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Publisher: Elsevier   (Total: 3159 journals)

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Showing 1 - 200 of 3159 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: 32, SJR: 1.655, CiteScore: 2)
Academic Radiology     Hybrid Journal   (Followers: 22, SJR: 1.015, CiteScore: 2)
Accident Analysis & Prevention     Partially Free   (Followers: 90, SJR: 1.462, CiteScore: 3)
Accounting Forum     Hybrid Journal   (Followers: 25, SJR: 0.932, CiteScore: 2)
Accounting, Organizations and Society     Hybrid Journal   (Followers: 34, 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: 407, 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: 8, 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: 246, 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: 10, SJR: 0.834, CiteScore: 2)
Acta Otorrinolaringologica (English Edition)     Full-text available via subscription  
Acta Otorrinolaringológica Española     Full-text available via subscription   (Followers: 2, 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: 27, 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: 15, SJR: 2.671, CiteScore: 5)
Ad Hoc Networks     Hybrid Journal   (Followers: 11, SJR: 0.53, CiteScore: 4)
Addictive Behaviors     Hybrid Journal   (Followers: 16, SJR: 1.29, CiteScore: 3)
Addictive Behaviors Reports     Open Access   (Followers: 8, SJR: 0.755, CiteScore: 2)
Additive Manufacturing     Hybrid Journal   (Followers: 9, SJR: 2.611, CiteScore: 8)
Additives for Polymers     Full-text available via subscription   (Followers: 22)
Advanced Drug Delivery Reviews     Hybrid Journal   (Followers: 142, SJR: 4.09, CiteScore: 13)
Advanced Engineering Informatics     Hybrid Journal   (Followers: 11, SJR: 1.167, CiteScore: 4)
Advanced Powder Technology     Hybrid Journal   (Followers: 16, 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: 12, 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: 22, 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: 30, SJR: 3.043, CiteScore: 6)
Advances in Carbohydrate Chemistry and Biochemistry     Full-text available via subscription   (Followers: 7, 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: 3)
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: 28, 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: 15)
Advances in Developmental Biology     Full-text available via subscription   (Followers: 11)
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: 24)
Advances in Ecological Research     Full-text available via subscription   (Followers: 43, SJR: 2.524, CiteScore: 4)
Advances in Engineering Software     Hybrid Journal   (Followers: 27, SJR: 1.159, CiteScore: 4)
Advances in Experimental Biology     Full-text available via subscription   (Followers: 7)
Advances in Experimental Social Psychology     Full-text available via subscription   (Followers: 44, 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: 54, 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: 21, SJR: 0.368, CiteScore: 1)
Advances in Heterocyclic Chemistry     Full-text available via subscription   (Followers: 11, 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: 36, 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: 6, 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: 9)
Advances in Marine Biology     Full-text available via subscription   (Followers: 14, 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: 21)
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: 16, 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: 10)
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: 8)
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: 62)
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: 5)
Advances in Space Research     Full-text available via subscription   (Followers: 396, 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: 10, SJR: 0.555, CiteScore: 2)
Advances in the Study of Behavior     Full-text available via subscription   (Followers: 31, SJR: 2.208, CiteScore: 4)
Advances in Veterinary Medicine     Full-text available via subscription   (Followers: 18)
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: 336, 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: 444, SJR: 1.238, CiteScore: 3)
Agri Gene     Hybrid Journal   (SJR: 0.13, CiteScore: 0)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 16, SJR: 1.818, CiteScore: 5)
Agricultural Systems     Hybrid Journal   (Followers: 32, SJR: 1.156, CiteScore: 4)
Agricultural Water Management     Hybrid Journal   (Followers: 43, SJR: 1.272, CiteScore: 3)
Agriculture and Agricultural Science Procedia     Open Access   (Followers: 1)
Agriculture and Natural Resources     Open Access   (Followers: 2)
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: 9)
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: 10, 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: 50, 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: 44, 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: 34, SJR: 2.973, CiteScore: 4)
American J. of Medicine     Hybrid Journal   (Followers: 45)
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: 204, SJR: 2.7, CiteScore: 4)
American J. of Ophthalmology     Hybrid Journal   (Followers: 63, 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: 27, 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: 37, 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: 6)
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: 16, 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: 40, SJR: 1.512, CiteScore: 5)
Analytical Biochemistry     Hybrid Journal   (Followers: 171, SJR: 0.633, CiteScore: 2)
Analytical Chemistry Research     Open Access   (Followers: 10, 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: 189, 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: 90  
  Partially Free Journal Partially Free Journal
ISSN (Print) 0001-4575
Published by Elsevier Homepage  [3159 journals]
  • The influence of impulsivity and the Dark Triad on self-reported
           aggressive driving behaviours
    • Abstract: Publication date: November 2018Source: Accident Analysis & Prevention, Volume 120Author(s): Laura Ball, Ruth Tully, Vincent EganAbstractThe present study tested the role of Dark Triad traits (DT; narcissism, psychopathy, and Machiavellianism) as potential contributors to self-reported aggressive driving alongside driving anger, general aggression, impulsiveness, and attributions of malign driving intent. Members of the general community (N = 168) completed an online survey battery measuring these characteristics, and a proxy measure of aggressive driving. Regression analyses revealed that psychopathy, a history of physical aggression towards others, and the “progress impeded” aspect of driving anger, accounted for 50.8% of the variance in self-reported aggressive driving behaviours. The remaining variables were not significant. A structural equation model found all measures fitted into a single model in which impulsivity and the DT predicted general aggression, general aggression fully mediated the effect of the DT on driving anger, and general aggression and progress impedance predicted self-reported aggressive driving (GFI = 0.925). These results indicate tendencies toward expressing aggression physically, frustration at goals being impeded, and a callous, impulsive nature can predispose an individual to aggressive driving behaviours. Implications of these findings and recommendations for research are discussed.
  • Multivariate linear intervention models with random parameters to estimate
           the effectiveness of safety treatments: Case study of intersection device
    • Abstract: Publication date: November 2018Source: Accident Analysis & Prevention, Volume 120Author(s): Emanuele Sacchi, Karim El-BasyounyAbstractA novel intervention model that analyzes time-series crash data was recently introduced in the road safety statistical field. The model allows the computation of components related to direct and indirect treatment effects using a linearized time-series intervention model. The isolation of a component corresponding to the direct treatment effects, known as the crash modification function (CMFunction), enables the assessment of safety countermeasures over time. To gain new insights into how crash counts are influenced by covariates and to account for the fact that many components affecting crash occurrence are not easily available (unobserved heterogeneity), the linear intervention models with random parameters are implemented to evaluate the safety impacts of a specific treatment. Both matched-pair and full random parameter models were applied. In addition, the analysis was carried out in a multivariate context to account for possible correlation between dependent variables. The safety treatment selected for this study was the Intersection Safety Device (ISD) program implemented in the City of Edmonton (Alberta, Canada). The safety impacts were estimated by assessing the change in crash severity (property-damage-only vs. fatal-plus-injury) over time. Overall, the results showed a lower deviance information criterion (better goodness of fit) of the multivariate linear intervention model with random parameters compared to the univariate form with fixed parameters. The difference of the indexes of treatment effectiveness between the proposed modeling framework and the univariate model with fixed parameters was estimated up to 2.7%, which indicates the importance of accounting for unobserved heterogeneity.
