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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: 33, SJR: 1.655, CiteScore: 2)
Academic Radiology     Hybrid Journal   (Followers: 23, SJR: 1.015, CiteScore: 2)
Accident Analysis & Prevention     Partially Free   (Followers: 95, SJR: 1.462, CiteScore: 3)
Accounting Forum     Hybrid Journal   (Followers: 25, SJR: 0.932, CiteScore: 2)
Accounting, Organizations and Society     Hybrid Journal   (Followers: 36, 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: 412, SJR: 0.758, CiteScore: 2)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 2)
Acta Biomaterialia     Hybrid Journal   (Followers: 27, SJR: 1.967, CiteScore: 7)
Acta Colombiana de Cuidado Intensivo     Full-text available via subscription   (Followers: 2)
Acta de Investigación Psicológica     Open Access   (Followers: 3)
Acta Ecologica Sinica     Open Access   (Followers: 10, SJR: 0.18, CiteScore: 1)
Acta Haematologica Polonica     Free   (Followers: 1, SJR: 0.128, CiteScore: 0)
Acta Histochemica     Hybrid Journal   (Followers: 3, SJR: 0.661, CiteScore: 2)
Acta Materialia     Hybrid Journal   (Followers: 249, SJR: 3.263, CiteScore: 6)
Acta Mathematica Scientia     Full-text available via subscription   (Followers: 5, SJR: 0.504, CiteScore: 1)
Acta Mechanica Solida Sinica     Full-text available via subscription   (Followers: 9, SJR: 0.542, CiteScore: 1)
Acta Oecologica     Hybrid Journal   (Followers: 12, SJR: 0.834, CiteScore: 2)
Acta Otorrinolaringologica (English Edition)     Full-text available via subscription  
Acta Otorrinolaringológica Española     Full-text available via subscription   (Followers: 2, SJR: 0.307, CiteScore: 0)
Acta Pharmaceutica Sinica B     Open Access   (Followers: 1, SJR: 1.793, CiteScore: 6)
Acta Poética     Open Access   (Followers: 4, SJR: 0.101, CiteScore: 0)
Acta Psychologica     Hybrid Journal   (Followers: 27, SJR: 1.331, CiteScore: 2)
Acta Sociológica     Open Access   (Followers: 1)
Acta Tropica     Hybrid Journal   (Followers: 6, SJR: 1.052, CiteScore: 2)
Acta Urológica Portuguesa     Open Access  
Actas Dermo-Sifiliograficas     Full-text available via subscription   (Followers: 3, SJR: 0.374, CiteScore: 1)
Actas Dermo-Sifiliográficas (English Edition)     Full-text available via subscription   (Followers: 2)
Actas Urológicas Españolas     Full-text available via subscription   (Followers: 3, SJR: 0.344, CiteScore: 1)
Actas Urológicas Españolas (English Edition)     Full-text available via subscription   (Followers: 1)
Actualites Pharmaceutiques     Full-text available via subscription   (Followers: 6, SJR: 0.19, CiteScore: 0)
Actualites Pharmaceutiques Hospitalieres     Full-text available via subscription   (Followers: 3)
Acupuncture and Related Therapies     Hybrid Journal   (Followers: 6)
Acute Pain     Full-text available via subscription   (Followers: 14, SJR: 2.671, CiteScore: 5)
Ad Hoc Networks     Hybrid Journal   (Followers: 11, SJR: 0.53, CiteScore: 4)
Addictive Behaviors     Hybrid Journal   (Followers: 16, SJR: 1.29, CiteScore: 3)
Addictive Behaviors Reports     Open Access   (Followers: 8, SJR: 0.755, CiteScore: 2)
Additive Manufacturing     Hybrid Journal   (Followers: 9, SJR: 2.611, CiteScore: 8)
Additives for Polymers     Full-text available via subscription   (Followers: 22)
Advanced Drug Delivery Reviews     Hybrid Journal   (Followers: 148, SJR: 4.09, CiteScore: 13)
Advanced Engineering Informatics     Hybrid Journal   (Followers: 11, SJR: 1.167, CiteScore: 4)
Advanced Powder Technology     Hybrid Journal   (Followers: 17, SJR: 0.694, CiteScore: 3)
Advances in Accounting     Hybrid Journal   (Followers: 8, SJR: 0.277, CiteScore: 1)
Advances in Agronomy     Full-text available via subscription   (Followers: 12, SJR: 2.384, CiteScore: 5)
Advances in Anesthesia     Full-text available via subscription   (Followers: 28, SJR: 0.126, CiteScore: 0)
Advances in Antiviral Drug Design     Full-text available via subscription   (Followers: 2)
Advances in Applied Mathematics     Full-text available via subscription   (Followers: 10, SJR: 0.992, CiteScore: 1)
