and while distracted. At all types of sites, a fifth of children over the age of 9 crossed by riding, the probability of crossing on red and of non-checking traffic prior to crossing at an un-signalized crosswalk was higher for children riding an electric bicycle or kick-scooter. The non-checking of traffic was also higher when a child is distracted by a mobile phone or other electronic gadget, or carries a big object. Children under age 9 were usually accompanied by adults but still exhibited risk-taking behaviors that apparently mirrored those of the adults. Risk-taking behaviors of young road users should be taken into account in the development of injury prevention programs focusing on child and parent education and training, and by adapting the urban environment to better meet their needs.
  • Reducing intercity bus crashes through driver rescheduling
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Shuo-Yen Wang, Kun-Feng Wu Intercity bus crashes often involve driver fatigue, which itself is usually the result of sleep deprivation, long driving hours, a maladjusted circadian rhythm, or some combination of the above. And driver scheduling has long been suspected as the root cause affecting sleepiness and fatigue. As such, a fundamental question for intercity bus carriers is how to reduce crashes associated with driver schedules, while maintaining a nonstop service' This research seeks to develop a paradigm to minimize overall fleet crash risk by rescheduling. In this study, we first identified those driving schedules associated with the highest crash risks, and a rescheduling scheme is then proposed to reduce fleet crashes overall. A case-study approach was employed to identify driver scheduling associated with higher crash risk, and a mathematical program was then formulated to minimize fleet crash risk. Our results showed that several types of driver schedules would lead to higher crash risk; for example: (1) working in the afternoon or early hours in the morning for two consecutive days; and (2) commencing a driving shift in the mornings, the afternoon or the early hours of the morning after being off-duty for more than 24 h. To meet the challenge of maintaining a nonstop service while simultaneously minimizing the crash risk associated with these risk patterns, a mathematical program was developed, and it was found that rescheduling based on our algorithm could reduce the incidence of crashes by approximately 30 percent.
  • Associations between upper extremity injury patterns in side impact motor
           vehicle collisions with occupant and crash characteristics
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Mireille E. Kelley, Jennifer W. Talton, Ashley A. Weaver, Andrew O. Usoro, Eric R. Barnard, Anna N. Miller IntroductionSide impact motor vehicle collisions (MVC) represent a significant burden of mortality and morbidity caused by automotive injury within the United States. The objective of this study was to evaluate the relationship between upper extremity (UE) injury patterns and contact sources in side impact MVC with occupant and crash variables.MethodsCrash Injury Research and Engineering Network data obtained from 1998 to 2012 were used to evaluate UE injuries in side impact crashes. First row drivers and passengers that were at least 16 years old with complete crash information were included. Side impact crashes were defined to have an area of deformation to the side of the vehicle and a principal direction of force between 60° and 120° or 240° and 300°. Injuries were stratified by type, anatomic location, and Abbreviated Injury Scale (AIS) severity. Occupant variables included age, sex, height, weight, body mass index, and Injury Severity Score. Vehicle and crash variables included in the analysis were change in vehicle velocity at the time of impact, maximum door intrusion, maximum B-pillar intrusion, seat track position, belt use, vehicle type, impact type, and injury source. Statistical analysis of the UE injury data included descriptive statistics, linear regression analyses with occupant variables, and logistic regression analyses with vehicle and crash variables.ResultsThere were 903 UE injuries among 408 case occupants. The most common injury type was soft tissue injury (72.5%). The majority of fractures were proximal to and including the humerus (70.3%) with the clavicle being the most common fracture location (N = 89). AIS 2+ UE injuries were associated with a significantly higher mean occupant Injury Severity Score than AIS 1 UE injuries (p = 0.01). Contact with the door was the leading cause of UE injury (34.2%). The odds (OR [95% confidence interval], p-value) of an AIS 2+ UE injury due to contact with the B-pillar (5.3 [3.1, 9.1],
  • Who is responsible for global road safety' A cross-cultural comparison
           of Actor Maps
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): R.C. McIlroy, K.A. Plant, M.S. Hoque, W. Jianping, G.O. Kokwaro, N.H. Vũ, N.A. Stanton The traditional three ‘E’s approach to road safety (engineering, education, enforcement) has had, and will continue to have, a significant impact on road traffic casualty rates worldwide. Nevertheless, with rising motorisation in many countries, global fatality numbers have changed little over the past decade. Following calls for the application of sociotechnical systems thinking to the problem, we widen the road safety discussion with an additional four ‘E’s; economics, emergency response, enablement, and, the umbrella term for the approach taken, ergonomics. The research presents an application of Rasmussen’s Risk Management Framework to the road safety systems of five distinct nations; Bangladesh, China, Kenya, the UK, and Vietnam. Following site visits, reviews of literature, and interviews with subject matter experts in each of the countries, a series of Actor Map models of the countries’ road safety systems were developed. These are compared and discussed in terms of the wide variety of interconnecting organisations involved, their influences on road safety outcomes, the differences between nations, and the need to look beyond road users when designing road safety interventions.