  • The relationship between driving skill and driving behavior: Psychometric
           adaptation of the Driver Skill Inventory in China
    • Abstract: Publication date: November 2018Source: Accident Analysis & Prevention, Volume 120Author(s): Jing Xu, Juan Liu, Xianghong Sun, Kan Zhang, Weina Qu, Yan GeAbstractMost road accidents are caused by human factors alone or in combination with other factors. Deficits in driving skill are a human factor that contributes to accidents. It is important to focus on driving skills to reduce traffic accidents and enhance safe driving. In this study, we adopted a Chinese version of the Driver Skill Inventory (DSI) and explored its correlation with driving behaviors, sociodemographic factors and personality. A total of 295 licensed drivers voluntarily completed a survey that covered the DSI, the Driver Behavior Questionnaire, the Positive Driver Behavior Scale, self-reported traffic accidents, penalty points and fines, the Big Five Inventory, and sociodemographic parameters. First, the results of principal axis analysis on the DSI yielded two clear factors: perceptual-motor skills and safety skills. Second, both perceptual-motor skills and safety skills were positively correlated with positive behaviors. Safety skills were negatively correlated with all aberrant driving behaviors (e.g., aggressive violations, ordinary violations, errors, and lapses), whereas perceptual-motor skills were negatively correlated with errors and lapses. Third, with regard to penalties, safety skills were negatively associated with penalty fines and points received within the past year, whereas perceptual-motor skills showed no such correlation. Fourth, with regard to sociodemographic parameters, perceptual-motor skills were positively correlated with years of holding a driving license, weekly driving distance and annual driving distance. Men reported higher perceptual-motor skills than women, whereas safety skills were unrelated to gender. Fifth, structural equation modeling was conducted to test the effects of personality traits on driving skill. The results showed that conscientiousness, neuroticism and openness to experience were significant predictors of perceptual-motor skills, whereas agreeableness and conscientiousness were significant predictors of safety skills. Overall, based on these results, the Chinese version of the DSI has acceptable internal consistency and a stable structure; thus, it represents a useful tool to measure driving skill. Moreover, the measurement of personality traits, which are important individual factors closely linked to driving skill, can aid in the education of professional drivers or to inform preventative and educational activities that focus on personality traits in addition to knowledge.
  • An empirical evaluation of multivariate spatial crash frequency models
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Wen Cheng, Gurdiljot Singh Gill, Mohan Dasu, Xudong JiaAbstractMany studies have employed spatial, temporal, or a combination of both specifications for analysis of roadway crashes at different spatial levels. However, there is lack of a comprehensive study which compares the crash estimation performance of different spatial weight matrices and their combination with various temporal treatments. The current study fills the research gap by comparing different Full Bayesian (FB) multivariate spatiotemporal crash models. The pedestrian and bicyclist crash data across an eight-year period for 58 counties in California were used as a case study. Three groups of models were developed based on temporal treatment, where each group comprised of 17 models differing on the basis of different adjacency- and distance-based spatial weight matrices. The first group of multivariate models incorporated only unstructured random error term and spatially structured conditional autoregressive (CAR) term. The second group built upon the former and introduced a linear time trend to develop a spatiotemporal model, while the third group allowed the interaction of space and time. The predictive performance of the alternate models across and within groups was assessed by employing several evaluation criteria.The modeling results demonstrated the robustness of models based on the similar signs and closeness of coefficients for the posterior estimates of parameters. For overall model comparison, the pure-distance model D0.5 demonstrated the best performance for different evaluation criteria based on training and test errors across three groups. The variability in performance of other distance models suggested that caution must be exercised for the choice of exponents. The correlation analysis revealed the presence of positive correlations among the criteria based on training errors, as well as with cross-validation. However, a very strong positive correlation was observed between the criteria based on effective number of parameters and posterior deviance, indicating that an increased number of parameters may not lead to improved model fit. This finding reinforced the importance of selecting the optimum weight matrix for spatial correlation as a more complex structure may not lead to expected advantages at model performance. For comparison among three groups of different temporal treatments, the third group demonstrated the best performance and conveyed the benefits of incorporating the spatial and temporal interaction. The results from ANOVA (analysis of variance) and HSD (Honest Significant Differences) tests also established the existence of statistical differences for the superiority of space-time interactions models. However, the box and whisker plots demonstrated high variability among the models of the third group, suggesting that some models may not benefit from interaction term. For comparison among adjacency- and distance-based models, the distance-based models were mostly observed to be superior. However, the greater variability of model performance associated with distance-based models suggested for careful consideration during their selection. Additionally, it is important to note that the results observed in this study are specific to the county-level crash data of California. As such, the study does not recommend generalization of the results for extension to other spatial levels of roadway network, and readers and future research studies are advised to exercise caution before implementing the models.
  • Validation of the influencing factors associated with traffic violations
           and crashes on freeways of developing countries: A case study of Iran
    • Abstract: Publication date: Available online 9 August 2018Source: Accident Analysis & PreventionAuthor(s): Mansour Hadji Hosseinlou, Alireza Mahdavi, Mehdi Jabbari NooghabiAbstractAmong the rural roads, freeways have the maximum allowable speed limit. This subject increases the tendency of drivers to use these kinds of roads, and despite its positive effects, it has caused numerous problems. One of them is the increase in the rate of traffic violations and crashes. The amount of crashes per kilometer in Iran’s freeways is almost twice the other rural roads. Hence, finding a solution to this problem is of particular importance. This research intends to validate some of the influencing factors which cause traffic violations and crashes in freeways and determine their amount of influence through statistical models. For this purpose, the authors considered violations and crashes for 36 road segments as dependent variables and other factors as independent ones. Since dependent variables were count, discrete, and non-zero, the proposed models were Poisson and Zero-truncated Poisson. The processing of the models indicated that the amounts of Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) indices for the Zero-truncated Poisson model are less than those of the Poisson model and the result of the Pseudo-R2 test for this model is within the acceptable range. Moreover, the result of Chi-square test which shows the proximity of expected and observed amounts was better for Zero-truncated Poisson model. Thus, this model has a considerable advantage against Poisson model. Final models indicated that the average speed has a positive correlation with the number of violations and crashes and as it increases, they increase too. Besides, peripheral landscapes, number of interchanges, number of passing lanes, and exemption from paying toll have an opposite relationship with violations and crashes.
  • Bivariate extreme value modeling for road safety estimation
    • Abstract: Publication date: November 2018Source: Accident Analysis & Prevention, Volume 120Author(s): Lai Zheng, Karim Ismail, Tarek Sayed, Tazeen FatemaAbstractSurrogate safety measures have been advocated as a complementary approach to study safety from a broader perspective than relying on crash data alone. This study proposes an approach to incorporate different surrogate safety measures in a unified framework for road safety estimation within the bivariate extreme value theory framework. The model structure, model specification, threshold selection method, and parameter estimation method of the bivariate threshold excess model are introduced. Two surrogate safety measures, post encroachment time (PET) and length proportion of merging (LPM), are chosen to characterize the severity of merging events on freeway entrance merging areas. Based on the field data collected along Highway 417 in the City of Ottawa, Ontario, Canada, the bivariate modelling methods with seven distribution functions are applied and compared, and the model with logistic distribution function is selected as the best model. The best bivariate models’ estimation results are then evaluated by comparing them to their two marginal (univariate Generalized Pareto distribution) models. The results show that the bivariate models tend to generate crash estimates that are much closer to observed crashes than univariate models. A more important finding is that incorporating two surrogate safety measures into the bivariate models can significantly reduce the uncertainty of crash estimates. The efficiency of a bivariate model is not evidently better than either of its marginal models, but it is expected to be improved with data of a prolonged observation period. This study is also a step forward in the direction of developing multivariate safety hierarchy models, since models of the safety hierarchy have been predominantly univariate.
  • Bike lanes next to on-street parallel parking
    • Abstract: Publication date: November 2018Source: Accident Analysis & Prevention, Volume 120Author(s): Paul SchimekAbstractFor decades it has been the conventional wisdom that crashes involving bicyclists and opening car doors are rare. This belief is based on motor vehicle crash reports, but these reports generally exclude this crash type by definition. More complete sources show that dooring crashes are one of the most common causes of urban bicycle-motor vehicle collisions, accounting for 12%–27% of the total.This paper reviews all available studies of bicyclist position in bike lanes adjacent to on-street parking. With bike lanes meeting current minimum standards, almost all bicyclists were observed riding within range of opening doors. However, when an additional three or four feet is provided between the bike lane and parked cars, hardly any bicyclists are observed in the door zone.All of the design guides recently developed in North America for separated bike lanes include a buffer to account for the door zone when the bike lane is placed between on-street parallel parking and the curb. However, only the Ontario design guide has a similar requirement for standard bike lanes. The buffer requirement for standard bike lanes adjacent to on-street parking should be incorporated into all design guidance.When there is not room for this necessary buffer, an alternative is to place a shared lane marking in the center of the travel lane, which encourages bicyclists to ride outside the door zone. Increasing the number of bicyclists who ride outside of the door zone may require lowering speed limits and repealing laws that create a presumption that bicyclists must always keep to the right of the travel lane.