Advances in Applied Mechanics     Full-text available via subscription   (Followers: 11, SJR: 1.551, CiteScore: 4)
Advances in Applied Microbiology     Full-text available via subscription   (Followers: 23, 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: 32, SJR: 3.043, CiteScore: 6)
Advances in Carbohydrate Chemistry and Biochemistry     Full-text available via subscription   (Followers: 8, 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: 29, SJR: 1.562, CiteScore: 3)
Advances in Colloid and Interface Science     Full-text available via subscription   (Followers: 19, SJR: 1.977, CiteScore: 8)
Advances in Computers     Full-text available via subscription   (Followers: 14, SJR: 0.205, CiteScore: 1)
Advances in Dermatology     Full-text available via subscription   (Followers: 15)
Advances in Developmental Biology     Full-text available via subscription   (Followers: 12)
Advances in Digestive Medicine     Open Access   (Followers: 9)
Advances in DNA Sequence-Specific Agents     Full-text available via subscription   (Followers: 5)
Advances in Drug Research     Full-text available via subscription   (Followers: 25)
Advances in Ecological Research     Full-text available via subscription   (Followers: 44, SJR: 2.524, CiteScore: 4)
Advances in Engineering Software     Hybrid Journal   (Followers: 28, SJR: 1.159, CiteScore: 4)
Advances in Experimental Biology     Full-text available via subscription   (Followers: 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: 58, SJR: 0.591, CiteScore: 2)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 16)
Advances in Genetics     Full-text available via subscription   (Followers: 16, SJR: 1.354, CiteScore: 4)
Advances in Genome Biology     Full-text available via subscription   (Followers: 8, SJR: 12.74, CiteScore: 13)
Advances in Geophysics     Full-text available via subscription   (Followers: 6, SJR: 1.193, CiteScore: 3)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 21, SJR: 0.368, CiteScore: 1)
Advances in Heterocyclic Chemistry     Full-text available via subscription   (Followers: 12, SJR: 0.749, CiteScore: 3)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 22)
Advances in Imaging and Electron Physics     Full-text available via subscription   (Followers: 2, SJR: 0.193, CiteScore: 0)
Advances in Immunology     Full-text available via subscription   (Followers: 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: 17, 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: 22)
Advances in Molecular and Cellular Endocrinology     Full-text available via subscription   (Followers: 8)
Advances in Molecular Toxicology     Full-text available via subscription   (Followers: 7, SJR: 0.182, CiteScore: 0)
Advances in Nanoporous Materials     Full-text available via subscription   (Followers: 3)
Advances in Oncobiology     Full-text available via subscription   (Followers: 1)
Advances in Organ Biology     Full-text available via subscription   (Followers: 1)
Advances in Organometallic Chemistry     Full-text available via subscription   (Followers: 17, SJR: 1.875, CiteScore: 4)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7, SJR: 0.174, CiteScore: 0)
Advances in Parasitology     Full-text available via subscription   (Followers: 5, SJR: 1.579, CiteScore: 4)
Advances in Pediatrics     Full-text available via subscription   (Followers: 24, SJR: 0.461, CiteScore: 1)
Advances in Pharmaceutical Sciences     Full-text available via subscription   (Followers: 11)
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: 9)
Advances in Plant Pathology     Full-text available via subscription   (Followers: 5)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Protein Chemistry     Full-text available via subscription   (Followers: 18)
Advances in Protein Chemistry and Structural Biology     Full-text available via subscription   (Followers: 20, SJR: 0.791, CiteScore: 2)
Advances in Psychology     Full-text available via subscription   (Followers: 62)