  • Full Bayesian conflict-based models for real time safety evaluation of
           signalized intersections
    • Abstract: Publication date: Available online 5 October 2018Source: Accident Analysis & PreventionAuthor(s): Mohamed Essa, Tarek Sayed Existing advanced traffic management and emerging connected vehicles (CVs) technology can generate considerable amount of data on vehicle positions and trajectories. This data can be used for real-time safety optimization of intersections. To achieve this, it is essential to first understand how changes in signal control affect safety in real-time. This paper develops conflict-based safety performance functions (SPFs) of signalized intersections at the cycle level using multiple traffic conflict indicators. The developed SPFs relate various dynamic traffic parameters to the number of rear-end conflicts at the signal cycle. The traffic parameters included: queue length, shock wave speed and area, and the platoon ratio. The Time-to-Collision, the Modified-Time-to-Collision, and the Deceleration Rate to Avoid the Crash were used as traffic conflict indicators. Traffic video-data collected from six signalized intersections was used in the analysis. The SPFs were developed using the Full Bayesian approach to address the unobserved heterogeneity and the variation among different sites. Overall, the results showed that all the developed SPFs have good fit with all explanatory variables being statistically significant. Also, the highest conflict frequency was noticed at the beginning of the green time, while the highest conflict severity was noticed at the beginning of the red time. Lastly, the results can be used most beneficially in real-time safety optimization of signalized intersection.
  • Comparison of univariate and two-stage approaches for estimating crash
           frequency by severity—Case study for horizontal curves on two-lane rural
    • Abstract: Publication date: Available online 1 September 2018Source: Accident Analysis & PreventionAuthor(s): Alireza Jafari Anarkooli, Bhagwant Persaud, Mehdi Hosseinpour, Taha Saleem The Highway Safety Manual (HSM) procedures apply specific safety performance functions (SPFs) and crash modification factors (CMFs) appropriate for estimating the safety effects of design and operational changes to a roadway. Although the applicability of the SPFs and CMFs may significantly vary by crash severity, they are mainly based on total crash counts, with different approaches for estimation of crashes by crash severity. The variety of approaches in the HSM and in the literature in general suggests that there may be no one best approach for all situations, and that there is a need to develop and compare alternative approaches for each potential application. This paper addresses this need by demonstrating the development and comparison of alternative approaches using horizontal curves on two-lane roads as a case study. This site type was chosen because of the high propensity for severe crashes and the potential for exploring a wide range of variables that affect this propensity. To facilitate this investigation, a two-stage modeling approach is developed whereby the proportion of crashes for each severity level is estimated as a function of roadway-specific factors and traffic attributes and then applied to an estimate of total crashes from an SPF. Using Highway Safety Information System (HSIS) curve data for Washington state, a heterogeneous negative binomial (HTNB) regression model is estimated for total crash counts and then applied with severity distribution functions (SDFs) developed by a generalized ordered probit model (GOP). To evaluate the performance of this two-stage approach, a comparison is made with predictions directly obtained from estimated univariate SPFs for crash frequency by severity and also from a fixed proportion method that has been suggested in the HSM. The results revealed that, while the two-stage SDF approach and univariate approach adopt different procedures for model estimation, their prediction accuracies are similar, and both are superior to the fixed proportion method. In short, this study highlights the potential of the two-stage SDF approach in accounting for crash frequency variations by severity levels, at least for curved two-lane road sections, and especially for the all too frequent cases where samples are too small to estimate viable univariate crash severity models.
  • Forecasting German crash numbers: The effect of meteorological variables
    • Abstract: Publication date: Available online 18 August 2018Source: Accident Analysis & PreventionAuthor(s): Kevin Diependaele, Heike Martensen, Markus Lerner, Andreas Schepers, Frits Bijleveld, Jacques J.F. Commandeur At the end of each year, the German Federal Highway Research Institute (BASt) publishes the road safety balance of the closing year. They describe the development of accident and casualty numbers disaggregated by road user types, age groups, type of road and the consequences of the accidents. However, at the time of publishing, these series are only available for the first eight or nine months of the year. To make the balance for the whole year, the last three or four months are forecasted. The objective of this study was to improve the accuracy of these forecasts through structural time-series models that include effects of meteorological conditions. The results show that, compared to the earlier heuristic approach, root mean squared errors are reduced by up to 55% and only two out of the 27 different data series yield a modest rise of prediction errors. With the exception of four data series, prediction accuracies also clearly improve incorporating meteorological data in the analysis. We conclude that our approach provides a valid alternative to provide input to policy makers in Germany.
  • The European road safety decision support system on risks and measures
    • Abstract: Publication date: Available online 18 August 2018Source: Accident Analysis & PreventionAuthor(s): Heike Martensen, Kevin Diependaele, Stijn Daniels, Wouter Van den Berghe, Eleonora Papadimitriou, George Yannis, Ingrid Van Schagen, Wendy Weijermars, Wim Wijnen, Ashleigh Filtness, Rachel Talbot, Pete Thomas, Klaus Machata, Eva Aigner Breuss, Susanne Kaiser, Thierry Hermitte, Rob Thomson, Rune Elvik The European Road Safety Decision Support System ( is an innovative system providing the available evidence on a broad range of road risks and possible countermeasures. This paper describes the scientific basis of the DSS. The structure underlying the DSS consists of (1) a taxonomy identifying risk factors and measures and linking them to each other, (2) a repository of studies, and (3) synopses summarizing the effects estimated in the literature for each risk factor and measure, and (4) an economic efficiency evaluation instrument (E3-calculator). The DSS is implemented in a modern web-based tool with a highly ergonomic interface, allowing users to get a quick overview or go deeper into the results of single studies according to their own needs.
