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Publisher: Elsevier   (Total: 3162 journals)

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Showing 1 - 200 of 3162 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: 30, 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: 404, 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: 241, 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  
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 Cement Based Materials     Full-text available via subscription   (Followers: 3, SJR: 0.732, CiteScore: 3)
Advanced Drug Delivery Reviews     Hybrid Journal   (Followers: 140, 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: 10, 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: 8)
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: 15, 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: 21)
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: 6)
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: 392, 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: 17)
Advances in Veterinary Science and Comparative Medicine     Full-text available via subscription   (Followers: 13)
Advances in Virus Research     Full-text available via subscription   (Followers: 5, SJR: 2.262, CiteScore: 5)
Advances in Water Resources     Hybrid Journal   (Followers: 46, SJR: 1.551, CiteScore: 3)
Aeolian Research     Hybrid Journal   (Followers: 6, SJR: 1.117, CiteScore: 3)
Aerospace Science and Technology     Hybrid Journal   (Followers: 335, 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: 442, 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: 44, 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: 32, SJR: 7.45, CiteScore: 8)
American J. of Infection Control     Hybrid Journal   (Followers: 26, 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: 43)
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: 201, SJR: 2.7, CiteScore: 4)
American J. of Ophthalmology     Hybrid Journal   (Followers: 61, 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: 169, 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)

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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  [3162 journals]
  • 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 Jung Inaugurated 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 Wang The 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 King Road 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 Stevenson Recent 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 Ho PurposeAnalyze 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. Rea Reducing 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 Job There 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 Lentz Secondary 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.
       
  • Factors influencing unsafe behaviors: A supervised learning approach
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Yang Miang Goh, Chalani U. Ubeynarayana, Karen Le Xin Wong, Brian H.W. Guo Despite its potential, the use of machine learning in safety studies had been limited. Considering machine learning’s advantage in predictive accuracy, this study used a supervised learning approach to evaluate the relative importance of different cognitive factors within the Theory of Reasoned Action (TRA) in influencing safety behavior. Data were collected from 80 workers in a tunnel construction project using a TRA-based questionnaire. At the same time, behavior-based safety (BBS) observation data, % unsafe behavior, was collected. Subsequently, with the TRA cognitive factors as the input attributes, six widely-used machine learning algorithms and logistic regression were used to develop models to predict % unsafe behavior. The receiver operating characteristic (ROC) curves show that decision tree provides the best prediction. It was found that intention and social norms have the biggest influence on whether a worker was observed to work safely or not. Thus, managers aiming to improve safety behaviors need to pay specific attention to social norms in the worksite. The study also showed that a TRA survey can be used to extend a BBS to facilitate more effective interventions. Lastly, the study showed that machine learning algorithms provide an alternative approach for analyzing the relationship between the cognitive factors and behavioral data.
       
  • Predicting crash frequency for multi-vehicle collision types using
           multivariate Poisson-lognormal spatial model: A comparative analysis
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Mehdi Hosseinpour, Sina Sahebi, Zamira Hasanah Zamzuri, Ahmad Shukri Yahaya, Noriszura Ismail According to crash configuration and pre-crash conditions, traffic crashes are classified into different collision types. Based on the literature, multi-vehicle crashes, such as head-on, rear-end, and angle crashes, are more frequent than single-vehicle crashes, and most often result in serious consequences. From a methodological point of view, the majority of prior studies focused on multivehicle collisions have employed univariate count models to estimate crash counts separately by collision type. However, univariate models fail to account for correlations which may exist between different collision types. Among others, multivariate Poisson lognormal (MVPLN) model with spatial correlation is a promising multivariate specification because it not only allows for unobserved heterogeneity (extra-Poisson variation) and dependencies between collision types, but also spatial correlation between adjacent sites. However, the MVPLN spatial model has rarely been applied in previous research for simultaneously modelling crash counts by collision type. Therefore, this study aims at utilizing a MVPLN spatial model to estimate crash counts for four different multi-vehicle collision types, including head-on, rear-end, angle, and sideswipe collisions. To investigate the performance of the MVPLN spatial model, a two-stage model and a univariate Poisson lognormal model (UNPLN) spatial model were also developed in this study. Detailed information on roadway characteristics, traffic volume, and crash history were collected on 407 homogeneous segments from Malaysian federal roads. The results indicate that the MVPLN spatial model outperforms the other comparing models in terms of goodness-of-fit measures. The results also show that the inclusion of spatial heterogeneity in the multivariate model significantly improves the model fit, as indicated by the Deviance Information Criterion (DIC). The correlation between crash types is high and positive, implying that the occurrence of a specific collision type is highly associated with the occurrence of other crash types on the same road segment. These results support the utilization of the MVPLN spatial model when predicting crash counts by collision manner. In terms of contributing factors, the results show that distinct crash types are attributed to different subsets of explanatory variables.
       
  • Young drivers’ perception of adult and child pedestrians in potential
           street-crossing situations
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Līva Ābele, Sonja Haustein, Mette Møller Despite overall improvements in road traffic safety, pedestrian accidents continue to be a serious public health problem. Due to lack of experience, limited cognitive and motoric skills, and smaller size, children have a higher injury risk as pedestrians than adults. To what extent drivers adjust their driving behaviour to children’s higher vulnerability is largely unknown. To determine whether young male drivers’ behaviour and scanning pattern differs when approaching a child and an adult pedestrian in a potential street-crossing situation, sixty-five young (18–24) male drivers’ speed, lateral position and eye movements were recorded in a driving simulator. Results showed that fewer drivers responded by slowing down and that drivers had a higher driving speed when approaching a child pedestrian, although the time of the first fixation on both types of pedestrians was the same. However, drivers drove farther away from a child than an adult pedestrian. Additionally, fewer drivers who did not slow down fixated on the speedometer while approaching the child pedestrian. The results show that young drivers behave differently when approaching a child and an adult pedestrian, though not in a way that appropriately accounts for the limitations of a child pedestrian. A better understanding of how drivers respond to different types of pedestrians and why could contribute to the development of pedestrian detection and emergency braking systems.
       
  • Driving behaviour while self-regulating mobile phone interactions: A
           human-machine system approach
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Oscar Oviedo-Trespalacios, Md Mazharul Haque, Mark King, Sebastien Demmel Mobile phone distracted driving is a recurrent issue in road safety worldwide. Recent research on driving behaviour of distracted drivers suggests that in certain circumstances drivers seem to assume safer behaviours while using a mobile phone. Despite a high volume of research on this topic, self-regulation by mobile phone distracted drivers is not well understood as many driving simulator experiments are designed to impose an equal level of distraction to participants being tested for their driving performance. The aim of this research was to investigate the relationship between self-regulatory secondary task performance and driving. By a driving simulator experiment in which participants were allowed to perform their secondary tasks whenever they feel appropriate, the driving performance of 35 drivers aged 18–29 years was observed under three phone conditions including non-distraction (no phone use), hands-free interactions and visual-manual interactions in the CARRS-Q advanced driving simulator. Drivers’ longitudinal and lateral vehicle control observed across various road traffic conditions were then modelled by Generalized Estimation Equations (GEE) with exchangeable correlation structure accounting for heterogeneity resulting from multiple observations from the same driver. Results show that the extent of engagement in the secondary task influence both longitudinal and lateral control of vehicles. Drivers who engaged in a large number of hands-free interactions are found to select lower driving speed. In contrast, longer visual-manual interactions are found to result in higher driving speed among drivers self-regulating their secondary task. Among the road traffic conditions, drivers distracted by their self-regulated secondary tasks are found to select lower speeds along the s-curve compared to straight and motorway segments. In summary, the applied human-machine system approach suggests that road traffic demands play a vital role in both secondary task management and driving performance.
       
  • What externally presented information do VRUs require when interacting
           with fully Automated Road Transport Systems in shared space'
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Natasha Merat, Tyron Louw, Ruth Madigan, Marc Wilbrink, Anna Schieben As the desire for deploying automated (“driverless”) vehicles increases, there is a need to understand how they might communicate with other road users in a mixed traffic, urban, setting. In the absence of an active and responsible human controller in the driving seat, who might currently communicate with other road users in uncertain/conflicting situations, in the future, understanding a driverless car’s behaviour and intentions will need to be relayed via easily comprehensible, intuitive and universally intelligible means, perhaps presented externally via new vehicle interfaces. This paper reports on the results of a questionnaire-based study, delivered to 664 participants, recruited during live demonstrations of an Automated Road Transport Systems (ARTS; SAE Level 4), in three European cities. The questionnaire sought the views of pedestrians and cyclists, focussing on whether respondents felt safe interacting with ARTS in shared space, and also what externally presented travel behaviour information from the ARTS was important to them. Results showed that most pedestrians felt safer when the ARTS were travelling in designated lanes, rather than in shared space, and the majority believed they had priority over the ARTS, in the absence of such infrastructure. Regardless of lane demarcations, all respondents highlighted the importance of receiving some communication information about the behaviour of the ARTS, with acknowledgement of their detection by the vehicle being the most important message. There were no clear patterns across the respondents, regarding preference of modality for these external messages, with cultural and infrastructural differences thought to govern responses. Generally, however, conventional signals (lights and beeps) were preferred to text-based messages and spoken words. The results suggest that until these driverless vehicles are able to provide universally comprehensible externally presented information or messages during interaction with other road users, they are likely to contribute to confusing and conflicting interactions between these actors, especially in a shared space setting, which may, therefore, reduce efficient traffic flow.
       