Advances in Quantum Chemistry     Full-text available via subscription   (Followers: 6, SJR: 0.371, CiteScore: 1)
Advances in Radiation Oncology     Open Access   (SJR: 0.263, CiteScore: 1)
Advances in Small Animal Medicine and Surgery     Hybrid Journal   (Followers: 3, SJR: 0.101, CiteScore: 0)
Advances in Space Biology and Medicine     Full-text available via subscription   (Followers: 6)
Advances in Space Research     Full-text available via subscription   (Followers: 395, 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: 33, 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: 340, 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: 449, SJR: 1.238, CiteScore: 3)
Agri Gene     Hybrid Journal   (Followers: 1, SJR: 0.13, CiteScore: 0)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 17, SJR: 1.818, CiteScore: 5)
Agricultural Systems     Hybrid Journal   (Followers: 31, SJR: 1.156, CiteScore: 4)
Agricultural Water Management     Hybrid Journal   (Followers: 42, SJR: 1.272, CiteScore: 3)
Agriculture and Agricultural Science Procedia     Open Access   (Followers: 3)
Agriculture and Natural Resources     Open Access   (Followers: 3)
Agriculture, Ecosystems & Environment     Hybrid Journal   (Followers: 57, SJR: 1.747, CiteScore: 4)
Ain Shams Engineering J.     Open Access   (Followers: 5, SJR: 0.589, CiteScore: 3)
Air Medical J.     Hybrid Journal   (Followers: 6, SJR: 0.26, CiteScore: 0)
AKCE Intl. J. of Graphs and Combinatorics     Open Access   (SJR: 0.19, CiteScore: 0)
Alcohol     Hybrid Journal   (Followers: 11, SJR: 1.153, CiteScore: 3)
Alcoholism and Drug Addiction     Open Access   (Followers: 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: 11, SJR: 1.142, CiteScore: 4)
Alkaloids: Chemical and Biological Perspectives     Full-text available via subscription   (Followers: 2)
Allergologia et Immunopathologia     Full-text available via subscription   (Followers: 1, SJR: 0.504, CiteScore: 1)
Allergology Intl.     Open Access   (Followers: 5, SJR: 1.148, CiteScore: 2)
Alpha Omegan     Full-text available via subscription   (SJR: 3.521, CiteScore: 6)
ALTER - European J. of Disability Research / Revue Européenne de Recherche sur le Handicap     Full-text available via subscription   (Followers: 9, SJR: 0.201, CiteScore: 1)
Alzheimer's & Dementia     Hybrid Journal   (Followers: 51, SJR: 4.66, CiteScore: 10)
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring     Open Access   (Followers: 4, SJR: 1.796, CiteScore: 4)
Alzheimer's & Dementia: Translational Research & Clinical Interventions     Open Access   (Followers: 4, SJR: 1.108, CiteScore: 3)
Ambulatory Pediatrics     Hybrid Journal   (Followers: 6)
American Heart J.     Hybrid Journal   (Followers: 50, SJR: 3.267, CiteScore: 4)
American J. of Cardiology     Hybrid Journal   (Followers: 54, SJR: 1.93, CiteScore: 3)
American J. of Emergency Medicine     Hybrid Journal   (Followers: 45, SJR: 0.604, CiteScore: 1)
American J. of Geriatric Pharmacotherapy     Full-text available via subscription   (Followers: 10)
American J. of Geriatric Psychiatry     Hybrid Journal   (Followers: 14, SJR: 1.524, CiteScore: 3)
American J. of Human Genetics     Hybrid Journal   (Followers: 34, SJR: 7.45, CiteScore: 8)
American J. of Infection Control     Hybrid Journal   (Followers: 28, SJR: 1.062, CiteScore: 2)
American J. of Kidney Diseases     Hybrid Journal   (Followers: 34, SJR: 2.973, CiteScore: 4)
American J. of Medicine     Hybrid Journal   (Followers: 46)
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: 209, SJR: 2.7, CiteScore: 4)
American J. of Ophthalmology     Hybrid Journal   (Followers: 63, SJR: 3.184, CiteScore: 4)
American J. of Ophthalmology Case Reports     Open Access   (Followers: 5, SJR: 0.265, CiteScore: 0)
American J. of Orthodontics and Dentofacial Orthopedics     Full-text available via subscription   (Followers: 6, SJR: 1.289, CiteScore: 1)
American J. of Otolaryngology     Hybrid Journal   (Followers: 25, SJR: 0.59, CiteScore: 1)
American J. of Pathology     Hybrid Journal   (Followers: 27, SJR: 2.139, CiteScore: 4)