  • Safety assessment of control design parameters through vehicle dynamics
    • Abstract: Publication date: Available online 20 July 2018Source: Accident Analysis & PreventionAuthor(s): Stergios Mavromatis, Alexandra Laiou, George Yannis An existing vehicle dynamics model was utilized to define design parameters up to which steady state cornering conditions apply and consequently lift the restrictions of the point mass model. Aiming to assess critical safety concerns in terms of vehicle skidding, the motion of a passenger car was examined over a range of design speed values paired with control design elements from AASHTO 2011 Design Guidelines as well as certain values of poor pavement friction coefficients.Two distinct cases were investigated; the determination of the maximum attainable constant speed (termed as safe speed) at impending skid conditions as well as the case of comfortable curve negotiation where lower constant speed values were utilized. The overall objective was to define the safety margins for each examined case.From the interaction between road geometry, pavement friction and vehicle characteristics, many interesting findings are reported, where some of them are beyond the confined field of road geometry parameters; such as demanded longitudinal and lateral friction values and horse-power utilization rates. From the road geometry point of view, it was found that control alignments on steep upgrades consisting of low design speed values and combined with poor friction pavements are critical in terms of safety. Such cases should be treated very cautiously through certain actions. These actions include the adoption of acceptable arrangements for the above values regarding new alignments, posted speed management for existing but also scheduling friction improvement programmes more accurately for both cases.
  • A novel method for imminent crash prediction and prevention
    • Abstract: Publication date: Available online 12 July 2018Source: Accident Analysis & PreventionAuthor(s): Zhi Chen, Xiao Qin A crash prediction and prevention method was proposed to detect imminent crash risk and help recommend traffic control strategies to prevent crashes. The method consists of two modules, the crash prediction module and the crash prevention module. The crash prediction module detects crash-prone conditions when the predicted crash probability exceeds a specified threshold. Then the crash prevention module would simulate the safety effect of traffic control alternatives and recommend the optimal one. The proposed method was demonstrated in a case study with variable speed limit (VSL). Results showed that the proposed crash prediction and prevention method could effectively detect crash-prone conditions and evaluate the safety and mobility impacts of various safety countermeasures.
  • Road safety data considerations
    • Abstract: Publication date: Available online 11 July 2018Source: Accident Analysis & PreventionAuthor(s): Loukas Dimitriou, Constantinos Antoniou
  • Use of real-world connected vehicle data in identifying high-risk
           locations based on a new surrogate safety measure
    • Abstract: Publication date: Available online 6 July 2018Source: Accident Analysis & PreventionAuthor(s): Kun Xie, Di Yang, Kaan Ozbay, Hong Yang Traditional methods for the identification of high-risk locations rely heavily on historical crash data. Rich information generated from connected vehicles could be used to obtain surrogate safety measures (SSMs) for risk identification. Conventional SSMs such as time to collision (TTC) neglect the potential risk of car-following scenarios in which the following vehicle’s speed is slightly less than or equal to the leading vehicle’s but the spacing between two vehicles is relatively small that a slight disturbance would yield collision risk. To address this limitation, this study proposes time to collision with disturbance (TTCD) for risk identification. By imposing a hypothetical disturbance, TTCD can capture rear-end conflict risks in various car following scenarios, even when the leading vehicle has a higher speed. Real-world connected vehicle pilot test data collected in Ann Arbor, Michigan is used in this study. A detailed procedure of cleaning and processing the connected vehicle data is presented. Results show that risk rate identified by TTCD can achieve a higher Pearson’s correlation coefficient with rear-end crash rate than other traditional SSMs. We show that high-risk locations identified by connected vehicle data from a relatively shorter time period are similar to the ones identified by using the historical crash data. The proposed method can substantially reduce the data collection time, compared with traditional safety analysis that generally requires more than three years to get sufficient crash data. The connected vehicle data has thus shown the potential to be used to develop proactive safety solutions and the risk factors can be eliminated in a timely manner.