  • Wildlife warning reflectors do not mitigate wildlife–vehicle
           collisions on roads
    • Abstract: Publication date: November 2018Source: Accident Analysis & Prevention, Volume 120Author(s): Anke Benten, Torsten Hothorn, Torsten Vor, Christian AmmerAbstractWildlife–vehicle collisions cause human fatalities and enormous economic and ecological losses on roads worldwide. A variety of mitigation measures have been developed over the past decades to separate traffic and wildlife, warn humans, or prevent wildlife from entering a road while vehicles are passing by, but only few are economical enough to be applied comprehensively. One such measure, wildlife warning reflectors, has been implemented over the past five decades. However, their efficacy is questioned because of contradictory study results and the variety of applied study designs and reflector models. We used a prospective, randomized non-superiority cross-over study design to test our hypothesis of the inefficacy of modern wildlife warning reflectors. We analyzed wildlife–vehicle collisions on 151 testing sites of approximately 2 km in length each. During the 24-month study period, 1984 wildlife–vehicle collisions were recorded. Confirmatory primary and exploratory secondary analyses using a log-link Poisson mixed model with normal nested random intercepts of observation year in road segment, involved species, and variables of the road segment and the surrounding environment showed that reflectors did not lower the number of wildlife–vehicle collisions by a relevant amount. In addition, variables of the road segment and the surrounding environment did not indicate differential effects of wildlife warning reflectors. Based on our results, we conclude that wildlife warning reflectors are not an effective tool for mitigating wildlife–vehicle collisions on roads.
  • Modeling and comparing injury severity of at-fault and not at-fault
           drivers in crashes
    • Abstract: Publication date: November 2018Source: Accident Analysis & Prevention, Volume 120Author(s): Venkata R. Duddu, Praveena Penmetsa, Srinivas S. PulugurthaAbstractThis paper examines and compares the effect of selected variables on driver injury severity of, both, at-fault and not at-fault drivers. Data from the Highway Safety Information System (HSIS) for the state of North Carolina was used for analysis and modeling. A partial proportional odds model was developed to examine the effect of each variable on injury severity of at-fault driver and not at-fault driver, and, to examine how each variable affects these two drivers’ injury severity differently. Road characteristics, weather condition, and geometric characteristics were observed to have a similar effect on injury severity in a crash to at-fault and not at-fault drivers. Age of the driver, physical condition, gender, vehicle type, and, the number and type of traffic rule violations were observed to play a significant role in the injury severity of not at-fault drivers when compared to at-fault drivers in the crash. Moreover, motorcyclists and drivers 70 years or older are observed to be the most vulnerable road users.
  • Young male drivers’ perceptions of and experiences with YouTube videos
           of risky driving behaviours
    • Abstract: Publication date: November 2018Source: Accident Analysis & Prevention, Volume 120Author(s): Evelyn Vingilis, Zümrut Yildirim-Yenier, Larissa Vingilis-Jaremko, Jane Seeley, Christine M. Wickens, Daniel H. Grushka, Judy FleiterAbstractObjectiveYouTube features millions of videos of high risk driving behaviours and negative consequences of high risk driving (“fails”), such as injuries or deaths. Unfortunately, no information is available on YouTube viewership of these types of sites or on the effects of these videos on viewers. The purpose of this study was to examine young male drivers’ perceptions of and experiences with YouTube videos of risky driving behaviours.MethodsUsing an exploratory qualitative descriptive approach, three 2-hour focus groups were conducted with young men 18–30 years of age to determine: (i) if they watch and share YouTube videos, including high risk driving videos; (ii) what effects high risk driving videos have on them and others and whether YouTube videos of negative consequences discourage high risk driving.ResultsParticipants indicated three uses for YouTube; it has replaced television watching and provides entertainment and information. Motivations of both risky drivers in videos and viewers to engage in high risk driving activities included person characteristics (e.g., sensation seeking and responsivity to financial rewards for high view count videos) and socio-environmental factors (e.g., peer pressure). Most indicated that they would not try to imitate the risky behaviours exhibited in videos, although a few had tried to copy some risky driving moves from videos.ConclusionsSocial, not mass media is now the common information and entertainment source for young people. YouTube videos of high risk driving are common and ubiquitous. Findings from these focus groups suggest that viewers could influence subsequent content of social media videos and reciprocally, videos could influence behaviours of some viewers, particularly young male viewers.
  • Safety performance functions for horizontal curves and tangents on two
           lane, two way rural roads
    • Abstract: Publication date: November 2018Source: Accident Analysis & Prevention, Volume 120Author(s): Jeffrey P. Gooch, Vikash V. Gayah, Eric T. DonnellAbstractHorizontal curves on two-way, two-lane rural roads pose critical safety concerns. Accurate prediction of safety performance at these locations is vital to properly allocate resources as a part of any safety management process. The current method of predicting safety performance on horizontal curves relies on the application of a safety performance function (SPF) developed using only tangent sections and adjusting this value using a crash modification factor (CMF). However, this process inherently assumes that safety performance on curves and tangent sections share the same general functional relationships with variables included in the SPF, notably traffic volumes and segment length, even though research suggests otherwise. In light of this, the goal of this paper is to systematically study the relationship between safety performance and traffic volumes on horizontal curves of two-lane, two-way rural roads and to compare this to the safety performance of tangent sections. The propensity scores-potential outcomes framework is used to help ensure similarity between tangent and curve sections considered in the study, while mixed-effects negative binomial regression is used to quantify safety performance. The results reveal that safety performance on horizontal curves differs significantly from that on tangent sections with respect to both traffic volumes and segment length. Significant differences were also found between the safety performance on tangents and curves relative to other roadway features. These results suggest that curve-specific SPFs should be considered in the next edition of the Highway Safety Manual.
  • Evaluating the safety and operational impacts of left-turn bay extension
           at signalized intersections using automated video analysis
    • Abstract: Publication date: November 2018Source: Accident Analysis & Prevention, Volume 120Author(s): Ahmed Tageldin, Tarek Sayed, Karim IsmailAbstractLeft-turn lanes are commonly introduced to provide space to accommodate comfortable deceleration and adequate storage of turning vehicles. Operational shortcomings may arise due to inadequate length, including overflow and blockage of left-turn entrance by queues on an adjacent through lane. This study investigates the potential safety and operational benefits of treating left-turn lanes by extending the length further upstream a signalized intersection. Video data was collected at three treated left-turn lanes as well as three matched control lanes; all in both before and after treatment conditions. Safety parameters consisted of the counts and severities of traffic conflicts occurring on the left-turn lanes and inside the intersection. There was a marked reduction in traffic conflict counts in all treated sites. The overall treatment effect, which accounts for the simultaneous change in control sites, was 63.2% (p 
  • Investigating factors of crash frequency with random effects and random
           parameters models: New insights from Chinese freeway study
    • Abstract: Publication date: November 2018Source: Accident Analysis & Prevention, Volume 120Author(s): Qinzhong Hou, Andrew P. Tarko, Xianghai MengAbstractIn response to the rapid economic growth in China, its freeway system has become the longest in the world and likely will continue to expand. Unfortunately, the safety issues on freeways in China have grown as well and are of great concern to Chinese transportation authorities and drivers. While many proven safety countermeasures developed and implemented by other countries are available for reference, they may be not fully transferrable to China due to the differences in driving cultures and conditions. As a result, an investigation of China’s unique safety factors and effective relevant countermeasures are urgently needed.The study presented in this paper thoroughly investigated the factors contributing to freeway crashes in China based on detailed crash data, traffic characteristics, freeway geometry, pavement conditions, and weather conditions. To properly account for the over-dispersion of data and unobserved heterogeneity, a random effects negative binomial (RENB) model and a random parameters negative binomial (RPNB) model were applied, along with a negative binomial (NB) model. The analysis revealed a large number of crash frequency factors, including several interesting and important factors rarely studied in the past, such as the safety effects of climbing lanes. Moreover, the RENB and RPNB models were found to considerably outperform the NB model; however, although the RPNB exhibited better goodness-of-fit than the RENB model, the difference was rather small. The findings of this study shed more light on the factors influencing freeway crashes in China. The results will be useful to highway designers and engineers for creating, building, and operating safe freeways as well as to safety management departments for developing effective safety countermeasures. The study presented in this paper also provides additional guidance for choosing relevant methods to analyze safety and to identify safety factors.