  • Examining vehicle operating speeds on rural two-lane curves using
           naturalistic driving data
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Bo Wang, Shauna Hallmark, Peter Savolainen, Jing Dong Horizontal curves have been shown to exhibit crash rates significantly higher than comparable tangent segments. Extensive research has investigated the causes of crashes on horizontal curves, particularly the curve navigation process and driver speed selection. Research in this area has generally been limited by the nature of the data, which is often inhibited by practical constraints as to the number of locations and drivers that can be observed. This study overcomes these hurdles through the use of naturalistic driving data, providing insights on how drivers navigate and react to curves on rural two-lane highways. Nearly 10,000 vehicle traces were collected from 202 drivers on 219 horizontal curves as a part of this study. All driving traces were collected on rural two-lane highways with prevailing posted speed limits of 45 mph or 55 mph, as well as a diverse range of curve advisory speeds. Regression models are estimated via generalized estimating equations to discern those factors affecting mean speeds on curves. A log-linear relationship was found between curve radius and mean vehicle speed, with speeds relatively stable on radii of 900–1000 ft. or more, decreasing more rapidly as radii decreased below this range. Drivers were found to reduce speeds when curve advisories were present, but the magnitude of these reductions was much less than suggested by the advisory signs. Speeds were significantly lower when a W1-6 curve arrow sign was present adjusting for the curve radius. There were also some differences in speeds based on driver age and gender. Ultimately, this paper provides insights into driver curve navigation and demonstrates the potential of high-fidelity naturalistic driving data to assess speed management and geometric design on horizontal curves.
       
  • Assessing rear-end crash potential in urban locations based on
           vehicle-by-vehicle interactions, geometric characteristics and operational
           conditions
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Loukas Dimitriou, Katerina Stylianou, Mohamed A. Abdel-Aty Rear-end crashes are one of the most frequently occurring crash types, especially in urban networks. An understanding of the contributing factors and their significant association with rear-end crashes is of practical importance and will help in the development of effective countermeasures. The objective of this study is to assess rear-end crash potential at a microscopic level in an urban environment, by investigating vehicle-by-vehicle interactions. To do so, several traffic parameters at the individual vehicle level have been taken into consideration, for capturing car-following characteristics and vehicle interactions, and to investigate their effect on potential rear-end crashes. In this study rear-end crash potential was estimated based on stopping distance between two consecutive vehicles, and four rear-end crash potential cases were developed. The results indicated that 66.4% of the observations were estimated as rear-end crash potentials. It was also shown that rear-end crash potential was presented when traffic flow and speed standard deviation were higher. Also, locational characteristics such as lane of travel and location in the network were found to affect drivers’ car following decisions and additionally, it was shown that speeds were lower and headways higher when Heavy Goods Vehicles lead. Finally, a model-based behavioral analysis based on Multinomial Logit regression was conducted to systematically identify the statistically significant variables in explaining rear-end risk potential. The modeling results highlighted the significance of the explanatory variables associated with rear-end crash potential, however it was shown that their effect varied among different model configurations. The outcome of the results can be of significant value for several purposes, such as real-time monitoring of risk potential, allocating enforcement units in urban networks and designing targeted proactive safety policies.
       
  • Consistency between subjectively and objectively measured hazard
           perception skills among young male drivers
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Līva Ābele, Sonja Haustein, Mette Møller, Laila M. Martinussen Young male drivers have lower hazard perception skills (HPS) than older and more experienced drivers and a tendency to overestimate their skills in hazardous situations. Both factors contribute to an over-representation in traffic accidents. Based on a sample of 63 drivers aged 18–24, this study compares the consistency of HPS measured by objective and subjective measures and the link between these measures is the key contribution of the study. Both visible and hidden hazards are included. Objective measures of HPS include responsiveness and eye movements while driving in a driving simulator. Subjective measures of HPS include self-reports derived based on the Hazard Perception Questionnaire (HPQ), Driving Skill Questionnaire (DSQ), and Brief Sensation Seeking Scale (BSSS). Results show that drivers who respond to the hazards on time, as compared to drivers who do not respond, have higher scores on subjective measures of HPS and higher driving skills in the visible but not in the hidden condition. Eye movement analysis confirms the difference and shows that response in time to hazards indicate higher HPS and young drivers are poor at detecting hidden hazards. Drivers with a response in time locate the hazard faster, have more fixations, but dwell less on the hazard. At the same time, those who do not respond have a later first fixation and fewer but longer fixations on the hazard. High sensation seeking drivers respond to visible hazards on time, suggesting that sensation seeking does not affect HPS negatively when the hazard is visible. To enhance the HPS among young drivers, the results of this study suggest that specific hazard perception training is relevant, especially for hazards that require more advanced HPS.
       
  • Dash Cam videos on YouTube™ offer insights into factors related to
           moose-vehicle collisions
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Roy V. Rea, Chris J. Johnson, Daniel A. Aitken, Kenneth N. Child, Gayle Hesse To gain a better understanding of the dynamics of moose-vehicle collisions, we analyzed 96 videos of moose-vehicle interactions recorded by vehicle dash-mounted cameras (Dash Cams) that had been posted to the video-sharing website YouTube™. Our objective was to determine the effects of road conditions, season and weather, moose behavior, and driver response to actual collisions compared to near misses when the collision was avoided. We identified 11 variables that were consistently observable in each video and that we hypothesized would help to explain a collision or near miss. The most parsimonious logistic regression model contained variables for number of moose, sight time, vehicle slows, and vehicle swerves (AICcw = 0.529). This model had good predictive accuracy (AUC = 0.860, SE = 0.041). The only statistically significant variable from this model that explained the difference between moose-vehicle collisions and near misses was ‘Vehicle slows’. Our results provide no evidence that road surface conditions (dry, wet, ice or snow), roadside habitat type (forested or cleared), the extent to which roadside vegetation was cleared, natural light conditions (overcast, clear, twilight, dark), season (winter, spring and summer, fall), the presence of oncoming traffic, or the direction from which the moose entered the roadway had any influence on whether a motorist collided with a moose. Dash Cam videos posted to YouTube™ provide a unique source of data for road safety planners trying to understand what happens in the moments just before a moose-vehicle collision and how those factors may differ from moose-vehicle encounters that do not result in a collision.
       
  • Police documentation of drug use in injured drivers: Implications for
           monitoring and preventing drug-impaired driving
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Jeffrey R. Brubacher, Herbert Chan, Shannon Erdelyi, Mark Asbridge, Robert E. Mann, Roy A. Purssell, Robert Solomon IntroductionMost countries have laws against driving while impaired by drugs. However, in many countries, including Canada and the United States, police must have individualized suspicion that the driver has recently used an impairing substance before they can gather the evidence required for laying a criminal charge. This report studies police documentation of drug involvement among drivers who had a motor-vehicle crash after using an impairing substance.MethodsWe obtained blood samples and police reports on injured drivers treated in participating British Columbia trauma centres following a crash. Blood was analyzed for alcohol, cannabinoids, other recreational drugs, and impairing medications. Corresponding police reports were examined to determine whether police recorded that the driver’s ability was impaired by alcohol, drug or medication, or that one of these substances was a possible contributory factor in the crash.ResultsWe obtained blood samples and corresponding police reports on 1816 injured drivers. Mean driver age was 44 years, 63.2% were male, and 25.8% were admitted to hospital. Alcohol was detected in 272 drivers (15.0%), THC (tetrahydrocannabinol - the principal psychoactive ingredient in cannabis) in 136 (7.5%), other recreational drugs in 166 (9.1%), and potentially impairing medications in 363 (20.0%). Police reported that the driver’s ability was impaired by alcohol or that alcohol was a possible contributory factor in 64.1% of the crashes involving alcohol-positive drivers. Drug impairment or drugs as a possible contributory factor was reported in 5.9% of the crashes involving THC-positive drivers, and in 16.9% of the crashes involving drivers who tested positive for other recreational drugs. Medication impairment was reported in only 2.2% of the crashes involving medication-positive drivers.ConclusionPolice seldom document drug involvement in drivers who were in a crash after using cannabis, other recreational drugs or potentially impairing medications. This finding raises serious concerns about the ability of the police to effectively enforce current drug-impaired driving laws and public health officials’ continued reliance on police crash reports to monitor the prevalence of drug-impaired driving.
       
  • Voices carry: Effects of verbal and physical aggression on injuries and
           accident reporting
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Lixin Jiang, Tahira M. Probst, Wendi Benson, Jesse Byrd Recent years have witnessed a staggeringly high number of workplace aggressive behaviors as well as employee accidents and injuries. Exposure to workplace aggression is associated with a host of negative psychological, emotional, and physiological outcomes, yet research relating workplace aggression to employee safety outcomes is lacking. This study aims to examine the association between exposure to workplace physical and verbal aggression with workplace injuries and underreporting of accidents and near misses. Furthermore, deriving from social exchange theory, we attempt to reveal an underlying mechanism in the association between workplace aggression and underreporting of accidents and near misses. Finally, borrowing from aggression research on intimate relationships, we compare the relative importance of exposure to physical and verbal aggression on workplace injuries and underreporting. Using survey data from 364 public transportation personnel, we found that both verbal and physical aggression significantly predict workplace injuries as well as underreporting. Moreover, mediation analyses found that the relationship between verbal and physical aggression and underreporting was largely explained by an increase in negative reporting attitudes (rather than decreases in safety knowledge or motivation). Compared to exposure to physical aggression, exposure to verbal aggression best predicted employee underreporting of accidents and near misses. However, physical aggression was a better predictor of injuries than verbal aggression. Given these findings, organizational leaders should strive to foster a safe working environment by minimizing interpersonal mistreatment and increasing employee attitudes for reporting accidents.
       