  • Corrigendum to “A farewell to brake reaction times'
           Kinematics-dependent brake response in naturalistic rear-end
           emergencies” [Accid. Anal. Prev. 95 (2016) 209–226]
    • Abstract: Publication date: Available online 15 June 2018Source: Accident Analysis & PreventionAuthor(s): Gustav Markkula, Johan Engström, Johan Lodin, Jonas Bärgman, Trent Victor
  • Evaluation of safety effect of turbo-roundabout lane dividers using
           floating car data and video observation
    • Abstract: Publication date: Available online 1 June 2018Source: Accident Analysis & PreventionAuthor(s): Mariusz Kieć, Jiří Ambros, Radosław Bąk, Ondřej Gogolín Roundabouts are one of the safest types of intersections. However, the needs to meet the requirements of operation, capacity, traffic organization and surrounding development lead to a variety of design solutions. One of such alternatives are turbo-roundabouts, which simplify drivers’ decision making, limit lane changing in the roundabout, and induce low driving speed thanks to raised lane dividers. However, in spite of their generally positive reception, the safety impact of turbo-roundabouts has not been sufficiently studied. Given the low number of existing turbo-roundabouts and the statistical rarity of accident occurrence, the prevalent previously conducted studies applied only simple before-after designs or relied on traffic conflicts in micro-simulations. Nevertheless, the presence of raised lane dividers is acknowledged as an important feature of well performing and safe turbo-roundabouts.Following the previous Polish studies, the primary objective of the present study was assessment of influence of presence of lane dividers on road safety and developing a reliable and valid surrogate safety measure based on field data, which will circumvent the limitations of accident data or micro-simulations. The secondary objective was using the developed surrogate safety measure to assess and compare the safety levels of Polish turbo-roundabout samples with and without raised lane dividers.The surrogate safety measure was based on speed and lane behaviour. Speed was obtained from video observations and floating car data, which enabled the construction of representative speed profiles. Lane behaviour data was gathered from video observations.The collection of the data allowed for a relative validation of the method by comparing the safety performance of turbo-roundabouts with and without raised lane dividers. In the end, the surrogate measure was applied for evaluation of safety levels and enhancement of the existing safety performance functions, which combine traffic volumes, and speeds as a function of radii). The final models may help quantify the safety impact of different turbo-roundabout solutions.
  • Evaluation of surrogate measures for pedestrian trips at intersections and
           crash modeling
    • Abstract: Publication date: Available online 31 May 2018Source: Accident Analysis & PreventionAuthor(s): Jaeyoung Lee, Mohamed Abdel-Aty, Imran Shah Pedestrians are considered the most vulnerable road users who are directly exposed to traffic crashes. With a view to addressing the growing concern of pedestrian safety, Federal and local governments aim at reducing pedestrian-involved crashes. Nevertheless, pedestrian volume data are rarely available even though they among the most important factors to identify pedestrian safety. Thus, this study aims at identifying surrogate measures for pedestrian exposure at intersections. A two-step process is implemented: the first step is the development of Tobit and generalized linear models for predicting pedestrian trips (i.e., exposure models). In the second step, negative binomial and zero inflated negative binomial models were developed for pedestrian crashes using the predicted pedestrian trips. The results indicate that among various exposure models the Tobit model performs the best in describing pedestrian exposure. The identified exposure-relevant factors are the presence of schools, car-ownership, pavement condition, sidewalk width, bus ridership, intersection control type and presence of sidewalk barrier. It was also found that the negative binomial model with the predicted pedestrian trips and that with the observed pedestrian trips perform equally well for estimating pedestrian crashes. Also, the difference between the observed and the predicted pedestrian trips does not appear as statistically significant, according to the results of the t-test and Wilcoxon signed-rank test. It is expected that the methodologies using predicted pedestrian trips or directly including pedestrian surrogate exposure variables can estimate safety performance functions for pedestrian crashes even though when pedestrian trip data is not available.
  • 10th International Conference on managing fatigue: Managing fatigue to
           improve safety, wellness, and effectiveness
    • Abstract: Publication date: Available online 19 May 2018Source: Accident Analysis & PreventionAuthor(s): Jeffrey S. Hickman, Richard J. Hanowski, Jana Price, J. Erin Mabry
  • How much is left in your “sleep tank”' Proof of concept for a
           simple model for sleep history feedback