  • Approach-level real-time crash risk analysis for signalized intersections
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Jinghui Yuan, Mohamed Abdel-AtyAbstractIntersections are among the most dangerous roadway facilities due to the complex traffic conflicting movements and frequent stop-and-go traffic. However, previous intersection safety analyses were conducted based on static and highly aggregated data (e.g., annual average daily traffic (AADT), annual crash frequency). These aggregated data may result in unreliable findings simply because they are averages and cannot represent the real conditions at the time of crash occurrence. This study attempts to investigate the relationship between crash occurrence at signalized intersections and real-time traffic, signal timing, and weather characteristics based on 23 signalized intersections in Central Florida. The intersection and intersection-related crashes were collected and then divided into two types, i.e., within intersection crashes and intersection entrance crashes. Bayesian conditional logistic models were developed for these two kinds of crashes, respectively. For the within intersection models, the model results showed that the through volume from “A” approach (the traveling approach of at-fault vehicle), the left turn volume from “B” approach (near-side crossing approach), and the overall average flow ratio (OAFR) from “D” approach (far-side crossing approach), were found to have significant positive effects on the odds of crash occurrence. Moreover, the increased adaptability for the left turn signal timing of “B” approach and more priority for “A” approach could significantly decrease the odds of crash occurrence. For the intersection entrance models, average speed was found to have significant negative effect on the odds of crash occurrence. The longer average green time and longer average waiting time for the left turn phase, higher green ratio for the through phase, and higher adaptability for the through phase can significantly improve the safety performance of intersection entrance area. In addition, the average queue length on the through lanes was found to have positive effect on the odds of crash occurrence. These results are important in real-time safety applications at signalized intersections in the context of proactive traffic management.
  • A Bayesian multivariate hierarchical spatial joint model for predicting
           crash counts by crash type at intersections and segments along corridors
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Saif A. Alarifi, Mohamed Abdel-Aty, Jaeyoung LeeAbstractThe safety and operational improvements of corridors have been the focus of many studies since they carry most traffic on the road network. Estimating a crash prediction model for total crash counts identifies the crash risk factors that are associated with crash counts at a specific type of road entity. However, this may not reveal useful information to detect the road problems and implement effective countermeasures. Therefore, investigating the contributing factors for crash counts by different types is of great importance. This study aims to provide a good understanding of the contributing factors to crash counts by different types at intersections and roadway segments along corridors. Data from 255 signalized intersections and 220 roadway segments along 20 corridors have been used for this study. The investigated crash types include same direction, angle and turning, opposite direction, non-motorized, single vehicle, and other multi-vehicle crashes. Two models have been estimated, which are multivariate hierarchical Poisson-lognormal (HPLN) spatial joint model and univariate HPLN spatial joint model. The significant variables include exposure measures and some geometric design variables at intersection, roadway segment, and corridor levels. The results revealed that the multivariate HPLN spatial joint model outperforms the univariate HPLN spatial joint model. Also, the correlations among crash counts of most types exist at individual road entity and between adjacent entities. Additionally, the significant explanatory variables are different across crash types, and the magnitude of the parameter estimates for the same independent variable is different across crash types. The results emphasize the need for estimating crash counts by type in a multivariate form to better detect the problems and provide appropriate countermeasures.
  • Traffic accident risk assessment with dynamic microsimulation model using
           range-range rate graphs
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Gennady Waizman, Shraga Shoval, Itzhak BenensonAbstractAnalysis of accidents that involve vehicles and pedestrians requires accurate reproduction of the dynamics of the vehicles and pedestrians immediately prior to and during the accident. In many cases, only centimeters and milliseconds separate survival from disaster, particularly when high-speed aggressive drivers and careless pedestrians are involved. In this paper we present a methodology for analyzing the dynamic interaction between drivers in conflict scenarios with pedestrians. We assess the safety of a traffic location’s environment with a high-resolution, spatially explicit, dynamic agent-based simulation model – SAFEPED. Based on the resulting data, Range-Range Rate (R-RR) graphs are generated. These graphs provide compact, simple, and objective presentation of the dynamic interaction between vehicles and pedestrians. Significant traffic risk indicators such as Time-To-Collision, acceleration/deceleration rates, and minimal distances between vehicles and pedestrians are easily extracted from the R-RR graphs. These indicators can provide insights on particular traffic scenarios and can assist road planners and developers of traffic safety measures in understanding the dynamic behavior of drivers and pedestrians before and during a conflict scenario.
  • Systematic review of observational studies on secondary task engagement
           while driving
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Anja Katharina Huemer, Markus Schumacher, Melina Mennecke, Mark VollrathAbstractThe last decade has seen a worldwide exponential increase in the use of mobile information systems, especially smartphones. This trend covers all areas of life, and also seems to include phone use while driving. In order to assess the scope of secondary task occupation, especially smartphone use while driving, observation studies from outside the car have been established as an efficient and valid method. A review of international studies using traffic observation was done finding 51 publications with a total of 117 observation studies with more than 1,800,000 single observations at more than 17,500 sites from nine different countries. The review describes the relevant aspects of the observation methods and gives an overview about the trends found in the data. As the methods differ widely over the years as well as between the countries and studies, an integration of the results is not possible. However, from all studies it is very clear that smartphone use has increased including not only phoning while driving but also, more important to traffic safety, using apps and texting on the smartphone. Additional observable secondary tasks were only rarely examined. Thus, further research using observational studies is strongly recommended. Suggestions are given with regard to the methodology which can contribute to get comparable and valid results across countries and studies.
  • Which drivers are at risk' Factors that determine the profile of the
           reoffender driver
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Jose-Luis Padilla, Pablo Doncel, Andres Gugliotta, Candida CastroAbstractFinding appropriate assessment tools to predict recidivism is a difficult aim, which may lead to actions with unintended consequences. Aims don’t have consequences. At times, the research has been used to justify penalising reoffenders with punitive measures rather than treating them with effective psychological interventions. This study aims to contribute to untangling and assessing the potential predictors of reoffender drivers. In this study, 296 drivers: 86 reoffenders (7 women and 79 men) and 206 non-reoffenders (105 women and 101 men) responded to a battery of assessment questionnaires in which they were asked for demographic data (i.e. gender and age), alcohol consumption habits, driving styles, general estimation of risk in everyday life, sensitivity to reward and punishment and anger while driving. The results provided a logistical regression model capable of predicting reoffending and explaining 34% of variability, successfully classifying 77.6% of participants. In this model, the best predictor of reoffending is higher consumption of alcohol (Alcohol Use Disorders, AUD), followed by incautious driving (since cautious driving style correlates negatively with reoffending) and to a lesser extent, infraestimation of recreational risk and a greater sensitivity to reward. Relying on results to predict recidivism could be important to plan better interventions to prevent it.
  • Speed change behavior on combined horizontal and vertical curves: driving
           simulator-based analysis
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Xiaomeng Wang, Xuesong WangAbstractRoad alignments that combine horizontal and vertical curves on freeways have effects on drivers’ speed changes that can lead to safety problems. This study examines speed changes on four types of combined curves: downslope, upslope, crest and sag. From design blueprints for a mountainous freeway under construction in Hunan Province, a total of 70 combined curves were programmed into the Tongji University driving simulator. Study participants drove through the simulated freeway while vehicle operation data was continuously captured. Speed changes on the combined curves were determined by calculating the differences between minimum and maximum speed values, and were classified into three behaviors: substantial speed decrease, steady speed (minimal change), and substantial speed increase. Multinomial logit models were used and the marginal effects of each variable were calculated in order to examine the effects on speed change behavior of each combined curve type and their adjacent segments. Results show that: 1) the speed change behaviors on the four types of combined curves differ in frequency, 2) the significant effects of geometric design characteristics on speed change differed by type of combined curve, and 3) design characteristics of adjacent segments also have significant and varying effects on speed change. Combined curves should therefore be studied separately, and their adjacent segments should be considered when combined curves are planned.