  • Risk perception and the warning strategy based on microscopic driving
           state
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Xiaomei Zhao, Qian Li, Dongfan Xie, Jun Bi, Rongqin Lu, Chao Li The paper aimed to explore the relationship between risks and individuals’ driving states and then design an efficient method to help drivers avoid high risks. The relationship between risks and individuals’ driving states was deeply studied first. Microscopic driving states were categorized into different clusters, and it was found that the risks are distinct in different clusters and a specific driver might experience different risks in car-following process. Then, according to these findings, a risk warning strategy was designed to help drivers avoid high risks. The risk warning is active when the risk is higher than its threshold. The Helly models were used to mimic the drivers’ reaction to study the influence of the warning strategy. Simulation results showed that with the consideration of the risk warning, the spacing obviously increases, and the oscillations of velocity and acceleration are significantly shrunk, and risks in the driving process dampen down. Because drivers can perceive high risks during the driving process, and then appropriately change their car-following decisions to avoid high risks. These findings are helpful to improve driving behaviors and promote traffic safety.
       
  • Evaluating variability in foot to pedal movements using functional
           principal components analysis
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Yuqing Wu, Linda Ng Boyle, Daniel V. McGehee There are reasons why the driver’s foot may not be applied to the correct pedal while driving and this can lead to unintended consequences. In this study, we seek to capture common and unique patterns of variations in drivers’ foot movements using functional principal components analysis (FPCA). This analysis technique was used to analyze three categories of pedal response types (direct hits, corrected trajectories, and pedal errors) based on the various foot to pedal trajectories. Data from a driving simulator study with video data of foot movements for 45 drivers was used for analyses. Most foot movements show common patterns associated with direct hits and corrected trajectories with some level of variation. However, those foot movements associated with unique patterns might be early indicators of pedal errors. The findings of this study can be used with collision mitigation systems to provide early detection of foot trajectories that are more likely to result in a pedal error.
       
  • Visualization and analysis of mapping knowledge domain of road safety
           studies
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Xin Zou, Wen Long Yue, Hai Le Vu Mapping knowledge domain (MKD) is an important application of visualization technology in Bibliometrics, which has been extensively applied in psychology, medicine, and information science. In this paper we conduct a systematic analysis of the development trend on road safety studies based on the Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) articles published between 2000 and 2018 using the MKD software tools VOSviewer and Sci2 Tool. Based on our analysis, we first present the annual numbers of articles, origin countries, main research organizations and groups as well as the source journals on road safety studies. We then report the collaborations among the main research organizations and groups using co-authorship analysis. Furthermore, we adopt the document co-citation analysis, keywords co-occurrence analysis, and burst detection analysis to visually explore the knowledge bases, topic distribution, research fronts and research trends on road safety studies. The proposed approach based on the visualized analysis of MKD can be used to establish a reference information and research basis for the application and development of methods in the domain of road safety studies. In particular, our results show that the knowledge bases (classical documents) of road safety studies in the last two decades have focused on five major areas of “Crash Frequency Data Analysis”, “Driver Behavior Questionnaire”, “Safety in Numbers for Walkers and Bicyclists”, “Road Traffic Injury and Prevention”, and “Driving Speed and Road Crashes”. Among the research topics, the five dominant clusters are “Causation and Injury Severity Analysis of Road Accidents”, “Epidemiologic Study and Prevention of Road Traffic Injury”, “Intelligent Transportation System and Active Safety”, “Young drivers’ driving behavior and psychology”, and “Older drivers’ psychological and physiological characteristics”. Finally, the burst keywords in research trends include Cycling, Intelligent Transportation Systems, and Distraction.
       
  • Correlations between mobile phone use and other risky behaviours while
           riding a motorcycle
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Long T. Truong, Hang T.T. Nguyen, Chris De Gruyter Motorcyclist safety is a major concern in many developing countries. Understanding motorcycle riders’ risky behaviours, particularly among the younger population, is essential to developing effective interventions. This paper explores the correlations between mobile phone use while riding and other risky riding behaviours as well as the relationships between perceived risks and risky riding behaviours, using an online survey of university students in Vietnam. Results show that calling while riding a motorcycle had the highest prevalence (74%) while reckless overtaking had the lowest prevalence (33.2%). Survey participants who indicated that they had the behaviours of reckless overtaking or riding on sidewalks were around twice as likely to call, text, or search for information while riding. In addition, those who admitted that they rode a motorcycle while under the influence of alcohol were nearly twice as likely to call or text while riding. The results also show that perceived crash risks reduced the likelihood of risky riding behaviours, including calling, texting, searching for information, speeding, running red lights, riding on the wrong side of a road, and riding on sidewalks. A more coordinated approach to enforcement is needed to help reduce the prevalence of multiple risk taking behaviours among motorcyclists.
       
  • Injury severity analysis of commercially-licensed drivers in
           single-vehicle crashes: Accounting for unobserved heterogeneity and age
           group differences
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Mohamed Osman, Sabyasachee Mishra, Rajesh Paleti This study analyzes the injury severity of commercially-licensed drivers involved in single-vehicle crashes. Considering the discrete ordinal nature of injury severity data, the ordered response modeling framework was adopted. The moderating effect of driver’s age on all other factors was examined by segmenting the parameters by driver’s age group. Additional effects of the different drivers’ age groups are taken into consideration through interaction terms. Unobserved heterogeneity of the different covariates was investigated using the Mixed Generalized Ordered Response Probit (MGORP) model. The empirical analysis was conducted using four years of the Highway Safety Information System (HSIS) data that included 6247 commercially-licensed drivers involved in single-vehicle crashes in the state of Minnesota. The MGORP model elasticity effects indicate that key factors that increase the likelihood of severe crashes for commercially-licensed drivers across all age groups include: lack of seatbelt usage, collision with a fixed object, speeding, vehicle age of 11 years or more, wind, night time, weekday, and female drivers. Also, the effects of several covariates were found to vary across different age groups.
       
  • Get ready for automated driving using Virtual Reality
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Daniele Sportillo, Alexis Paljic, Luciano Ojeda In conditionally automated vehicles, drivers can engage in secondary activities while traveling to their destination. However, drivers are required to appropriately respond, in a limited amount of time, to a take-over request when the system reaches its functional boundaries. Interacting with the car in the proper way from the first ride is crucial for car and road safety in general. For this reason, it is necessary to train drivers in a risk-free environment by providing them the best practice to use these complex systems. In this context, Virtual Reality (VR) systems represent a promising training and learning tool to properly familiarize drivers with the automated vehicle and allow them to interact with the novel equipment involved. In addition, Head-Mounted Display (HMD)-based VR (light VR) would allow for the easy deployment of such training systems in driving schools or car dealerships. In this study, the effectiveness of a light Virtual Reality training program for acquiring interaction skills in automated cars was investigated. The effectiveness of this training was compared to a user manual and a fixed-base simulator with respect to both objective and self-reported measures. Sixty subjects were randomly assigned to one of the systems in which they went through a training phase followed by a test drive in a high-end driving simulator. Results show that the training system affects the take-over performances. Moreover, self-reported measures indicate that the light VR training is preferred with respect to the other systems. Finally, another important outcome of this research is the evidence that VR plays a strategic role in the definition of the set of metrics for profiling proper driver interaction with the automated vehicle.
       
  • Vehicle ownership and other predictors of teenagers risky driving
           behavior: Evidence from a naturalistic driving study
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Pnina Gershon, Johnathon Ehsani, Chunming Zhu, Fearghal O’Brien, Sheila Klauer, Tom Dingus, Bruce Simons-Morton ObjectiveRisky driving behavior may contribute to the high crash risk among teenage drivers. The current naturalistic driving study assessed predictors for teenagers’ kinematic risky driving (KRD) behavior and the interdependencies between them.MethodThe private vehicles of 81 novice teenage drivers were equipped with data acquisition system that recorded driving kinematics, miles driven, and video recordings of the driver, passengers and the driving environment. Psychosocial measures were collected using questionnaires administered at licensure. Poisson regression analyses and model selection were used to assess factors associated with teens’ risky driving behavior and the interactions between them.ResultsDriving own vs shared vehicle, driving during the day vs at night, and driving alone vs with passengers were significantly associated with higher KRD rates (Incidence rate ratios (IRRs) of 1.60, 1.41, and 1.28, respectively). Teenagers reporting higher vs lower levels of parental trust had significantly lower KRD rates (IRR = 0.58). KRD rates were 88% higher among teenagers driving with a passenger in their own vehicle compared to teenagers driving with a passenger in a shared vehicle. Similarly, KRD rates during the day were 74% higher among teenagers driving their own vehicle compared to those driving a shared vehicle.ConclusionsNovice teenagers’ risky driving behavior varied according to driver attributes and contextual aspects of the driving environment. As such, examining teenagers’ risky driving behavior should take into account multiple contributing factors and their interactions. The variability in risky driving according to the driving context can inform the development of targeted interventions to reduce the crash risk of novice teenage drivers.
       