    • Abstract: Publication date: Available online 7 May 2018Source: Accident Analysis & PreventionAuthor(s): Jillian Dorrian, Steven Hursh, Lauren Waggoner, Crystal Grant, Maja Pajcin, Charlotte Gupta, Alison Coates, David Kennaway, Gary Wittert, Leonie Heilbronn, Chris Della Vedova, Siobhan Banks Technology-supported methods for sleep recording are becoming increasingly affordable. Sleep history feedback may help with fatigue-related decision making – Should I drive' Am I fit for work' This study examines a “sleep tank” model (SleepTank™), which is analogous to the fuel tank in a car, refilled by sleep, and depleted during wake. Required inputs are sleep period time and sleep efficiency (provided by many consumer-grade actigraphs). Outputs include suggested hours remaining to “get sleep” and percentage remaining in tank (Tank%). Initial proof of concept analyses were conducted using data from a laboratory-based simulated nightshift study. Ten, healthy males (18–35y) undertook an 8h baseline sleep opportunity and daytime performance testing (BL), followed by four simulated nightshifts (2000 h–0600 h), with daytime sleep opportunities (1000 h–1600 h), then an 8 h night-time sleep opportunity to return to daytime schedule (RTDS), followed by daytime performance testing. Psychomotor Vigilance Task (PVT) and Karolinska Sleepiness Scale were performed at 1200 h on BL and RTDS, and at 1830 h, 2130 h 0000 h and 0400 h each nightshift. A 40-minute York Driving Simulation was performed at 1730 h, 2030 h and 0300 h on each nightshift. Model outputs were calculated using sleep period timing and sleep efficiency (from polysomnography) for each participant. Tank% was a significant predictor of PVT lapses (p 
  • Effects of strategic early-morning caffeine gum administration on
           association between salivary alpha-amylase and neurobehavioural
           performance during 50 h of sleep deprivation
    • Abstract: Publication date: Available online 7 May 2018Source: Accident Analysis & PreventionAuthor(s): Maja Pajcin, Jason M White, Siobhan Banks, Jill Dorrian, Gemma M Paech, Crystal L Grant, Kayla Johnson, Katie Tooley, Eugene Aidman, Justin Fidock, Gary H Kamimori, Chris B Della Vedova Self-assessment is the most common method for monitoring performance and safety in the workplace. However, discrepancies between subjective and objective measures have increased interest in physiological assessment of performance. In a double-blind placebo-controlled study, 23 healthy adults were randomly assigned to either a placebo (n = 11; 5 F, 6 M) or caffeine condition (n = 12; 4 F, 8 M) while undergoing 50 h (i.e. two days) of total sleep deprivation. In previous work, higher salivary alpha-amylase (sAA) levels were associated with improved psychomotor vigilance and simulated driving performance in the placebo condition. In this follow-up article, the effects of strategic caffeine administration on the previously reported diurnal profiles of sAA and performance, and the association between sAA and neurobehavioural performance were investigated. Participants were given a 10 h baseline sleep opportunity (monitored via standard polysomnography techniques) prior to undergoing sleep deprivation (total sleep time: placebo = 8.83 ± 0.48 h; caffeine = 9.01 ± 0.48 h). During sleep deprivation, caffeine gum (200 mg) was administered at 01:00 h, 03:00 h, 05:00 h, and 07:00 h to participants in the caffeine condition (n = 12). This strategic administration of caffeine gum (200 mg) has been shown to be effective at maintaining cognitive performance during extended wakefulness. Saliva samples were collected, and psychomotor vigilance and simulated driving performance assessed at three-hour intervals throughout wakefulness. Caffeine effects on diurnal variability were compared with previously reported findings in the placebo condition (n = 11). The impact of caffeine on the circadian profile of sAA coincided with changes in neurobehavioural performance. Higher sAA levels were associated with improved performance on the psychomotor vigilance test during the first 24 h of wakefulness in the caffeine condition. However, only the association between sAA and response speed (i.e. reciprocal-transform of mean reaction time) was consistent across both days of sleep deprivation. The association between sAA and driving performance was not consistent across both days of sleep deprivation. Results show that the relationship between sAA and reciprocal-transform of mean reaction time on the psychomotor vigilance test persisted in the presence of caffeine, however the association was relatively weaker as compared with the placebo condition.
  • Analysing truck harsh braking incidents to study roundabout accident risk
    • Abstract: Publication date: Available online 5 May 2018Source: Accident Analysis & PreventionAuthor(s): Jwan Kamla, Tony Parry, Andrew Dawson In order to reduce accident risk, highway authorities prioritise maintenance budgets partly based upon previous accident history. However, as accident rates have continued to fall, this approach has become problematic as accident ‘black spots’ have been treated and the number of accidents at any individual site has fallen, making previous accident history a less reliable indicator of future accident risk. Another way of identifying sites of higher accident risk might be to identify near-miss accidents (where an accident nearly happened but was avoided). The principal aim of this paper is to analyze potentially unsafe truck driving conditions from counts of Harsh Braking Incidents (HBIs) at roundabouts and compare the results to similar, previous studies of accident numbers at the same sites, to explore if HBIs can be studied as a surrogate for accidents. This is achieved by processing truck telematics data with geo-referenced incidents of harsh braking. Models are then developed to characterise the relationships between truck HBIs and geometric and traffic variables. These HBIs are likely to occur more often than accidents and may, therefore, be useful in identifying sites with high accident risk. Based on the results of this study, it can be concluded that HBIs are influenced by traffic and geometric variables in a similar way to accidents; therefore they may be useful in considering accident risk at roundabouts. They are a source of higher volumes of data than accidents, which is important in considering changes or trends in accident risk over time. The results showed that random-parameters count data models provide better goodness of fit compared to fixed-parameters models and more variables were found to be significant, giving a better prediction of events.