  • A heterogeneity based case-control analysis of motorcyclist’s injury
           crashes: Evidence from motorcycle crash causation study
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Behram Wali, Asad J. Khattak, Aemal J. KhattakAbstractThe main objective of this study is to quantify how different “policy-sensitive” factors are associated with risk of motorcycle injury crashes, while controlling for rider-specific, psycho-physiological, and other observed/unobserved factors. The analysis utilizes data from a matched case-control design collected through the FHWA’s Motorcycle Crash Causation Study. In particular, 351 cases (motorcyclists involved in injury crashes) are analyzed vis-à-vis similarly-at-risk 702 matched controls (motorcyclists not involved in crashes). Unlike traditional conditional estimation of relative risks, the paper presents heterogeneity based statistical analysis that accounts for the possibility of both within and between matched case-control variations. Overall, the correlations between key risk factors and injury crash propensity exhibit significant observed and unobserved heterogeneity. The results of best-fit random parameters logit model with heterogeneity-in-means show that riders with partial helmet coverage (U.S. DOT compliant helmets with partial coverage, least intrusive covering only the top half of the cranium) have a significantly lower risk of injury crash involvement. Lack of motorcycle rider conspicuity captured by dark (red) upper body clothing is associated with significantly higher injury crash risk (odds ratio 3.87, 95% CI: 1.63, 9.61). Importantly, a rider’s motorcycle-oriented lower clothing (e.g., cannot easily get stuck in the machinery) significantly lowers the odds of injury crash involvement. Regarding the effectiveness of training, formal motorcycle driving training in recent years was associated with lower injury crash propensity. Finally, riders with less sleep prior to crash/interview exhibited 1.97 times higher odds of crash involvement compared to riders who had more than 5 h of sleep. Methodologically, the conclusion is that the correlations of several rider, exposure, apparel, and riding history related factors with crash risk are not homogeneous and in fact vary in magnitude as well as direction. The study results indicate the need to develop appropriate countermeasures, such as refresher motorcycle training courses, prevention of sleep-deprived/fatigued riding, and riding under the influence of alcohol and drugs.
  • A new approach for calibrating safety performance functions
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Ahmed Farid, Mohamed Abdel-Aty, Jaeyoung LeeAbstractSafety performance functions (SPFs) are statistical regression models used for estimating crash counts by roadway facility classification. They are required for identifying high crash risk locations, assessing the effectiveness of safety countermeasures and comparing road designs in terms of safety. Roadway agencies may opt to develop local SPFs or adopt them from elsewhere such as the national Highway Safety Manual (HSM), provided by the American Association of State Highway and Transportation Officials. The HSM offers a simple technique to calibrate its SPFs to conditions of specific jurisdictions. A more recent calibration technique, also known as the calibration function, is similar to that of the HSM. In this research, we develop SPFs of total crashes for rural divided multilane highway segments in four states. The states are Florida, Ohio, California and Washington. We also calibrate each SPF to each state using the HSM calibration method and the calibration function. Furthermore, we propose the use of the K nearest neighbor data mining method for calibrating SPFs. According to the goodness of fit (GOF) results, our proposed calibration method performs better than the other two methods.
  • Freeway crash risks evaluation by variable speed limit strategy using
           real-world traffic flow data
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Zeyang Cheng, Jian Lu, Yunxuan LiAbstractThe primary objective of this study is to evaluate the real-time crash risk of freeways by using real-world traffic flow data. The crash risk expressed as the potential crash likelihood is assessed under variable speed limit (VSL) and without VSL, in which both spatial correlation between different sites and temporal similarity are contained. Traffic flow data of Whitemud Drive network (WMD) in Canada is used to perform the relevant analysis, including VSL implementation analysis, traffic flow similarity analysis, crash risk and congestion analysis. Analytical results demonstrate that the average traffic flow under VSL schemes 1, 2, 3 and 4 are highly correlated from spatial-temporal perspective. The crash likelihoods and congestions under these VSL schemes are greatly improved. The best VSL control scheme, the most dangerous area and time, together with the most congested station of WMD are eventually determined. Subsequently, a t-test is employed to examine the significance of these results. t-Test results suggest that the improvement degree between crash risk and congestion under the best VSL control scheme show a difference, i.e., the best VSL control scheme can reduce the crash risk of moderate risk area more than high risk area, while it may have a larger melioration on the most congested area than the relatively uncongested area. Finally, these results are considered to have the potential reference in the mitigation of WMD traffic issues.
  • Heat waves and fatal traffic crashes in the continental United States
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Connor Y.H. Wu, Benjamin F. Zaitchik, Julia M. GohlkeAbstractBackgroundA better understanding of how heat waves affect fatal traffic crashes will be useful to promote awareness of drivers’ vulnerability during an extreme heat event.Objective and MethodsWe applied a time-stratified case-crossover design to examine associations between heat waves and fatal traffic crashes during May-September of 2001–2011 in the continental United States (US). Heat waves, defined as the daily mean temperature>95% threshold for ≥2 consecutive days, were derived using gridded 12.5 km2 air temperatures from Phase 2 of the North American Land Data Assimilation System (NLDAS-2). Dates and locations of fatal traffic crash records were acquired from the National Highway Traffic Safety Administration (NHTSA).ResultsResults show a significant positive association between fatal traffic crashes and heat waves with a 3.4% (95% CI: 0.9, 5.9%) increase in fatal traffic crashes on heat wave days versus non-heat wave days. The association was more positive for 56–65 years old drivers [8.2% (0.3, 16.7%)] and driving on rural roadways [6.1% (2.8, 9.6%)]. Moreover, a positive association was only present when the heat wave days were characterized by no precipitation [10.9% (7.3%, 14.6%)] and medium or high solar radiation [24.6% (19.9%, 29.5%) and 19.9% (15.6%, 24.4%), respectively].ConclusionsThese findings are relevant for developing targeted interventions for these driver groups and driving situations to efficiently reduce the negative effects of heat waves on fatal traffic crashes.
  • How does intersection field of view influence driving safety in an
           emergent situation'
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Xuedong Yan, Xinran Zhang, Qingwan XueAbstractRestricted intersection field of view (IFOV) can influence drivers’ hazard detection abilities and driving safety in an emergent traffic event. However, no field studies or crash-data analyses have been conducted to prove the adequateness of the current intersection sight-distance design standards, which are adopted to ensure that the approaching-intersection drivers have a sufficient field of view to detect traffic hazards and travel safely at intersections. In this study, we conducted a driving simulator experiment to compare drivers’ behavioral and eye-movement measures between different IFOV conditions that met the current intersection sight distance design standards. We examined the influencing mechanism of IFOV on the drivers' collision avoidance process being composed of three consequential stages, respectively in terms of search stage, decision stage and action stage. Our experiment results showed that restricted IFOV impacts the three-stage driving performance interlockingly. Enlarging IFOV can significantly improve drivers' performance in detecting a conflicting vehicle more timely, having a longer perception-reaction time in monitoring the hazard, spending more time on observing intersection surroundings, and taking brake actions earlier and more smoothly so that drivers were more likely to successfully avoid colliding with the conflicting vehicle. In addition, we found that compared with female drivers, male drivers were less likely to take brake actions to avoid a potential collision and had a lower deceleration rate in the braking stage of collision avoidance while there was no significant gender difference in crash involvement rates. The findings indicated that male drivers were more skillful in vehicle control than female drivers. Nevertheless, male drivers had less traffic-crash expectation, which degraded their overall crash avoidance effect. Considering the traffic safety that more than five million intersection-related crashes occur in American each year, these experimental findings have implications for public safety and health.
  • The mediating effect of traffic safety climate between pedestrian
           inconvenience and pedestrian behavior
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Jing Xu, Yan Ge, Weina Qu, Xianghong Sun, Kan ZhangAbstractBecause most people are pedestrians at some point on any given day and walking is the most indispensable means of transportation, pedestrian safety should be investigated. The primary aim of this study was to investigate the relationships among the inconveniences that pedestrians perceive in city traffic, the traffic safety climate and pedestrian behavior. A total of 311 participants voluntarily and validly completed a survey that included the Pedestrian Inconvenience Questionnaire (PIQ), the Traffic Climate Scale (TCS) and the Pedestrian Behavior Scale (PBS). We discovered that pedestrians’ perceived inconvenience was positively correlated with transgression and positive behavior by pedestrians and it also positively correlated with the external affective demands (emotional engagement facet of TCS) while negatively correlated with the functionality (functional traffic system facet of TCS). We determined that the external affective demands were positively correlated with pedestrian risk behaviors (i.e., transgression, aggressive behaviors and lapses), internal requirements (traffic participants’ skills facet of TCS) were positively correlated with positive behaviors, and functionality was negatively correlated with transgression and lapses. Moreover, the results indicate that the relationship between the inconveniences pedestrians perceive in city traffic and pedestrians’ transgressive behavior was fully mediated by the functionality dimension of the traffic safety climate. Pedestrians’ perceived inconvenience is an important factor that affects pedestrian behavior, and the influence of pedestrians’ perceptions of the traffic safety climate cannot be disregarded.