  • Does gender really matter' A structural equation model to explain
           risky and positive cycling behaviors
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Sergio A. Useche, Luis Montoro, Francisco Alonso, Francisco M. Tortosa IntroductionWhile the use of bicycles as mean of transport is growing worldwide, the increasing rates of traffic crashes involving cyclists have turned into a relevant scientific, public health, and road safety concern. According to several studies, and despite the fact that some countries are taking part in preventive actions, the data indicate that the problem of cycling injuries implies high costs for the community welfare, for the economy, and for healthcare systems, thus proving a clear need for solutions. In this regard, and considering the available empirical evidence, risky and positive riding behaviors have gained significant weight in terms of explaining, intervening in, and preventing traffic crashes of cyclists, and some evidence suggests that gender may influence the road behavior of users.ObjectiveThe objective of this study was to examine the effect of gender on cyclists' risky and positive riding behavior, considering a set of demographic, psychosocial and bike-use-related variables as potential predictors.MethodFor this cross-sectional study, data from 1064 cyclists (61.2% males and 38.8% females, aged between 17 and 80) from 20 countries, responding an electronic survey, were analyzed through a multi-group structural equation modeling approach. Results: Although hourly intensity, psychological distress and level of knowledge of traffic rules similarly predict the risky road behaviors of both genders, age and risk perception are significant behavioral predictors only in the case of male cyclists. On the other hand, positive behaviors of men are predicted by cycling intensity, knowledge of traffic rules and risk perception, while in the case of women psychological distress predicts -to a significant extent- positive behaviors. Age had no significant effect on the explanation of positive behaviors.ConclusionThe findings of this study support the influence of gender in the statistical explanation of risky and protective behaviors, and they also reveal differentiating variables predicting the riding behavior of male and female cyclists.
       
  • The impact of texting on driver behaviour at rail level crossings
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Kristie L. Young, Michael G. Lenné, Paul M. Salmon, Neville A. Stanton A driver text messaging in the vicinity of a rail level crossing represents the merging of a high-risk, high-workload driving environment with a highly distracting secondary task. In this simulator study, we examined how texting impacts driver behaviour on approach to actively controlled urban rail level crossings. Twenty-eight participants drove a series of simulated urban routes containing rail level crossings, while sending text messages and while driving without performing a secondary task. At half of the crossings, drivers were required to respond to the crossing warnings as a train approached. Results revealed that texting on approach to rail level crossings had a detrimental impact on a range of driver behaviour measures. Specifically, texting more than doubled the amount of time spent with eyes off the forward roadway, resulting in drivers spending more than half of their approach time to rail level crossings looking away from the road. This lack of visual attention to the roadway was associated with a range of decrements in driving that may be indicative of a loss of situation awareness, including increased brake reaction time to the crossing warnings and a reduction in lateral position control. The findings have safety implications, not only for urban level crossings, but also for passive level crossings where no warnings are present to re-orient the distracted driver’s attention toward an approaching train.
       
  • An evidence based method to calculate pedestrian crossing speeds in
           vehicle collisions (PCSC)
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): C. Bastien, R. Wellings, B. Burnett Pedestrian accident reconstruction is necessary to establish cause of death, i.e. establishing vehicle collision speed as well as circumstances leading to the pedestrian being impacted and determining culpability of those involved for subsequent court enquiry. Understanding the complexity of the pedestrian attitude during an accident investigation is necessary to ascertain the causes leading to the tragedy. A generic new method, named Pedestrian Crossing Speed Calculator (PCSC), based on vector algebra, is proposed to compute the pedestrian crossing speed at the moment of impact. PCSC uses vehicle damage and pedestrian anthropometric dimensions to establish a combination of head projection angles against the windscreen; this angle is then compared against the combined velocities angle created from the vehicle and the pedestrian crossing speed at the time of impact. This method has been verified using one accident fatality case in which the exact vehicle and pedestrian crossing speeds were known from Police forensic video analysis. PCSC was then applied on two other accident scenarios and correctly corroborated with the witness statements regarding the pedestrians crossing behaviours. The implications of PCSC could be significant once fully validated against further future accident data, as this method is reversible, allowing the computation of vehicle impact velocity from pedestrian crossing speed as well as verifying witness accounts.
       
  • A qualitative exploration of driving stress and driving discourtesy
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): B. Scott-Parker, C.M. Jones, K. Rune, J. Tucker BackgroundDriving courtesy, and conversely driving discourtesy, recently has been of great interest in the public domain. In addition, there has been increasing recognition of the negative impact of stress upon the individual’s health and wellbeing, with a plethora of interventions aimed at minimising stress more generally. The research literature regarding driving dis/courtesy, in comparison, is scant, with a handful of studies examining the dis/courteous driving behaviour of road users, and the relationship between driving discourtesy and driving stress.AimTo examine courteous and discourteous driving experiences, and to explore the impact of stress associated with such driving experiences.MethodThirty-eight drivers (20 females) from the Sunshine Coast region volunteered to participate in one of four 1–1.5 h focus groups. Content analysis used the verbatim utterances captured via an Mp3 device.ResultsThree themes pertaining to stressful and discourteous interactions were identified. Theme one pertained to the driving context: road infrastructure (eg, roundabouts, roadwork), vehicles (eg, features), location (eg, country vs city, unfamiliar areas), and temporal aspects (eg, holidays). Theme two pertained to other road users: their behaviour (eg, tailgating, merging), and unknown factors (eg, illicit and licit drug use). Theme three pertained to the self as road user: their own behaviours (eg, deliberate intimidation), and their emotions (eg, angry reaction to other drivers, being in control).Discussion and conclusionsDriving dis/courtesy and driving stress is a complex phenomenon, suggesting complex intervention efforts are required. Driving discourtesy was reported as being highly stressful, therefore intervention efforts which encourage driving courtesy and which foster emotional capacity to cope with stressful circumstances appear warranted.
       
  • Are estimates of crash modification factors mis-specified'
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Robert B. Noland, Yemi Adediji Transportation planners and traffic engineers are using crash modification factors to evaluate how changes in road geometry and design features can reduce crashes. Crash modification factors are typically estimated based on segmenting links on a highway and associating with geometric features. This allows statistical methods to be applied to the data. Concurrently there is a stream of research that relies on spatial units of analysis to examine crashes; these typically use broad features of the road network combined with socio-economic and demographic factors that are associated with crashes. In this paper, we examine whether omission of these spatial factors in a link-based model results in mis-specified models, in particular, omitted variable bias. Our results suggest that there is no change in coefficient signs, but that there is a reduction in the magnitude of estimates, suggesting that omitted variable bias exists. The sign of spatial variables differ substantially when combined with a link-based model. We also find substantial variability in coefficient estimates, and discuss the implications of these results for the use of crash modification factors in cost-benefit analysis of road safety projects.
       
  • Calibration of the inertial consistency index to assess road safety on
           horizontal curves of two-lane rural roads
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): David Llopis-Castelló, Francisco Javier Camacho-Torregrosa, Alfredo García One of every four road fatalities occurs on horizontal curves of two-lane rural roads. To this regard, many studies have been undertaken to analyze the crash risk on this road element. Most of them were based on the concept of geometric design consistency, which can be defined as how drivers’ expectancies and road behavior relate. However, none of these studies included a variable which represents and estimates drivers’ expectancies.This research presents a new local consistency model based on the Inertial Consistency Index (ICI). This consistency parameter is defined as the difference between the inertial operating speed, which represents drivers’ expectations, and the operating speed, which represents road behavior. The inertial operating speed was defined as the weighted average operating speed of the preceding road section. In this way, different lengths, periods of time, and weighting distributions were studied to identify how the inertial operating speed should be calculated.As a result, drivers’ expectancies should be estimated considering 15 s along the segment and a linear weighting distribution. This was consistent with drivers’ expectancies acquirement process, which is closely related to Short-Term Memory.A Safety Performance Function was proposed to predict the number of crashes on a horizontal curve and consistency thresholds were defined based on the ICI. To this regard, the crash rate increased as the ICI increased.Finally, the proposed consistency model was compared with previous models. As a conclusion, the new Inertial Consistency Index allowed a more accurate estimation of the number of crashes and a better assessment of the consistency level on horizontal curves.Therefore, highway engineers have a new tool to identify where road crashes are more likely to occur during the design stage of both new two-lane rural roads and improvements of existing highways.
       
  • Using perceptual cues for brake response to a lead vehicle: Comparing
           threshold and accumulator models of visual looming
    • Abstract: Publication date: September 2018Source: Accident Analysis & Prevention, Volume 118Author(s): Qingwan Xue, Gustav Markkula, Xuedong Yan, Natasha Merat Previous studies have shown the effect of a lead vehicle’s speed, deceleration rate and headway distance on drivers’ brake response times. However, how drivers perceive this information and use it to determine when to apply braking is still not quite clear. To better understand the underlying mechanisms, a driving simulator experiment was performed where each participant experienced nine deceleration scenarios. Previously reported effects of the lead vehicle’s speed, deceleration rate and headway distance on brake response time were firstly verified in this paper, using a multilevel model. Then, as an alternative to measures of speed, deceleration rate and distance, two visual looming-based metrics (angular expansion rate θ˙ of the lead vehicle on the driver’s retina, and inverse tau τ-1, the ratio between θ˙ and the optical size θ), considered to be more in line with typical human psycho-perceptual responses, were adopted to quantify situation urgency. These metrics were used in two previously proposed mechanistic models predicting brake onset: either when looming surpasses a threshold, or when the accumulated evidence (looming and other cues) reaches a threshold. Results showed that the looming threshold model did not capture the distribution of brake response time. However, regardless of looming metric, the accumulator models fitted the distribution of brake response times better than the pure threshold models. Accumulator models, including brake lights, provided a better model fit than looming-only versions. For all versions of the mechanistic models, models using τ-1 as the measure of looming fitted better than those using θ˙, indicating that the visual cues drivers used during rear-end collision avoidance may be more close to τ-1.
       