American J. of Preventive Medicine     Hybrid Journal   (Followers: 28, SJR: 2.164, CiteScore: 4)
American J. of Surgery     Hybrid Journal   (Followers: 38, SJR: 1.141, CiteScore: 2)
American J. of the Medical Sciences     Hybrid Journal   (Followers: 12, SJR: 0.767, CiteScore: 1)
Ampersand : An Intl. J. of General and Applied Linguistics     Open Access   (Followers: 7)
Anaerobe     Hybrid Journal   (Followers: 4, SJR: 1.144, CiteScore: 3)
Anaesthesia & Intensive Care Medicine     Full-text available via subscription   (Followers: 62, SJR: 0.138, CiteScore: 0)
Anaesthesia Critical Care & Pain Medicine     Full-text available via subscription   (Followers: 17, SJR: 0.411, CiteScore: 1)
Anales de Cirugia Vascular     Full-text available via subscription  
Anales de Pediatría     Full-text available via subscription   (Followers: 3, SJR: 0.277, CiteScore: 0)
Anales de Pediatría (English Edition)     Full-text available via subscription  
Anales de Pediatría Continuada     Full-text available via subscription  
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 5, SJR: 4.849, CiteScore: 10)
Analytica Chimica Acta     Hybrid Journal   (Followers: 43, SJR: 1.512, CiteScore: 5)
Analytical Biochemistry     Hybrid Journal   (Followers: 175, SJR: 0.633, CiteScore: 2)
Analytical Chemistry Research     Open Access   (Followers: 11, SJR: 0.411, CiteScore: 2)
Analytical Spectroscopy Library     Full-text available via subscription   (Followers: 11)
Anesthésie & Réanimation     Full-text available via subscription   (Followers: 2)
Anesthesiology Clinics     Full-text available via subscription   (Followers: 23, SJR: 0.683, CiteScore: 2)
Angiología     Full-text available via subscription   (SJR: 0.121, CiteScore: 0)
Angiologia e Cirurgia Vascular     Open Access   (Followers: 1, SJR: 0.111, CiteScore: 0)
Animal Behaviour     Hybrid Journal   (Followers: 192, SJR: 1.58, CiteScore: 3)

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Journal Cover
Accident Analysis & Prevention
Journal Prestige (SJR): 1.462
Citation Impact (citeScore): 3
Number of Followers: 95  
 
  Partially Free Journal Partially Free Journal
ISSN (Print) 0001-4575
Published by Elsevier Homepage  [3162 journals]
  • Comparative analysis of multiple techniques for developing and
           transferring safety performance functions
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Ahmed Farid, Mohamed Abdel-Aty, Jaeyoung Lee Safety performance functions (SPFs) are crash count prediction models that are used for identifying high crash risk locations, evaluating road safety before and after countermeasure deployment and comparing the safety of alternative site designs. The traditional method of modeling crash counts is negative binomial (NB) regression. Furthermore, the Highway Safety Manual (HSM) provides analytical tools, including NB SPFs, to assess and improve road safety. Even though the HSM’s SPFs are restricted to NB models, the road safety literature is rich with a variety of different modeling techniques. Researchers have calibrated the HSM’s SPFs to local conditions using a calibration method prescribed by the HSM. However, studies in which SPFs are developed and transferred to other localities are uncommon. In this paper, we develop and transfer rural divided multilane highway segment SPFs of Florida, Ohio, Illinois, Minnesota, California, Washington and North Carolina to each state. For every state, NB, zero-inflated NB, Poisson lognormal (PLN), regression tree, random forest (RF), boosting and Tobit models are developed. A hybrid model that coalesces the predictions of both the Tobit and the NB model is proposed and developed as well. All SPFs are transferred to each state and their predictive performances are evaluated to discern which model type is the most transferable. According to the transferability results, there is no single superior model type. However, the Tobit, RF, tree, NB and hybrid models demonstrate better predictive performances than those of the other methods in a considerably large proportion of transferred SPFs.