  • Development of a global inertial consistency model to assess road safety
           on Spanish two-lane rural roads
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): David Llopis-Castelló, Francisco Javier Camacho-Torregrosa, Alfredo GarcíaAbstractThe most important factors for road crash occurrence are infrastructure, vehicle, and human factors. In fact, infrastructure and its interaction with human factor have been thoroughly studied in recent years through geometric design consistency, which can be defined as how drivers’ expectations and road behavior relate.Global consistency models were calibrated in the last decade to assess road safety on an entire homogeneous road segment. However, none of them include the underlying consistency phenomenon in their formulation.Recently, a new model was developed based on the difference between the inertial operating speed profile, which represents drivers’ expectancies, and the operating speed profile, which represents road behavior. While the operating speed represents the estimated operating speed for every location along the road, the inertial operating speed aggregates for every station the operating speed effect along some distance already covered by drivers. The authors hypothesized that this ‘aggregation effect’ was connected to drivers’ expectancies, which proved to be true based on the best model fitted. However, the exact distance (or time) that should be considered to estimate the inertial operating speed still remains unknown. This paper aims to complete this model, analyzing how the inertial operating speed varies depending on different distances and periods of time. This impact is measured considering the reliability of the corresponding consistency model. The paper also covers how the inertial operating speed should be determined along the final distance or time. For this, a total of 184 homogeneous road segments along 650 km in Spain were used.
  • The driver-level crash risk associated with daily cellphone use and
           cellphone use while driving
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Jon Atwood, Feng Guo, Greg Fitch, Thomas A. DingusAbstractThis study examined the overall prevalence of cellphone use, including the rates of calls and texts both per day and hourly while driving, and assessed whether or not individual crash risk was correlated with cellphone use. The study used data from the Second Strategic Highway Research Program Naturalistic Driving Study (SHRP 2 NDS), which had more than 3500 participants who provided up to three years of driving data. Of these participants, 620 provided cellphone records, 564 of which included both call and text records. The prevalence of cellphone calls and texts per day was calculated. By overlaying the cellphone records with the SHRP 2 NDS data, we also evaluated the rates of calls and texts while driving by driver demographics. Crashes for these cellphone-using participants were also identified from the SHRP 2 NDS data. Negative binomial regression models were used to determine whether the crash rate was associated with cellphone use. Participants made an average of 27.1 texts and 7.3 calls per day. They averaged 1.6 texts and 1.2 calls per hour of driving. Cellphone use varied significantly by age, especially for texting. The texting rate for drivers aged 16–19 was 59.4 per day and 2.9 per hour of driving, four times higher than the 14.3 per day and 1.0 per hour for drivers 30–64 years old. The texting rate for drivers 20–29 years old was also high at 42.4 per day and 2.6 per hour of driving. Participants experienced 243 crashes in 216,231 h of driving. It was found that those who texted more often per day or per hour of driving had higher crash rates after adjusting for age and gender effects. The severe crash rate increases 0.58% for every additional text per day and all 8.3% for every text per hour of driving; overall crash rate increases 0.41% for every additional text per day and 6.46% for every text per hour of driving. The results show that cellphone texting and calling are quite common while driving. The texting rate for young drivers is substantially higher than for middle-aged and senior drivers. This study confirmed that those who text at a higher rate are associated with a higher crash risk.
  • 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 YannisAbstractAn 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.
  • Health and safety practitioners’ health and wellbeing — The link with
           safety climate and job demand-control-support
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Sara Leitão, Vera J.C. Mc Carthy, Birgit A. GreinerAbstractBackground/AimsHealth and Safety Practitioners (HSPs), as frontline professionals advocating for health and safety (HS) working conditions, have crucial roles for the wellbeing of employees. However, research studying HSPs psychosocial working conditions - i.e. job demands, control and support (JDCS) -, safety climate (SC) and their impact on HSPs health and wellbeing is scarce. This novel study aims to examine the link of JDCS and SC with HSPs’ health, wellbeing and efficacy.MethodsA web-survey was completed by 879 HSPs, members of the Institution of Occupational Safety and Health (IOSH) in Ireland and the UK. Multiple linear regression analysis was used to determine the association between JDCS, SC and general health (GHQ12), mental wellbeing (WEMWBS) and efficacy.ResultsAfter adjusting for age, gender and years of experience, job demands were significantly associated with HSPs health (β = 0.40; p = 0.00) and mental wellbeing (β=-0.29; p = 0.00). Positive significant independent associations were also found between job control, support, SC and HSPs health, mental-wellbeing as well as efficacy. In a final model, all psychosocial working conditions and SC were significantly associated with health and mental-wellbeing of HSPs.ConclusionThis study showed that psychosocial working conditions and SC can affect HSPs health and wellbeing - associations rarely previously recorded. The link of safety climate with HSPs efficacy, with contribution of job control and support, reveals possible further impacts of SC on safety performance. The findings highlight the importance of HSPs working conditions while reflecting on the wider impact on OHS in organisations, its workforce and stakeholders.
  • Quantifying drivers’ visual perception to analyze accident-prone
           locations on two-lane mountain highways
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Bo Yu, Yuren Chen, Shan Bao, Duo XuAbstractOwing to constrained topography and road geometry, mountainous highways are subjected to frequent traffic accidents, and these crashes have relatively high mortality rates. In middle and high mountains, most roads are two-lane highways. Most two-lane mountain highways are located in rural areas in China, where traffic volume is relatively small; namely, traffic accidents are mainly related to the design of roads, rather than the impact of traffic flow. Previous studies primarily focused on the relationship between actual road geometry and traffic safety. However, some scholars put forward that there was a significant discrepancy between actual and visual perceived information. Drivers greatly depend on what they perceived by their vision to determine driving behavior. Thus, in this paper drivers’ visual lane model was established to quantify drivers’ visual perception. To further explore drivers’ perception of horizontal and vertical alignments, the visual lane model was projected onto horizontal and vertical planes in drivers’ vision respectively. The length and curvature of the visual curve were extracted as shape parameters of drivers’ visual lane models. Real vehicle driving tests were conducted on typical two-lane mountain highway sections of G318 in Tibet, China. Then the differences of visual perception at black spots and accident-free locations were analyzed and compared. In horizontal and vertical projections of visual lane model, there were 9 shape parameters have significant differences between accident-prone and accident-free locations. A probabilistic neural network (PNN) was formed to identify accident-prone locations on two-lane mountain highways. This study will lay a foundation for the improvement of traffic safety on mountain highways based on the quantification of drivers’ visual perception, during the phase of both road design and reconstruction, and can also make a contribution to the automatic driving technique.
  • Do Silver Zones reduce auto-related elderly pedestrian collisions'
           Based on a case in Seoul, South Korea
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Yunwon Choi, Heeyeun Yoon, Eunah JungAbstractInaugurated in 2007, in Seoul, South Korea, the Silver Zone is a designated pedestrian safety zone for the elderly that adopts speed limit measures such as traffic signage and road surface markings. In this study, we empirically investigate the effectiveness of the Silver Zone in two respects: first, whether the establishment of the Silver Zone has lowered the number of elderly pedestrian collisions, and second, whether Silver Zones are established in the appropriate areas, that is, those with the highest frequency of such collisions. From our quasi-experimental statistical analysis, Difference-in-Difference, we learn that the Silver Zone has no effects on reducing elderly pedestrian collisions. From our spatial statistical analyses—Kernel Density mapping and Bivariate Moran’s I—we found a spatial mismatch between the frequency of senior pedestrian-vehicular collisions and the location of Silver Zones. For better performance of the Silver Zone system, we suggest additional types of physical measures to be integrated into the Silver Zone system. Municipal-level comprehensive master plan for Silver Zone system is also necessary, under which local governments should use periodic surveys to inventory and prioritise the locations of highest elderly pedestrian-vehicular collisions.