  • A novel method for imminent crash prediction and prevention
    • Abstract: Publication date: Available online 12 July 2018Source: Accident Analysis & PreventionAuthor(s): Zhi Chen, Xiao Qin A crash prediction and prevention method was proposed to detect imminent crash risk and help recommend traffic control strategies to prevent crashes. The method consists of two modules, the crash prediction module and the crash prevention module. The crash prediction module detects crash-prone conditions when the predicted crash probability exceeds a specified threshold. Then the crash prevention module would simulate the safety effect of traffic control alternatives and recommend the optimal one. The proposed method was demonstrated in a case study with variable speed limit (VSL). Results showed that the proposed crash prediction and prevention method could effectively detect crash-prone conditions and evaluate the safety and mobility impacts of various safety countermeasures.
       
  • Road safety data considerations
    • Abstract: Publication date: Available online 11 July 2018Source: Accident Analysis & PreventionAuthor(s): Loukas Dimitriou, Constantinos Antoniou
       
  • Use of real-world connected vehicle data in identifying high-risk
           locations based on a new surrogate safety measure
    • Abstract: Publication date: Available online 6 July 2018Source: Accident Analysis & PreventionAuthor(s): Kun Xie, Di Yang, Kaan Ozbay, Hong Yang Traditional methods for the identification of high-risk locations rely heavily on historical crash data. Rich information generated from connected vehicles could be used to obtain surrogate safety measures (SSMs) for risk identification. Conventional SSMs such as time to collision (TTC) neglect the potential risk of car-following scenarios in which the following vehicle’s speed is slightly less than or equal to the leading vehicle’s but the spacing between two vehicles is relatively small that a slight disturbance would yield collision risk. To address this limitation, this study proposes time to collision with disturbance (TTCD) for risk identification. By imposing a hypothetical disturbance, TTCD can capture rear-end conflict risks in various car following scenarios, even when the leading vehicle has a higher speed. Real-world connected vehicle pilot test data collected in Ann Arbor, Michigan is used in this study. A detailed procedure of cleaning and processing the connected vehicle data is presented. Results show that risk rate identified by TTCD can achieve a higher Pearson’s correlation coefficient with rear-end crash rate than other traditional SSMs. We show that high-risk locations identified by connected vehicle data from a relatively shorter time period are similar to the ones identified by using the historical crash data. The proposed method can substantially reduce the data collection time, compared with traditional safety analysis that generally requires more than three years to get sufficient crash data. The connected vehicle data has thus shown the potential to be used to develop proactive safety solutions and the risk factors can be eliminated in a timely manner.
       
  • 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 Corcoran We 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 Gogolín Roundabouts are one of the safest types of intersections. However, the needs to meet the requirements of operation, capacity, traffic organization and surrounding development lead to a variety of design solutions. One of such alternatives are turbo-roundabouts, which simplify drivers’ decision making, limit lane changing in the roundabout, and induce low driving speed thanks to raised lane dividers. However, in spite of their generally positive reception, the safety impact of turbo-roundabouts has not been sufficiently studied. Given the low number of existing turbo-roundabouts and the statistical rarity of accident occurrence, the prevalent previously conducted studies applied only simple before-after designs or relied on traffic conflicts in micro-simulations. Nevertheless, the presence of raised lane dividers is acknowledged as an important feature of well performing and safe turbo-roundabouts.Following the previous Polish studies, the primary objective of the present study was assessment of influence of presence of lane dividers on road safety and developing a reliable and valid surrogate safety measure based on field data, which will circumvent the limitations of accident data or micro-simulations. The secondary objective was using the developed surrogate safety measure to assess and compare the safety levels of Polish turbo-roundabout samples with and without raised lane dividers.The surrogate safety measure was based on speed and lane behaviour. Speed was obtained from video observations and floating car data, which enabled the construction of representative speed profiles. Lane behaviour data was gathered from video observations.The collection of the data allowed for a relative validation of the method by comparing the safety performance of turbo-roundabouts with and without raised lane dividers. In the end, the surrogate measure was applied for evaluation of safety levels and enhancement of the existing safety performance functions, which combine traffic volumes, and speeds as a function of radii). The final models may help quantify the safety impact of different turbo-roundabout solutions.
       
  • Evaluation of surrogate measures for pedestrian trips at intersections and
           crash modeling
    • Abstract: Publication date: Available online 31 May 2018Source: Accident Analysis & PreventionAuthor(s): Jaeyoung Lee, Mohamed Abdel-Aty, Imran Shah Pedestrians are considered the most vulnerable road users who are directly exposed to traffic crashes. With a view to addressing the growing concern of pedestrian safety, Federal and local governments aim at reducing pedestrian-involved crashes. Nevertheless, pedestrian volume data are rarely available even though they among the most important factors to identify pedestrian safety. Thus, this study aims at identifying surrogate measures for pedestrian exposure at intersections. A two-step process is implemented: the first step is the development of Tobit and generalized linear models for predicting pedestrian trips (i.e., exposure models). In the second step, negative binomial and zero inflated negative binomial models were developed for pedestrian crashes using the predicted pedestrian trips. The results indicate that among various exposure models the Tobit model performs the best in describing pedestrian exposure. The identified exposure-relevant factors are the presence of schools, car-ownership, pavement condition, sidewalk width, bus ridership, intersection control type and presence of sidewalk barrier. It was also found that the negative binomial model with the predicted pedestrian trips and that with the observed pedestrian trips perform equally well for estimating pedestrian crashes. Also, the difference between the observed and the predicted pedestrian trips does not appear as statistically significant, according to the results of the t-test and Wilcoxon signed-rank test. It is expected that the methodologies using predicted pedestrian trips or directly including pedestrian surrogate exposure variables can estimate safety performance functions for pedestrian crashes even though when pedestrian trip data is not available.
       
  • The measurement equivalence of a safety climate measure across five
           faultlines
    • Abstract: Publication date: Available online 21 May 2018Source: Accident Analysis & PreventionAuthor(s): Xiaohong Xu, Stephanie C. Payne, Mindy E. Bergman This 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. Sallinen Education 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
           drivers'
    • Abstract: Publication date: Available online 18 May 2018Source: Accident Analysis & PreventionAuthor(s): David Crundall, Victoria Kroll Can 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 Banks Technology-supported methods for sleep recording are becoming increasingly affordable. Sleep history feedback may help with fatigue-related decision making – Should I drive' Am I fit for work' This study examines a “sleep tank” model (SleepTank™), which is analogous to the fuel tank in a car, refilled by sleep, and depleted during wake. Required inputs are sleep period time and sleep efficiency (provided by many consumer-grade actigraphs). Outputs include suggested hours remaining to “get sleep” and percentage remaining in tank (Tank%). Initial proof of concept analyses were conducted using data from a laboratory-based simulated nightshift study. Ten, healthy males (18–35y) undertook an 8h baseline sleep opportunity and daytime performance testing (BL), followed by four simulated nightshifts (2000 h–0600 h), with daytime sleep opportunities (1000 h–1600 h), then an 8 h night-time sleep opportunity to return to daytime schedule (RTDS), followed by daytime performance testing. Psychomotor Vigilance Task (PVT) and Karolinska Sleepiness Scale were performed at 1200 h on BL and RTDS, and at 1830 h, 2130 h 0000 h and 0400 h each nightshift. A 40-minute York Driving Simulation was performed at 1730 h, 2030 h and 0300 h on each nightshift. Model outputs were calculated using sleep period timing and sleep efficiency (from polysomnography) for each participant. Tank% was a significant predictor of PVT lapses (p 
       