       
  • Mind wandering during everyday driving: An on-road study
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Bridget R.D. Burdett, Samuel G. Charlton, Nicola J. Starkey This study was an investigation into mind wandering during everyday driving, and its association with crash patterns. We selected a 25 km route on urban roads for analysis of crashes, and an on-road study of mind wandering by a sample of drivers familiar with the route. We analysed reported crashes on the route over a five year period from New Zealand's crash database. For the on-road study a researcher accompanied 25 drivers on the route, asking them what they were thinking about at 15 predetermined road sections. The road sections were selected to include a range of different speed limits and traffic volumes as well as roundabouts, priority intersections and midblocks. Thought samples were categorised as either mind wandering or driving focus, and triggered by the senses, or internally. The frequencies of mind wandering at different road sections on the route were compared to the frequencies of reported crashes along the same route over the preceding five years. Results showed that although all drivers reported mind wandering, it was more likely to be reported at slower, quieter, less complex road sections. Overall, more crashes were reported at priority intersections and midblocks than at roundabouts, but the crash rate (per road section) was higher at roundabouts, where mind wandering was least likely to be reported. These findings suggest that although drivers' minds wander constantly, driving focus is commanded in demanding situations and in response to the actions of other road users. While mind wandering is ubiquitous, drivers are least likely to report mind wandering at locations showing the highest crash rates. More work is needed to test these findings and to provide direction for road safety interventions.
       
  • Night-time driving visibility associated with LED streetlight dimming
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Joanne M. Wood, Gillian Isoardi, Alex Black, Ian Cowling New LED streetlighting designs and dimming are being introduced worldwide, however, while their cost savings are well established, their impact on driving performance has received little attention. This study investigated the effect of streetlight dimming on night-time driving performance. Participants included 14 licensed drivers (mean age 34.2 ± 4.9 years, range 27–40 years) who drove an instrumented vehicle around a closed circuit at night. Six LED streetlights were positioned along a 250 m, straight section and their light output varied between laps (dimming levels of 25%, 50%, 75% and 100% of maximum output; L25, L50, L75 and L100 respectively; at 100% average road surface luminance of 1.14 cd/m2). Driving tasks involved recognition distances and reaction times to a low contrast, moving target and a pedestrian walking at the roadside. Participants drove at an average driving speed of 55 km/hr in the streetlight zone. Streetlight dimming significantly delayed driver reaction times to the moving target (F3,13.06 = 6.404; p = 0.007); with an average 0.4 s delay in reaction times under L25 compared to L100, (estimated reduction in recognition distances of 6 m). Pedestrian recognition distances were significantly shorter under dimmed streetlight levels (F3,12.75 = 8.27; p = 0.003); average pedestrian recognition distances were 15 m shorter under L25 compared to L100, and 11 m shorter under L50 compared to L100. These data suggest that streetlight dimming impacts on driver visibility but it is unclear how these differences impact on safety; future studies are required to inform decisions on safe dimming levels for road networks.
       
  • A comparison of bus passengers’ and car drivers’ valuation of casualty
           risk reductions in their routes
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Stefan Flügel, Knut Veisten, Luis I. Rizzi, Juan de Dios Ortúzar, Rune Elvik IntroductionThe economic value of safety represents an important guide to transport policy, and more studies on individuals’ valuation of road safety are called for. This paper presents a stated preference study of the value of preventing fatal and serious injuries involving bus passengers and car drivers in road accidents.ObjectivesFormer valuation studies based on travel behaviour and route choice have involved primarily car drivers. Our study also included bus passengers, thus providing a comparison of two types of transport mode users. Moreover, the comparison was based on two different valuation methods.MethodologyAbout 600 bus passengers and nearly 2300 car users from different areas of Norway reported a recent trip, described by its distance and travel cost. Then they answered stated choice tasks that took a reference in the reported trip and involved trade-offs among travel time, fatal and seriously injured victims and travel costs. Afterwards, they faced a simple trade-off between travel costs, and fatal and seriously injured victims.FindingsPooling the data from the two stated preference formats, we derived values of a statistical life and of a statistical seriously injured victim. Regarding the value of statistical life, our point estimates were NOK 45.5 million and NOK 58.3 million for bus users and car users respectively.DiscussionThe point estimates for bus passengers and car users were not statistically different given their confidence intervals. Thus, we recommend the use of a single value, identical for both modes of transport, for the prevention of a statistical fatality as well as for a statistical injury
       