  • A study on correlation of pedestrian head injuries with physical
           parameters using in-depth traffic accident data and mathematical models
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Jing Huang, Yong Peng, Jikuang Yang, Dietmar Otte, Bingyu WangAbstractThe objective of the present study is to predict brain injuries and injury severities from realworld traffic accidents via in-depth investigation of head impact responses, injuries and brain injury tolerances. Firstly, a total of 43 passenger car versus adult pedestrian accidents were selected from two databases of the In-depth Investigation of Vehicle Accidents in Changsha of China (IVAC) and the German In-Depth Accident Study (GIDAS). In a previous study the 43 accidents were reconstructed by using the multi-body system (MBS) model (Peng et al., 2013a) for determining the initial conditions of the head-windscreen impact in each accident. Then, a study of the head injuries and injury mechanisms is carried out via 43 finite element (FE) modelings of a head strike to a windscreen, in which the boundary and loading conditions are defined according to results from accident reconstructions, including impact velocity, position and orientation of the head FE model. The brain dynamic responses were calculated for the physical parameters of the coup/countercoup pressure, von Mises and maximum shear stresses at the cerebrum, the callosum, the cerebellum and the brain stem. In addition, head injury criteria, including the cumulative strain damage measure (CSDM) (with tissue level strain threshold 0.20) and the dilatational damage measure (DDM), were developed in order to predict the diffuse axonal injury (DAI) and contusions, respectively. The correlations between calculated parameters and brain injuries were determined via comparing the simulation results with the observed injuries in accident data. The regression models were developed for predicting the injury risks in terms of the brain dynamic responses and the calculated CSDM and DDM values. The results indicate that the predicted values of 50% probability causing head injuries in the Abbreviated Injury Scale (AIS) 2+ correspond to coup pressure 167 kPa, countercoup pressure −117 kPa, von Mises 16.3 kPa and shear stress 7.9 kPa respectively, and causing AIS 3+ head injuries were 227 kPa, −169 kPa, 24.2 kPa and 12.2 kPa respectively. The results also suggest that a 50% probability of contusions corresponds to CSDM value of 48% at strain levels of 0.2, and the 50% probability of contusions corresponds to a DDM value of 6.7%.
  • Applying a random parameters Negative Binomial Lindley model to examine
           multi-vehicle crashes along rural mountainous highways in Malaysia
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Rusdi Rusli, Md. Mazharul Haque, Amir Pooyan Afghari, Mark KingAbstractRoad safety in rural mountainous areas is a major concern as mountainous highways represent a complex road traffic environment due to complex topology and extreme weather conditions and are associated with more severe crashes compared to crashes along roads in flatter areas. The use of crash modelling to identify crash contributing factors along rural mountainous highways suffers from limitations in data availability, particularly in developing countries like Malaysia, and related challenges due to the presence of excess zero observations. To address these challenges, the objective of this study was to develop a safety performance function for multi-vehicle crashes along rural mountainous highways in Malaysia. To overcome the data limitations, an in-depth field survey, in addition to utilization of secondary data sources, was carried out to collect relevant information including roadway geometric factors, traffic characteristics, real-time weather conditions, cross-sectional elements, roadside features, and spatial characteristics. To address heterogeneity resulting from excess zeros, three specialized modelling techniques for excess zeros including Random Parameters Negative Binomial (RPNB), Random Parameters Negative Binomial – Lindley (RPNB-L) and Random Parameters Negative Binomial – Generalized Exponential (RPNB-GE) were employed. Results showed that the RPNB-L model outperformed the other two models in terms of prediction ability and model fit. It was found that heavy rainfall at the time of crash and the presence of minor junctions along mountainous highways increase the likelihood of multi-vehicle crashes, while the presence of horizontal curves along a steep gradient, the presence of a passing lane and presence of road delineation decrease the likelihood of multi-vehicle crashes. Findings of this study have significant implications for road safety along rural mountainous highways, particularly in the context of developing countries.
  • The effect of ‘smart’ financial incentives on driving
           behaviour of novice drivers
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Duncan Mortimer, Jasper S. Wijnands, Anthony Harris, Alan Tapp, Mark StevensonAbstractRecent studies have demonstrated that financial incentives can improve driving behaviour but high-value incentives are unlikely to be cost-effective and attempts to amplify the impact of low-value incentives have so far proven disappointing. The present study provides experimental evidence to inform the design of ‘smart’ and potentially more cost-effective incentives for safe driving in novice drivers. Study participants (n = 78) were randomised to one of four financial incentives: high-value penalty; low-value penalty; high-value reward; low-value reward; allowing us to compare high-value versus low-value incentives, penalties versus rewards, and to test specific hypotheses regarding motivational crowding out and gain/loss asymmetry. Results suggest that (i) penalties may be more effective than rewards of equal value, (ii) even low-value incentives can deliver net reductions in risky driving behaviours and, (iii) increasing the dollar-value of incentives may not increase their effectiveness. These design principles are currently being used to optimise the design of financial incentives embedded within PAYD insurance, with their impact on the driving behaviour of novice drivers to be evaluated in on-road trials.
  • Selecting anti-speeding messages for roadside application
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): A. Ian Glendon, Ioni Lewis, Kfir Levin, Bonnie HoAbstractPurposeAnalyze qualitative and quantitative data to determine the relative effectiveness of theoretically-developed anti-speeding messages, as judged by relatively inexperienced and experienced drivers, both for themselves as a driver, and for drivers in general.MethodEight focus groups and three individual interviews were conducted. Participants initially completed a questionnaire, ranking sets of three anti-speeding messages representing each of the six components of protection motivation theory (PMT). Participants were encouraged to write down the reasons for their rankings. During group and individual facilitation sessions, the rankings and reasons for them were discussed to identify salient reasons for participants’ judgments. The ranking data were analyzed quantitatively, with individual and group-based comments being analyzed thematically.ResultsQuantitative analyses of message pairs revealed five third-person effects (TPEs). Three messages were perceived as more relevant to drivers in general than to the participant-as-driver while two were associated with reverse TPEs, which participants perceived as more relevant to themselves-as-driver than for drivers in general. For four PMT components (rewards, self-efficacy, response efficacy, response costs), one or more messages received significantly higher rankings than one or more other messages representing the same component. Substantial variation was found within the individual and group discussion comments in respect of nearly all the messages, reflecting different driver perspectives and demographics.DiscussionA general preference for shorter messages was evident, leading to a revision of most of the messages comprising the stimuli for this study. On the basis of the focus group and interview responses, consideration was given as to which messages would be recommended for a pilot field study.
  • Investigation of flashing and intensity characteristics for
           vehicle-mounted warning beacons
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Kristin Kersavage, Nicholas P. Skinner, John D. Bullough, Philip M. Garvey, Eric T. Donnell, Mark S. ReaAbstractReducing the potential for crashes involving front line service workers and passing vehicles is important for increasing worker safety in work zones and similar locations. Flashing yellow warning beacons are often used to protect, delineate, and provide visual information to drivers within and approaching work zones. A nighttime field study using simulated workers, with and without reflective vests, present outside trucks was conducted to evaluate the effects of different warning beacon intensities and flash frequencies. Interactions between intensity and flash frequency were also analyzed. This study determined that intensitiesof 25/2.5 cd and 150/15 cd (peak/trough intensity) provided the farthest detection distances of the simulated worker. Mean detection distances in response to a flash frequency of 1 Hz were not statistically different from those in response to 4 Hz flashing. Simulated workers wearing reflective vests were seen the farthest distances away from the trucks for all combinations of intensity and flash frequency.
  • The effects of training impulse control on simulated driving
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Julie Hatfield, Ann Williamson, E. James Kehoe, James Lemon, Amaël Arguel, Prasannah Prabhakharan, R. F. Soames JobAbstractThere is growing interest in young driver training that addresses age-related factors, including incompletely developed impulse control. Two studies investigated whether training of response inhibition can reduce risky simulated driving in young drivers (aged 16–24 years). Each study manipulated aspects of response inhibition training then assessed transfer of training using simulated driving measures including speeding, risky passing, and compliance with traffic controls. Study 1 (n = 65) used a Go/No-go task, Stop Signal Task and a Collision Detection Task. Designed to promote engagement, learning, and transfer, training tasks were driving-relevant and adaptive (i.e. difficulty increased as performance improved), included performance feedback, and were distributed over five days. Control participants completed matching “filler” tasks. Performance on trained tasks improved with training, but there was no significant improvement in simulated driving. Study 2 enhanced response inhibition training using Go/No-go and SST tasks, with clearer performance feedback, and 10 days of training. Control participants completed testing only, in order to avoid any possibility of training response inhibition in the filler tasks. Again performance on trained tasks improved, but there was no evidence of transfer of training to simulated driving. These findings suggest that although training of sufficient interest and duration can improve response inhibition task performance, a training schedule that is likely to be acceptable to the public does not result in improvements in simulated driving. Further research is needed to investigate whether response inhibition training can improve risky driving in the context of real-world motivations for risky driving.