  • Effects of strategic early-morning caffeine gum administration on
           association between salivary alpha-amylase and neurobehavioural
           performance during 50 h of sleep deprivation
    • Abstract: Publication date: Available online 7 May 2018Source: Accident Analysis & PreventionAuthor(s): Maja Pajcin, Jason M White, Siobhan Banks, Jill Dorrian, Gemma M Paech, Crystal L Grant, Kayla Johnson, Katie Tooley, Eugene Aidman, Justin Fidock, Gary H Kamimori, Chris B Della Vedova Self-assessment is the most common method for monitoring performance and safety in the workplace. However, discrepancies between subjective and objective measures have increased interest in physiological assessment of performance. In a double-blind placebo-controlled study, 23 healthy adults were randomly assigned to either a placebo (n = 11; 5 F, 6 M) or caffeine condition (n = 12; 4 F, 8 M) while undergoing 50 h (i.e. two days) of total sleep deprivation. In previous work, higher salivary alpha-amylase (sAA) levels were associated with improved psychomotor vigilance and simulated driving performance in the placebo condition. In this follow-up article, the effects of strategic caffeine administration on the previously reported diurnal profiles of sAA and performance, and the association between sAA and neurobehavioural performance were investigated. Participants were given a 10 h baseline sleep opportunity (monitored via standard polysomnography techniques) prior to undergoing sleep deprivation (total sleep time: placebo = 8.83 ± 0.48 h; caffeine = 9.01 ± 0.48 h). During sleep deprivation, caffeine gum (200 mg) was administered at 01:00 h, 03:00 h, 05:00 h, and 07:00 h to participants in the caffeine condition (n = 12). This strategic administration of caffeine gum (200 mg) has been shown to be effective at maintaining cognitive performance during extended wakefulness. Saliva samples were collected, and psychomotor vigilance and simulated driving performance assessed at three-hour intervals throughout wakefulness. Caffeine effects on diurnal variability were compared with previously reported findings in the placebo condition (n = 11). The impact of caffeine on the circadian profile of sAA coincided with changes in neurobehavioural performance. Higher sAA levels were associated with improved performance on the psychomotor vigilance test during the first 24 h of wakefulness in the caffeine condition. However, only the association between sAA and response speed (i.e. reciprocal-transform of mean reaction time) was consistent across both days of sleep deprivation. The association between sAA and driving performance was not consistent across both days of sleep deprivation. Results show that the relationship between sAA and reciprocal-transform of mean reaction time on the psychomotor vigilance test persisted in the presence of caffeine, however the association was relatively weaker as compared with the placebo condition.
       
  • Analysing truck harsh braking incidents to study roundabout accident risk
    • Abstract: Publication date: Available online 5 May 2018Source: Accident Analysis & PreventionAuthor(s): Jwan Kamla, Tony Parry, Andrew Dawson In order to reduce accident risk, highway authorities prioritise maintenance budgets partly based upon previous accident history. However, as accident rates have continued to fall, this approach has become problematic as accident ‘black spots’ have been treated and the number of accidents at any individual site has fallen, making previous accident history a less reliable indicator of future accident risk. Another way of identifying sites of higher accident risk might be to identify near-miss accidents (where an accident nearly happened but was avoided). The principal aim of this paper is to analyze potentially unsafe truck driving conditions from counts of Harsh Braking Incidents (HBIs) at roundabouts and compare the results to similar, previous studies of accident numbers at the same sites, to explore if HBIs can be studied as a surrogate for accidents. This is achieved by processing truck telematics data with geo-referenced incidents of harsh braking. Models are then developed to characterise the relationships between truck HBIs and geometric and traffic variables. These HBIs are likely to occur more often than accidents and may, therefore, be useful in identifying sites with high accident risk. Based on the results of this study, it can be concluded that HBIs are influenced by traffic and geometric variables in a similar way to accidents; therefore they may be useful in considering accident risk at roundabouts. They are a source of higher volumes of data than accidents, which is important in considering changes or trends in accident risk over time. The results showed that random-parameters count data models provide better goodness of fit compared to fixed-parameters models and more variables were found to be significant, giving a better prediction of events.
       
  • School start times and teenage driver motor vehicle crashes
    • Abstract: Publication date: Available online 26 April 2018Source: Accident Analysis & PreventionAuthor(s): Robert D. Foss, Richard L. Smith, Natalie P. O'Brien IntroductionShifting school start times to 8:30 am or later has been found to improve academic performance and reduce behavior problems. Limited research suggests this may also reduce adolescent driver motor vehicle crashes. A change in the school start time from 7:30 am to 8:45 am for all public high schools in one North Carolina county presented the opportunity to address this question with greater methodologic rigor.MethodWe conducted ARIMA interrupted time-series analyses to examine motor vehicle crash rates of high school age drivers in the intervention county and 3 similar comparison counties with comparable urban-rural population distribution. To focus on crashes most likely to be affected, we limited analysis to crashes involving 16- & 17-year-old drivers occurring on days when school was in session.ResultsIn the intervention county, there was a 14% downward shift in the time-series following the 75 min delay in school start times (p = .076). There was no change approaching statistical significance in any of the other three counties. Further analysis indicated marked, statistically significant shifts in hourly crash rates in the intervention county, reflecting effects of the change in school start time on young driver exposure. Crashes from 7 to 7:59 am decreased sharply (−25%, p = .008), but increased similarly from 8 to 8:59 am (21%, p = .004). Crashes from 2 to 2:59 pm declined dramatically (−48%, p = .000), then increased to a lesser degree from 3 to 3:59 pm (32%, p = .024) and non-significantly from 4 to 4:59 (19%, p = .102). There was no meaningful change in early morning or nighttime crashes, when drowsiness-induced crashes might have been expected to be most common.DiscussionThe small decrease in crashes among high school age drivers following the shift in school start time is consistent with the findings of other studies of teen driver crashes and school start times. All these studies, including the present one, have limitations, but the similar findings suggest that crashes and school start times are indeed related, with earlier start times equating to more crashes.ConclusionLater high school start times (>8:30 am) appear to be associated with lower adolescent driver crash rates, but additional research is needed to confirm this and to identify the mechanism by which this occurs (reduced drowsiness or reduced exposure).
       
  • Drowsiness measures for commercial motor vehicle operations
    • Abstract: Publication date: Available online 26 April 2018Source: Accident Analysis & PreventionAuthor(s): Amy R. Sparrow, Cynthia M. LaJambe, Hans P.A. Van Dongen Timely detection of drowsiness in Commercial Motor Vehicle (C MV) operations is necessary to reduce drowsiness-related CMV crashes. This is relevant for manual driving and, paradoxically, even more so with increasing levels of driving automation. Measures available for drowsiness detection vary in reliability, validity, usability, and effectiveness. Passively recorded physiologic measures such as electroencephalography (EEG) and a variety of ocular parameters tend to accurately identify states of considerable drowsiness, but are limited in their potential to detect lower levels of drowsiness. They also do not correlate well with measures of driver performance. Objective measures of vigilant attention performance capture drowsiness reliably, but they require active driver involvement in a performance task and are prone to confounds from distraction and (lack of) motivation. Embedded performance measures of actual driving, such as lane deviation, have been found to correlate with physiologic and vigilance performance measures, yet to what extent drowsiness levels can be derived from them reliably remains a topic of investigation. Transient effects from external circumstances and behaviors – such as task load, light exposure, physical activity, and caffeine intake – may mask a driver’s underlying state of drowsiness. Also, drivers differ in the degree to which drowsiness affects their driving performance, based on trait vulnerability as well as age. This paper provides a broad overview of the current science pertinent to a range of drowsiness measures, with an emphasis on those that may be most relevant for CMV operations. There is a need for smart technologies that in a transparent manner combine different measurement modalities with mathematical representations of the neurobiological processes driving drowsiness, that account for various mediators and confounds, and that are appropriately adapted to the individual driver. The research for and development of such technologies requires a multi-disciplinary approach and significant resources, but is technically within reach.
       
  • Effects of methodological decisions on rainfall-related crash relative
           risk estimates
    • Abstract: Publication date: Available online 23 April 2018Source: Accident Analysis & PreventionAuthor(s): Alan W. Black, Gabriele Villarini Numerous studies have examined the influence of rainfall on the relative risk of crash, and they all agree that rainfall leads to an increase in relative risk as compared to dry conditions; what they do not agree on is the magnitude of these increases. Here we consider three methodological decisions made in computing the relative risk and examine their impacts: the inclusion or exclusion of zero total events (where no crashes occur during event or control periods), the temporal scale of analysis, and the use of information on pavement and weather conditions contained with the crash reports to determine relative risk. Our analyses are based on several years of data from six U.S. states (Arkansas, Georgia, Illinois, Maryland, Minnesota and Ohio). Zero total events in the context of weather related crash studies typically provide no information on the actual crash odds and greatly alter the distribution of relative risk estimates and should be removed from the analysis. While the use of a daily time step provides an estimate of relative risk that is not significantly different from an hourly time step for the majority of rural counties in our study area, the same is true of only 39% of the urban counties. Finally, the use of pavement and weather condition information from the crash reports results in relative risk estimates that are lower than the standard approach, however this difference decreases as rainfall totals increase. By highlighting the influence of methodological choices, we hope to pave the way towards the potential reduction in uncertainties in weather-related relative risk estimates.
       
  • Implications of estimating road traffic serious injuries from hospital
           data
    • Abstract: Publication date: Available online 19 April 2018Source: Accident Analysis & PreventionAuthor(s): K. Pérez, W. Weijermars, N. Bos, A.J. Filtness, R. Bauer, H. Johannsen, N. Nuyttens, L. Pascal, P. Thomas, M. Olabarria, The Working group of WP7 project To determine accurately the number of serious injuries at EU level and to compare serious injury rates between different countries it is essential to use a common definition. In January 2013, the High Level Group on Road Safety established the definition of serious injuries as patients with an injury level of MAIS3+(Maximum Abbreviated Injury Scale). Whatever the method used for estimating the number or serious injuries, at some point it is always necessary to use hospital records. The aim of this paper is to understand the implications for (1) in/exclusion criteria applied to case selection and (2) a methodological approach for converting ICD (International Classification of Diseases/Injuries) to MAIS codes, when estimating the number of road traffic serious injuries from hospital data. A descriptive analysis with hospital data from Spain and the Netherlands was carried out to examine the effect of certain choices concerning in- and exclusion criteria based on codes of the ICD9-CM and ICD10. The main parameters explored were: deaths before and after 30 days, readmissions, and external injury causes. Additionally, an analysis was done to explore the impact of using different conversion tools to derive MAIS3 + using data from Austria, Belgium, France, Germany, Netherlands, and Spain. Recommendations are given regarding the in/exclusion criteria and when there is incomplete data to ascertain a road injury, weighting factors could be used to correct data deviations and make more real estimations.
       