  • School start times and teenage driver motor vehicle crashes
    • Abstract: Publication date: Available online 26 April 2018Source: Accident Analysis & PreventionAuthor(s): Robert D. Foss, Richard L. Smith, Natalie P. O'Brien IntroductionShifting school start times to 8:30 am or later has been found to improve academic performance and reduce behavior problems. Limited research suggests this may also reduce adolescent driver motor vehicle crashes. A change in the school start time from 7:30 am to 8:45 am for all public high schools in one North Carolina county presented the opportunity to address this question with greater methodologic rigor.MethodWe conducted ARIMA interrupted time-series analyses to examine motor vehicle crash rates of high school age drivers in the intervention county and 3 similar comparison counties with comparable urban-rural population distribution. To focus on crashes most likely to be affected, we limited analysis to crashes involving 16- & 17-year-old drivers occurring on days when school was in session.ResultsIn the intervention county, there was a 14% downward shift in the time-series following the 75 min delay in school start times (p = .076). There was no change approaching statistical significance in any of the other three counties. Further analysis indicated marked, statistically significant shifts in hourly crash rates in the intervention county, reflecting effects of the change in school start time on young driver exposure. Crashes from 7 to 7:59 am decreased sharply (−25%, p = .008), but increased similarly from 8 to 8:59 am (21%, p = .004). Crashes from 2 to 2:59 pm declined dramatically (−48%, p = .000), then increased to a lesser degree from 3 to 3:59 pm (32%, p = .024) and non-significantly from 4 to 4:59 (19%, p = .102). There was no meaningful change in early morning or nighttime crashes, when drowsiness-induced crashes might have been expected to be most common.DiscussionThe small decrease in crashes among high school age drivers following the shift in school start time is consistent with the findings of other studies of teen driver crashes and school start times. All these studies, including the present one, have limitations, but the similar findings suggest that crashes and school start times are indeed related, with earlier start times equating to more crashes.ConclusionLater high school start times (>8:30 am) appear to be associated with lower adolescent driver crash rates, but additional research is needed to confirm this and to identify the mechanism by which this occurs (reduced drowsiness or reduced exposure).
  • Drowsiness measures for commercial motor vehicle operations
    • Abstract: Publication date: Available online 26 April 2018Source: Accident Analysis & PreventionAuthor(s): Amy R. Sparrow, Cynthia M. LaJambe, Hans P.A. Van Dongen Timely detection of drowsiness in Commercial Motor Vehicle (C MV) operations is necessary to reduce drowsiness-related CMV crashes. This is relevant for manual driving and, paradoxically, even more so with increasing levels of driving automation. Measures available for drowsiness detection vary in reliability, validity, usability, and effectiveness. Passively recorded physiologic measures such as electroencephalography (EEG) and a variety of ocular parameters tend to accurately identify states of considerable drowsiness, but are limited in their potential to detect lower levels of drowsiness. They also do not correlate well with measures of driver performance. Objective measures of vigilant attention performance capture drowsiness reliably, but they require active driver involvement in a performance task and are prone to confounds from distraction and (lack of) motivation. Embedded performance measures of actual driving, such as lane deviation, have been found to correlate with physiologic and vigilance performance measures, yet to what extent drowsiness levels can be derived from them reliably remains a topic of investigation. Transient effects from external circumstances and behaviors – such as task load, light exposure, physical activity, and caffeine intake – may mask a driver’s underlying state of drowsiness. Also, drivers differ in the degree to which drowsiness affects their driving performance, based on trait vulnerability as well as age. This paper provides a broad overview of the current science pertinent to a range of drowsiness measures, with an emphasis on those that may be most relevant for CMV operations. There is a need for smart technologies that in a transparent manner combine different measurement modalities with mathematical representations of the neurobiological processes driving drowsiness, that account for various mediators and confounds, and that are appropriately adapted to the individual driver. The research for and development of such technologies requires a multi-disciplinary approach and significant resources, but is technically within reach.
  • Effects of methodological decisions on rainfall-related crash relative
           risk estimates
    • Abstract: Publication date: Available online 23 April 2018Source: Accident Analysis & PreventionAuthor(s): Alan W. Black, Gabriele Villarini Numerous studies have examined the influence of rainfall on the relative risk of crash, and they all agree that rainfall leads to an increase in relative risk as compared to dry conditions; what they do not agree on is the magnitude of these increases. Here we consider three methodological decisions made in computing the relative risk and examine their impacts: the inclusion or exclusion of zero total events (where no crashes occur during event or control periods), the temporal scale of analysis, and the use of information on pavement and weather conditions contained with the crash reports to determine relative risk. Our analyses are based on several years of data from six U.S. states (Arkansas, Georgia, Illinois, Maryland, Minnesota and Ohio). Zero total events in the context of weather related crash studies typically provide no information on the actual crash odds and greatly alter the distribution of relative risk estimates and should be removed from the analysis. While the use of a daily time step provides an estimate of relative risk that is not significantly different from an hourly time step for the majority of rural counties in our study area, the same is true of only 39% of the urban counties. Finally, the use of pavement and weather condition information from the crash reports results in relative risk estimates that are lower than the standard approach, however this difference decreases as rainfall totals increase. By highlighting the influence of methodological choices, we hope to pave the way towards the potential reduction in uncertainties in weather-related relative risk estimates.
  • Implications of estimating road traffic serious injuries from hospital
    • Abstract: Publication date: Available online 19 April 2018Source: Accident Analysis & PreventionAuthor(s): K. Pérez, W. Weijermars, N. Bos, A.J. Filtness, R. Bauer, H. Johannsen, N. Nuyttens, L. Pascal, P. Thomas, M. Olabarria, The Working group of WP7 project To determine accurately the number of serious injuries at EU level and to compare serious injury rates between different countries it is essential to use a common definition. In January 2013, the High Level Group on Road Safety established the definition of serious injuries as patients with an injury level of MAIS3+(Maximum Abbreviated Injury Scale). Whatever the method used for estimating the number or serious injuries, at some point it is always necessary to use hospital records. The aim of this paper is to understand the implications for (1) in/exclusion criteria applied to case selection and (2) a methodological approach for converting ICD (International Classification of Diseases/Injuries) to MAIS codes, when estimating the number of road traffic serious injuries from hospital data. A descriptive analysis with hospital data from Spain and the Netherlands was carried out to examine the effect of certain choices concerning in- and exclusion criteria based on codes of the ICD9-CM and ICD10. The main parameters explored were: deaths before and after 30 days, readmissions, and external injury causes. Additionally, an analysis was done to explore the impact of using different conversion tools to derive MAIS3 + using data from Austria, Belgium, France, Germany, Netherlands, and Spain. Recommendations are given regarding the in/exclusion criteria and when there is incomplete data to ascertain a road injury, weighting factors could be used to correct data deviations and make more real estimations.