  • Likelihood estimation of secondary crashes using Bayesian complementary
           log-log model
    • Abstract: Publication date: October 2018Source: Accident Analysis & Prevention, Volume 119Author(s): Angela E. Kitali, Priyanka Alluri, Thobias Sando, Henrick Haule, Emmanuel Kidando, Richard LentzAbstractSecondary crashes (SCs) occur within the spatial and temporal impact range of a primary incident. They are non-recurring events and are major contributors to increased traffic delay, and reduced safety, particularly in urban areas. However, the limited knowledge on the nature of SCs has largely impeded their mitigation strategies. The primary objective of this study was to develop a reliable SC risk prediction model using real-time traffic flow conditions. The study data were collected on a 35-mile I-95 freeway section for three years in Jacksonville, Florida. SCs were identified based on travel speed data archived by the Bluetooth detectors. Bayesian random effect complementary log-log model was used to link the probability of SCs with real-time traffic flow characteristics, primary incident characteristics, environmental conditions, and geometric characteristics. Random forests technique was used to select the important variables. The results indicated that the following variables significantly affect the likelihood of SCs: average occupancy, incident severity, percent of lanes closed, incident type, incident clearance duration, incident impact duration, and incident occurrence time. The study results have the potential to proactively prevent SCs.
  • A novel method for imminent crash prediction and prevention
    • Abstract: Publication date: Available online 12 July 2018Source: Accident Analysis & PreventionAuthor(s): Zhi Chen, Xiao QinAbstractA 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 YangAbstractTraditional 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.
  • A computational model of pedestrian road safety: The long way round is the
           safe way home
    • Abstract: Publication date: Available online 28 June 2018Source: Accident Analysis & PreventionAuthor(s): Charlotte Hannah, Irena Spasić, Padraig CorcoranAbstractWe propose a novel linear model of pedestrian safety in urban areas with respect to road traffic crashes that considers a single independent variable of pedestrian path safety. This variable is estimated for a given urban area by sampling pedestrian paths from the population of such paths in that area and in turn estimating the mean safety of these paths. We argue that this independent variable directly models the factors contributing to pedestrian safety. This contrasts previous approaches, which, by considering multiple independent variables describing the environment, traffic and pedestrians themselves, indirectly model these factors. Using data about 15 UK cities, we demonstrate that the proposed model accurately estimates numbers of pedestrian casualties.
  • 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 GogolínAbstractRoundabouts 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 ShahAbstractPedestrians 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.
  • The measurement equivalence of a safety climate measure across five
    • Abstract: Publication date: Available online 21 May 2018Source: Accident Analysis & PreventionAuthor(s): Xiaohong Xu, Stephanie C. Payne, Mindy E. BergmanAbstractThis study examines the appropriateness of comparing safety climate survey responses across multiple faultlines—hypothetical dividing lines that split a group into subgroups based on one or more attributes. Using survey data from 8790 employees of a multinational chemical processing and manufacturing company from 76 work sites nested within 19 different countries, we examined the multilevel measurement equivalence of a safety climate measure across cultural dimensions, survey languages, organizational hierarchy, employment arrangements, and work environments. As simulation studies support the faultline at the individual-level requires measurement equivalence tests that are different from the faultline at the country-level, we used multi-group multilevel confirmatory factor analyses for the Level-3 faultline, and multilevel factor mixture models for known classes for the Level-1 faultlines. The results demonstrated that faultlines can prevent safety climate measurement equivalence, which prohibits the aggregation of individual-level scores to higher levels and making comparisons across faultlines. This first study on multilevel safety climate measurement equivalence serves as both a warning to safety climate researchers and practitioners regarding the importance of faultlines and reminds us to consider the level of the faultlines when testing measurement equivalence with multilevel data.
  • 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
  • Effects of alertness management training on sleepiness among long-haul
           truck drivers: A randomized controlled trial
    • Abstract: Publication date: Available online 18 May 2018Source: Accident Analysis & PreventionAuthor(s): M. Pylkkönen, A. Tolvanen, C. Hublin, J. Kaartinen, K. Karhula, S. Puttonen, M. Sihvola, M. SallinenAbstractEducation is a frequently recommended remedy for driver sleepiness in occupational settings, although not many studies have examined its usefulness. To date, there are no previous on-road randomized controlled trials investigating the benefits of training on sleepiness among employees working in road transport. To examine the effects of an educational intervention on long-haul truck drivers’ sleepiness at the wheel, amount of sleep between work shifts, and use of efficient sleepiness countermeasures (SCM) in association with night and non-night shift, a total of 53 truck drivers operating from southern Finland were allocated into an intervention and a control group using a stratified randomization method (allocation ratio for intervention and control groups 32:21, respectively). The intervention group received a 3.5-hour alertness management training followed by a two-month consultation period and motivational self-evaluation tasks two and 4–5 months after the training, while the control group had an opportunity to utilize their usual statutory occupational health care services. The outcomes were measured under drivers’ natural working and shift conditions over a period of two weeks before and after the intervention using unobtrusive data-collection methods including the Karolinska Sleepiness Scale measuring on-duty sleepiness, a combination of actigraphy and a sleep-log measuring sleep between duty hours, and self-report questionnaire items measuring the use of SCMs while on duty. The data analysis followed a per-protocol analysis. Results of the multilevel regression models showed no significant intervention-related improvements in driver sleepiness, prior sleep, or use of SCMs while working on night and early morning shifts compared to day and/or evening shifts. The current study failed to provide support for a feasible non-recurrent alertness-management training being effective remedy for driver sleepiness in occupational settings. These results cannot, however, be interpreted as evidence against alertness management training in general but propose that driver education is not a sufficient measure as such to alleviate driver sleepiness.
  • Prediction and perception of hazards in professional drivers: Does hazard
           perception skill differ between safe and less-safe fire-appliance
    • Abstract: Publication date: Available online 18 May 2018Source: Accident Analysis & PreventionAuthor(s): David Crundall, Victoria KrollAbstractCan hazard perception testing be useful for the emergency services' Previous research has found emergency response drivers’ (ERDs) to perform better than controls, however these studies used clips of normal driving. In contrast, the current study filmed footage from a fire-appliance on blue-light training runs through Nottinghamshire, and endeavoured to discriminate between different groups of EDRs based on experience and collision risk. Thirty clips were selected to create two variants of the hazard perception test: a traditional push-button test requiring speeded-responses to hazards, and a prediction test that occludes at hazard onset and provides four possible outcomes for participants to choose between. Three groups of fire-appliance drivers (novices, low-risk experienced and high-risk experienced), and age-matched controls undertook both tests. The hazard perception test only discriminated between controls and all FA drivers, whereas the hazard prediction test was more sensitive, discriminating between high and low-risk experienced fire appliance drivers. Eye movement analyses suggest that the low-risk drivers were better at prioritising the hazardous precursors, leading to better predictive accuracy. These results pave the way for future assessment and training tools to supplement emergency response driver training, while supporting the growing literature that identifies hazard prediction as a more robust measure of driver safety than traditional hazard perception tests.
  • 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 BanksAbstractTechnology-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 VedovaAbstractSelf-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 DawsonAbstractIn 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'BrienAbstractIntroductionShifting 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 DongenAbstractTimely 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 VillariniAbstractNumerous 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 projectAbstractTo 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 LinAbstractThe 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. PratoAbstractAlthough 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 DongenAbstractFatigue 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 DongenAbstractIn 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. RitchieAbstractTrucks 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.
  • 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. WegmanAbstractThis 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 AntoniouAbstractGiven 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 JafarabadiAbstractThe 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. HanowskiAbstractSimilar 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 StipancicAbstractThe 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 PapadimitriouAbstractConsiderable 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.
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Tel: +00 44 (0)131 4513762
Fax: +00 44 (0)131 4513327
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