  • Risk management in port and maritime logistics
    • Abstract: Publication date: Available online 11 April 2018Source: Accident Analysis & PreventionAuthor(s): Jasmine Siu Lee Lam, Y.H. Venus Lun, Michael G.H. Bell
       
  • Dangerous intersections' A review of studies of fatigue and
           distraction in the automated vehicle
    • Abstract: Publication date: Available online 10 April 2018Source: Accident Analysis & PreventionAuthor(s): Gerald Matthews, Catherine Neubauer, Dyani J. Saxby, Ryan W. Wohleber, Jinchao Lin The impacts of fatigue on the vehicle driver may change with technological advancements including automation and the increasing prevalence of potentially distracting in-car systems. This article reviews the authors’ simulation studies of how fatigue, automation, and distraction may intersect as threats to safety. Distinguishing between states of active and passive fatigue supports understanding of fatigue and the development of countermeasures. Active fatigue is a stress-like state driven by overload of cognitive capabilities. Passive fatigue is produced by underload and monotony, and is associated with loss of task engagement and alertness. Our studies show that automated driving reliably elicits subjective symptoms of passive fatigue and also loss of alertness that persists following manual takeover. Passive fatigue also impairs attention and automation use in operators of Remotely Piloted Vehicles (RPVs). Use of in-vehicle media has been proposed as a countermeasure to fatigue, but such media may also be distracting. Studies tested whether various forms of phone-based media interacted with automation-induced fatigue, but effects were complex and dependent on task configuration. Selection of fatigue countermeasures should be guided by an understanding of the form of fatigue confronting the operator. System design, regulation of level of automation, managing distraction, and selection of fatigue-resilient personnel are all possible interventions for passive fatigue, but careful evaluation of interventions is necessary prior to deployment.
       
  • The relation between working conditions, aberrant driving behaviour and
           crash propensity among taxi drivers in China
    • Abstract: Publication date: Available online 4 April 2018Source: Accident Analysis & PreventionAuthor(s): Yonggang Wang, Linchao Li, Carlo G. Prato Although the taxi industry is playing an important role in Chinese everyday life, little attention has been posed towards occupational health issues concerning the taxi drivers’ working conditions, driving behaviour and road safety. A cross-sectional survey was administered to 1021 taxi drivers from 21 companies in four Chinese cities and collected information about (i) sociodemographic characteristics, (ii) working conditions, (iii) frequency of daily aberrant driving behaviour, and (iv) involvement in property-damage-only (PDO) and personal injury (PI) crashes over the past two years. A hybrid bivariate model of crash involvement was specified: (i) the hybrid part concerned a latent variable model capturing unobserved traits of the taxi drivers; (ii) the bivariate part modelled jointly both types of crashes while capturing unobserved correlation between error terms. The survey answers paint a gloomy picture in terms of workload, as taxi drivers reported averages of 9.4 working hours per day and 6.7 working days per week that amount on average to about 63.0 working hours per week. Moreover, the estimates of the hybrid bivariate model reveal that increasing levels of fatigue, reckless behaviour and aggressive behaviour are positively related to a higher propensity of crash involvement. Lastly, the heavy workload is also positively correlated with the higher propensity of crashing, not only directly as a predictor of crash involvement, but also indirectly as a covariate of fatigue and aberrant driving behaviour. The findings from this study provide insights into potential strategies for preventive education and taxi industry management to improve the working conditions and hence reduce fatigue and road risk for the taxi drivers.
       
  • Predicting performance and safety based on driver fatigue
    • Abstract: Publication date: Available online 3 April 2018Source: Accident Analysis & PreventionAuthor(s): Daniel Mollicone, Kevin Kan, Chris Mott, Rachel Bartels, Steve Bruneau, Matthew van Wollen, Amy R. Sparrow, Hans P.A. Van Dongen Fatigue causes decrements in vigilant attention and reaction time and is a major safety hazard in the trucking industry. There is a need to quantify the relationship between driver fatigue and safety in terms of operationally relevant measures. Hard-braking events are a suitable measure for this purpose as they are relatively easily observed and are correlated with collisions and near-crashes. We developed an analytic approach that predicts driver fatigue based on a biomathematical model and then estimates hard-braking events as a function of predicted fatigue, controlling for time of day to account for systematic variations in exposure (traffic density). The analysis used de-identified data from a previously published, naturalistic field study of 106 U.S. commercial motor vehicle (CMV) drivers. Data analyzed included drivers’ official duty logs, sleep patterns measured around the clock using wrist actigraphy, and continuous recording of vehicle data to capture hard-braking events. The curve relating predicted fatigue to hard-braking events showed that the frequency of hard-braking events increased as predicted fatigue levels worsened. For each increment on the fatigue scale, the frequency of hard-braking events increased by 7.8%. The results provide proof of concept for a novel approach that predicts fatigue based on drivers’ sleep patterns and estimates driving performance in terms of an operational metric related to safety. The approach can be translated to practice by CMV operators to achieve a fatigue risk profile specific to their own settings, in order to support data-driven decisions about fatigue countermeasures that cost-effectively deliver quantifiable operational benefits.
       
  • Cognitive flexibility: A distinct element of performance impairment due to
           sleep deprivation
    • Abstract: Publication date: Available online 15 March 2018Source: Accident Analysis & PreventionAuthor(s): K.A. Honn, J.M. Hinson, P. Whitney, H.P.A. Van Dongen In around-the-clock operations, reduced alertness due to circadian misalignment and sleep loss causes performance impairment, which can lead to catastrophic errors and accidents. There is mounting evidence that performance on different tasks is differentially affected, but the general principles underlying this differentiation are not well understood. One factor that may be particularly relevant is the degree to which tasks require executive control, that is, control over the initiation, monitoring, and termination of actions in order to achieve goals. A key aspect of this is cognitive flexibility, i.e., the deployment of cognitive control resources to adapt to changes in events. Loss of cognitive flexibility due to sleep deprivation has been attributed to “feedback blunting,” meaning that feedback on behavioral outcomes has reduced salience - and that feedback is therefore less effective at driving behavior modification under changing circumstances. The cognitive mechanisms underlying feedback blunting are as yet unknown. Here we present data from an experiment that investigated the effects of sleep deprivation on performance after an unexpected reversal of stimulus-response mappings, requiring cognitive flexibility to maintain good performance. Nineteen healthy young adults completed a 4-day in-laboratory study. Subjects were randomized to either a total sleep deprivation condition (n = 11) or a control condition (n = 8). Athree-phase reversal learning decision task was administered at baseline, and again after 30.5 h of sleep deprivation, or matching well-rested control. The task was based on a go/no go task paradigm, in which stimuli were assigned to either a go (response) set or a no go (no response) set. Each phase of the task included four stimuli (two in the go set and two in the no go set). After each stimulus presentation, subjects could make a response within 750 ms or withhold their response. They were then shown feedback on the accuracy of their response. In phase 1 of the task, subjects were explicitly told which stimuli were assigned to the go and no go sets. In phases 2 and 3, new stimuli were used that were different from those used in phase 1. Subjects were not explicitly told the go/no go mappings and were instead required to use accuracy feedback to learn which stimuli were in the go and nogo sets. Phase 3 continued directly from phase 2 and retained the same stimuli as in phase 2, but there was an unannounced reversal of the stimulus-response mappings. Task results confirmed that sleep deprivation resulted in loss of cognitive flexibility through feedback blunting, and that this effect was not produced solely by (1) general performance impairment because of overwhelming sleep drive; (2) reduced working memory resources available to perform the task; (3) incomplete learning of stimulus-response mappings before the unannounced reversal; or (4) interference with stimulus identification through lapses in vigilant attention. Overall, the results suggest that sleep deprivation causes a fundamental problem with dynamic attentional control. This element of performance impairment due to sleep deprivation appears to be distinct from vigilant attention deficits, and represents a particularly significant challenge for fatigue risk management.
       
  • Assessing crash risk considering vehicle interactions with trucks using
           point detector data
    • Abstract: Publication date: Available online 12 March 2018Source: Accident Analysis & PreventionAuthor(s): Kyung (Kate) Hyun, Kyungsoo Jeong, Andre Tok, Stephen G. Ritchie Trucks have distinct driving characteristics in general traffic streams such as lower speeds and limitations in acceleration and deceleration. As a consequence, vehicles keep longer headways or frequently change lane when they follow a truck, which is expected to increase crash risk. This study introduces several traffic measures at the individual vehicle level to capture vehicle interactions between trucks and non-trucks and analyzed how the measures affect crash risk under different traffic conditions. The traffic measures were developed using headways obtained from Inductive Loop Detectors (ILDs). In addition, a truck detection algorithm using a Gaussian Mixture (GM) model was developed to identify trucks and to estimate truck exposure from ILD data. Using the identified vehicle types from the GM model, vehicle interaction metrics were categorized into three groups based on the combination of leading and following vehicle types. The effects of the proposed traffic measures on crash risk were modeled in two different cases of prior- and non-crash using a case-control approach utilizing a conditional logistic regression. Results showed that the vehicle interactions between the leading and following vehicle types were highly associated with crash risk, and further showed different impacts on crash risk by traffic conditions. Specifically, crashes were more likely to occur when a truck following a non-truck had shorter average headway but greater headway variance in heavy traffic while a non-truck following a truck had greater headway variance in light traffic. This study obtained meaningful conclusions that vehicle interactions involved with trucks were significantly related to the crash likelihood rather than the measures that estimate average traffic condition such as total volume or average headway of the traffic stream.
       