  • Risk management in port and maritime logistics
    • Abstract: Publication date: Available online 11 April 2018Source: Accident Analysis & PreventionAuthor(s): Jasmine Siu Lee Lam, Y.H. Venus Lun, Michael G.H. Bell
  • Dangerous intersections' A review of studies of fatigue and
           distraction in the automated vehicle
    • Abstract: Publication date: Available online 10 April 2018Source: Accident Analysis & PreventionAuthor(s): Gerald Matthews, Catherine Neubauer, Dyani J. Saxby, Ryan W. Wohleber, Jinchao Lin The impacts of fatigue on the vehicle driver may change with technological advancements including automation and the increasing prevalence of potentially distracting in-car systems. This article reviews the authors’ simulation studies of how fatigue, automation, and distraction may intersect as threats to safety. Distinguishing between states of active and passive fatigue supports understanding of fatigue and the development of countermeasures. Active fatigue is a stress-like state driven by overload of cognitive capabilities. Passive fatigue is produced by underload and monotony, and is associated with loss of task engagement and alertness. Our studies show that automated driving reliably elicits subjective symptoms of passive fatigue and also loss of alertness that persists following manual takeover. Passive fatigue also impairs attention and automation use in operators of Remotely Piloted Vehicles (RPVs). Use of in-vehicle media has been proposed as a countermeasure to fatigue, but such media may also be distracting. Studies tested whether various forms of phone-based media interacted with automation-induced fatigue, but effects were complex and dependent on task configuration. Selection of fatigue countermeasures should be guided by an understanding of the form of fatigue confronting the operator. System design, regulation of level of automation, managing distraction, and selection of fatigue-resilient personnel are all possible interventions for passive fatigue, but careful evaluation of interventions is necessary prior to deployment.
  • The relation between working conditions, aberrant driving behaviour and
           crash propensity among taxi drivers in China
    • Abstract: Publication date: Available online 4 April 2018Source: Accident Analysis & PreventionAuthor(s): Yonggang Wang, Linchao Li, Carlo G. Prato Although the taxi industry is playing an important role in Chinese everyday life, little attention has been posed towards occupational health issues concerning the taxi drivers’ working conditions, driving behaviour and road safety. A cross-sectional survey was administered to 1021 taxi drivers from 21 companies in four Chinese cities and collected information about (i) sociodemographic characteristics, (ii) working conditions, (iii) frequency of daily aberrant driving behaviour, and (iv) involvement in property-damage-only (PDO) and personal injury (PI) crashes over the past two years. A hybrid bivariate model of crash involvement was specified: (i) the hybrid part concerned a latent variable model capturing unobserved traits of the taxi drivers; (ii) the bivariate part modelled jointly both types of crashes while capturing unobserved correlation between error terms. The survey answers paint a gloomy picture in terms of workload, as taxi drivers reported averages of 9.4 working hours per day and 6.7 working days per week that amount on average to about 63.0 working hours per week. Moreover, the estimates of the hybrid bivariate model reveal that increasing levels of fatigue, reckless behaviour and aggressive behaviour are positively related to a higher propensity of crash involvement. Lastly, the heavy workload is also positively correlated with the higher propensity of crashing, not only directly as a predictor of crash involvement, but also indirectly as a covariate of fatigue and aberrant driving behaviour. The findings from this study provide insights into potential strategies for preventive education and taxi industry management to improve the working conditions and hence reduce fatigue and road risk for the taxi drivers.
  • Predicting performance and safety based on driver fatigue
    • Abstract: Publication date: Available online 3 April 2018Source: Accident Analysis & PreventionAuthor(s): Daniel Mollicone, Kevin Kan, Chris Mott, Rachel Bartels, Steve Bruneau, Matthew van Wollen, Amy R. Sparrow, Hans P.A. Van Dongen Fatigue causes decrements in vigilant attention and reaction time and is a major safety hazard in the trucking industry. There is a need to quantify the relationship between driver fatigue and safety in terms of operationally relevant measures. Hard-braking events are a suitable measure for this purpose as they are relatively easily observed and are correlated with collisions and near-crashes. We developed an analytic approach that predicts driver fatigue based on a biomathematical model and then estimates hard-braking events as a function of predicted fatigue, controlling for time of day to account for systematic variations in exposure (traffic density). The analysis used de-identified data from a previously published, naturalistic field study of 106 U.S. commercial motor vehicle (CMV) drivers. Data analyzed included drivers’ official duty logs, sleep patterns measured around the clock using wrist actigraphy, and continuous recording of vehicle data to capture hard-braking events. The curve relating predicted fatigue to hard-braking events showed that the frequency of hard-braking events increased as predicted fatigue levels worsened. For each increment on the fatigue scale, the frequency of hard-braking events increased by 7.8%. The results provide proof of concept for a novel approach that predicts fatigue based on drivers’ sleep patterns and estimates driving performance in terms of an operational metric related to safety. The approach can be translated to practice by CMV operators to achieve a fatigue risk profile specific to their own settings, in order to support data-driven decisions about fatigue countermeasures that cost-effectively deliver quantifiable operational benefits.