  • Data and methods for studying commercial motor vehicle driver fatigue,
           highway safety and long-term driver health
    • Abstract: Publication date: Available online 9 March 2018Source: Accident Analysis & PreventionAuthor(s): Hal S. Stern, Daniel Blower, Michael L. Cohen, Charles A. Czeisler, David F. Dinges, Joel B. Greenhouse, Feng Guo, Richard J. Hanowski, Natalie P. Hartenbaum, Gerald P. Krueger, Melissa M. Mallis, Richard F. Pain, Matthew Rizzo, Esha Sinha, Dylan S. Small, Elizabeth A. Stuart, David H. Wegman This article summarizes the recommendations on data and methodology issues for studying commercial motor vehicle driver fatigue of a National Academies of Sciences, Engineering, and Medicine study. A framework is provided that identifies the various factors affecting driver fatigue and relating driver fatigue to crash risk and long-term driver health. The relevant factors include characteristics of the driver, vehicle, carrier and environment. Limitations of existing data are considered and potential sources of additional data described. Statistical methods that can be used to improve understanding of the relevant relationships from observational data are also described. The recommendations for enhanced data collection and the use of modern statistical methods for causal inference have the potential to enhance our understanding of the relationship of fatigue to highway safety and to long-term driver health.
       
  • Exploring the temporal stability of global road safety statistics
    • Abstract: Publication date: Available online 21 February 2018Source: Accident Analysis & PreventionAuthor(s): Loukas Dimitriou, Paraskevas Nikolaou, Constantinos Antoniou Given the importance of rigorous quantitative reasoning in supporting national, regional or global road safety policies, data quality, reliability, and stability are of the upmost importance. This study focuses on macroscopic properties of road safety statistics and the temporal stability of these statistics at a global level. A thorough investigation of two years of measurements was conducted to identify any unexpected gaps that could highlight the existence of inconsistent measurements. The database used in this research includes 121 member countries of the United Nation (UN-121) with a population of at least one million (smaller country data shows higher instability) and includes road safety and socioeconomic variables collected from a number of international databases (e.g. WHO and World Bank) for the years 2010 and 2013. For the fulfillment of the earlier stated goal, a number of data visualization and exploratory analyses (Hierarchical Clustering and Principal Component Analysis) were conducted. Furthermore, in order to provide a richer analysis of the data, we developed and compared the specification of a number of Structural Equation Models for the years 2010 and 2013. Different scenarios have been developed, with different endogenous variables (indicators of mortality rate and fatality risk) and structural forms. The findings of the current research indicate inconsistency phenomena in global statistics of different instances/years. Finally, the results of this research provide evidence on the importance of careful and systematic data collection for developing advanced statistical and econometric techniques and furthermore for developing road safety policies.
       
  • Fatigue as a mediator of the relationship between quality of life and
           mental health problems in hospital nurses
    • Abstract: Publication date: Available online 14 February 2018Source: Accident Analysis & PreventionAuthor(s): Ahmad Bazazan, Iman Dianat, Zohreh Mombeini, Aydin Aynehchi, Mohammad Asghari Jafarabadi The aims of this study were to investigate the relationships among quality of life (QoL), mental health problems and fatigue among hospital nurses, and to test whether fatigue and its multiple dimensions would mediate the effect of QoL on mental health problems. Data were collected using questionnaires (including the World Health Organization Quality of Life-BREF [WHOQOL-BREF], General Health Questionnaire [GHQ-12] and Multidimensional Fatigue Inventory [MFI-20] for evaluation of QoL, mental health problems and fatigue, respectively) from 990 Iranian hospital nurses, and analysed by generalized structural equation modelling (GSEM). The results indicated that QoL, mental health problems and fatigue were interrelated, and supported the direct and indirect (through fatigue) effects of QoL on mental health problems. All domains of the WHOQOL-BREF, and particularly physical (sleep problems), psychological (negative feelings) and environmental health (leisure activities) domains, were strongly related to the mental health status of the studied nurses. Fatigue and its multiple dimensions partially mediated the relationship between QoL and mental health problems. The results highlighted the importance of physical, psychological and environmental aspects of QoL and suggested the need for potential interventions to improve fatigue (particularly physical fatigue along with mental fatigue) and consequently mental health status of this working population. The findings have possible implications for nurses' health and patient safety outcomes.
       
  • Prevalence of operator fatigue in winter maintenance operations
    • Abstract: Publication date: Available online 3 February 2018Source: Accident Analysis & PreventionAuthor(s): Matthew C. Camden, Alejandra Medina-Flintsch, Jeffrey S. Hickman, James Bryce, Gerardo Flintsch, Richard J. Hanowski Similar to commercial motor vehicle drivers, winter maintenance operators are likely to be at an increased risk of becoming fatigued while driving due to long, inconsistent shifts, environmental stressors, and limited opportunities for sleep. Despite this risk, there is little research concerning the prevalence of winter maintenance operator fatigue during winter emergencies. The purpose of this research was to investigate the prevalence, sources, and countermeasures of fatigue in winter maintenance operations. Questionnaires from 1043 winter maintenance operators and 453 managers were received from 29 Clear Road member states. Results confirmed that fatigue was prevalent in winter maintenance operations. Over 70% of the operators and managers believed that fatigue has a moderate to significant impact on winter maintenance operations. Approximately 75% of winter maintenance operators reported to at least sometimes drive while fatigued, and 96% of managers believed their winter maintenance operators drove while fatigued at least some of the time. Furthermore, winter maintenance operators and managers identified fatigue countermeasures and sources of fatigue related to winter maintenance equipment. However, the countermeasures believed to be the most effective at reducing fatigue during winter emergencies (i.e., naps) were underutilized. For example, winter maintenance operators reported to never use naps to eliminate fatigue. These results indicated winter maintenance operations are impacted by operator fatigue. These results support the increased need for research and effective countermeasures targeting winter maintenance operator fatigue.
       
  • Modeling when and where a secondary accident occurs
    • Abstract: Publication date: Available online 2 February 2018Source: Accident Analysis & PreventionAuthor(s): Junhua Wang, Boya Liu, Ting Fu, Shuo Liu, Joshua Stipancic The occurrence of secondary accidents leads to traffic congestion and road safety issues. Secondary accident prevention has become a major consideration in traffic incident management. This paper investigates the location and time of a potential secondary accident after the occurrence of an initial traffic accident. With accident data and traffic loop data collected over three years from California interstate freeways, a shock wave-based method was introduced to identify secondary accidents. A linear regression model and two machine learning algorithms, including a back-propagation neural network (BPNN) and a least squares support vector machine (LSSVM), were implemented to explore the distance and time gap between the initial and secondary accidents using inputs of crash severity, violation category, weather condition, tow away, road surface condition, lighting, parties involved, traffic volume, duration, and shock wave speed generated by the primary accident. From the results, the linear regression model was inadequate in describing the effect of most variables and its goodness-of-fit and accuracy in prediction was relatively poor. In the training programs, the BPNN and LSSVM demonstrated adequate goodness-of-fit, though the BPNN was superior with a higher CORR and lower MSE. The BPNN model also outperformed the LSSVM in time prediction, while both failed to provide adequate distance prediction. Therefore, the BPNN model could be used to forecast the time gap between initial and secondary accidents, which could be used by decision makers and incident management agencies to prevent or reduce secondary collisions.
       
  • Impact of real-time traffic characteristics on crash occurrence:
           Preliminary results of the case of rare events
    • Abstract: Publication date: Available online 5 January 2018Source: Accident Analysis & PreventionAuthor(s): Athanasios Theofilatos, George Yannis, Pantelis Kopelias, Fanis Papadimitriou Considerable efforts have been made from researchers and policy makers in order to explain road crash occurrence and improve road safety performance of highways. However, there are cases when crashes are so few that they could be considered as rare events. In such cases, the binary dependent variable is characterized by dozens to thousands of times fewer events (crashes) than non-events (non-crashes). This paper attempts to add to the current knowledge by investigating crash likelihood by utilizing real-time traffic data and by proposing a framework driven by appropriate statistical models (Bias Correction and Firth method) in order to overcome the problems that arise when the number of crashes is very low. Under this approach instead of using traditional logistic regression methods, crashes are considered as rare events In order to demonstrate this approach, traffic data were collected from three random loop detectors in the Attica Tollway (“Attiki Odos”) located in Greater Athens Area in Greece for the 2008–2011 period. The traffic dataset consists of hourly aggregated traffic data such as flow, occupancy, mean time speed and percentage of trucks in traffic. This study demonstrates the application and findings of our approach and revealed a negative relationship between crash occurrence and speed in crash locations. The method and findings of the study attempt to provide insights on the mechanism of crash occurrence and also to overcome data considerations for the first time in safety evaluation of motorways.
       
 
 
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