  • Cognitive flexibility: A distinct element of performance impairment due to
           sleep deprivation
    • Abstract: Publication date: Available online 15 March 2018Source: Accident Analysis & PreventionAuthor(s): K.A. Honn, J.M. Hinson, P. Whitney, H.P.A. Van Dongen In around-the-clock operations, reduced alertness due to circadian misalignment and sleep loss causes performance impairment, which can lead to catastrophic errors and accidents. There is mounting evidence that performance on different tasks is differentially affected, but the general principles underlying this differentiation are not well understood. One factor that may be particularly relevant is the degree to which tasks require executive control, that is, control over the initiation, monitoring, and termination of actions in order to achieve goals. A key aspect of this is cognitive flexibility, i.e., the deployment of cognitive control resources to adapt to changes in events. Loss of cognitive flexibility due to sleep deprivation has been attributed to “feedback blunting,” meaning that feedback on behavioral outcomes has reduced salience - and that feedback is therefore less effective at driving behavior modification under changing circumstances. The cognitive mechanisms underlying feedback blunting are as yet unknown. Here we present data from an experiment that investigated the effects of sleep deprivation on performance after an unexpected reversal of stimulus-response mappings, requiring cognitive flexibility to maintain good performance. Nineteen healthy young adults completed a 4-day in-laboratory study. Subjects were randomized to either a total sleep deprivation condition (n = 11) or a control condition (n = 8). Athree-phase reversal learning decision task was administered at baseline, and again after 30.5 h of sleep deprivation, or matching well-rested control. The task was based on a go/no go task paradigm, in which stimuli were assigned to either a go (response) set or a no go (no response) set. Each phase of the task included four stimuli (two in the go set and two in the no go set). After each stimulus presentation, subjects could make a response within 750 ms or withhold their response. They were then shown feedback on the accuracy of their response. In phase 1 of the task, subjects were explicitly told which stimuli were assigned to the go and no go sets. In phases 2 and 3, new stimuli were used that were different from those used in phase 1. Subjects were not explicitly told the go/no go mappings and were instead required to use accuracy feedback to learn which stimuli were in the go and nogo sets. Phase 3 continued directly from phase 2 and retained the same stimuli as in phase 2, but there was an unannounced reversal of the stimulus-response mappings. Task results confirmed that sleep deprivation resulted in loss of cognitive flexibility through feedback blunting, and that this effect was not produced solely by (1) general performance impairment because of overwhelming sleep drive; (2) reduced working memory resources available to perform the task; (3) incomplete learning of stimulus-response mappings before the unannounced reversal; or (4) interference with stimulus identification through lapses in vigilant attention. Overall, the results suggest that sleep deprivation causes a fundamental problem with dynamic attentional control. This element of performance impairment due to sleep deprivation appears to be distinct from vigilant attention deficits, and represents a particularly significant challenge for fatigue risk management.
  • Assessing crash risk considering vehicle interactions with trucks using
           point detector data
    • Abstract: Publication date: Available online 12 March 2018Source: Accident Analysis & PreventionAuthor(s): Kyung (Kate) Hyun, Kyungsoo Jeong, Andre Tok, Stephen G. Ritchie Trucks have distinct driving characteristics in general traffic streams such as lower speeds and limitations in acceleration and deceleration. As a consequence, vehicles keep longer headways or frequently change lane when they follow a truck, which is expected to increase crash risk. This study introduces several traffic measures at the individual vehicle level to capture vehicle interactions between trucks and non-trucks and analyzed how the measures affect crash risk under different traffic conditions. The traffic measures were developed using headways obtained from Inductive Loop Detectors (ILDs). In addition, a truck detection algorithm using a Gaussian Mixture (GM) model was developed to identify trucks and to estimate truck exposure from ILD data. Using the identified vehicle types from the GM model, vehicle interaction metrics were categorized into three groups based on the combination of leading and following vehicle types. The effects of the proposed traffic measures on crash risk were modeled in two different cases of prior- and non-crash using a case-control approach utilizing a conditional logistic regression. Results showed that the vehicle interactions between the leading and following vehicle types were highly associated with crash risk, and further showed different impacts on crash risk by traffic conditions. Specifically, crashes were more likely to occur when a truck following a non-truck had shorter average headway but greater headway variance in heavy traffic while a non-truck following a truck had greater headway variance in light traffic. This study obtained meaningful conclusions that vehicle interactions involved with trucks were significantly related to the crash likelihood rather than the measures that estimate average traffic condition such as total volume or average headway of the traffic stream.
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