  • Situational influences on response time and maneuver choice: Development
           of time-critical scenarios
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Matthias Powelleit, Mark Vollrath Findings concerning drivers’ response times to sudden events vary considerably across studies due to different experimental setups and situational characteristics, such as expectancy of an event and urgency to react. While response times are widely reported in the literature, understanding of drivers’ choice of maneuvers in time-critical situations is limited. Standardized test scenarios could enhance the comparability of studies and help in attaining a better understanding of driver behavior in these situations.In an effort to achieve these improvements, three driving simulator studies (N = 131) were conducted to investigate drivers’ response time and maneuver choice under a range of situational conditions. Each study took place in a specific environmental setting (urban, rural, and highway) and incorporated one unexpected and 12 subsequent events (increased expectancy). Four different time-critical scenarios were used to evoke different driver responses. In three scenarios, obstacles suddenly entered the roadway (braking, steering, or both possible). A fourth scenario comprised the sudden braking of a leading vehicle (only braking possible). Half of the drivers performed a cognitive secondary task. To validate the findings, results from an additional field test (N = 14) were compared to the results from the simulated urban environment.As expected, response choice was influenced by scenario characteristics (available braking distance and room for evasive maneuvers). Braking maneuvers were more frequent in settings with lower speed limits (urban) while steering maneuvers were found at higher speed limits (highway). Responses to suddenly appearing obstacles were fastest in the urban setting at 540–680 ms; these responses were 200–300 ms slower in the rural and highway settings. Response times increased by 100–200 ms when drivers responded to braking leading vehicles rather than obstacles. Braking responses were 200–350 ms slower and steering responses were 90–200 ms slower when drivers responded to an unexpected event rather than subsequent events. The cognitive secondary task had no significant effect. The simulated environment and the field test produced comparable response behavior.The current study provides reference numbers that help to establish a set of standardized test scenarios for future studies. On basis of this study, nine scenarios are recommended for the context of time-critical crash avoidance maneuvers. Such standardized test scenarios could improve the comparability of future studies on response time and maneuver choice.
       
  • Exploring patterns of child pedestrian behaviors at urban intersections
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Victoria Gitelman, Sharon Levi, Roby Carmel, Anna Korchatov, Shalom Hakkert Children are more vulnerable as pedestrians due to their cognitive, physical and behavioral traits. However, walking is one of the main forms of travel for children, particularly during leisure hours. Child pedestrian injury primarily occurs in urban areas, with a significant share at crosswalks. This study observed child pedestrian behaviors at crosswalks of urban intersections aiming to characterize their behavior patterns and identify risk factors that may lead to injury. Crossing behaviors of children and adolescents up to age 18, during leisure hours, were video-recorded at 29 crosswalks, on signalized and un-signalized intersections situated on collector roads. Some children used pedestrian crosswalks while riding a bicycle or other non-motorized means; they were also included in the sample. Behaviors of 2930 young road users were encoded and compared by age groups. Multivariate logistic regression models were adjusted to identify factors associated with crossing on red and with non-checking vehicle traffic at un-signalized crosswalks. The findings pointed to different behavior patterns for the various child age groups. Risk-taking behaviors are higher for older children; adolescents aged 14–17 cross more on red, without checking traffic, outside crosswalk boundaries and while distracted. At all types of sites, a fifth of children over the age of 9 crossed by riding, the probability of crossing on red and of non-checking traffic prior to crossing at an un-signalized crosswalk was higher for children riding an electric bicycle or kick-scooter. The non-checking of traffic was also higher when a child is distracted by a mobile phone or other electronic gadget, or carries a big object. Children under age 9 were usually accompanied by adults but still exhibited risk-taking behaviors that apparently mirrored those of the adults. Risk-taking behaviors of young road users should be taken into account in the development of injury prevention programs focusing on child and parent education and training, and by adapting the urban environment to better meet their needs.
       
  • Reducing intercity bus crashes through driver rescheduling
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Shuo-Yen Wang, Kun-Feng Wu Intercity bus crashes often involve driver fatigue, which itself is usually the result of sleep deprivation, long driving hours, a maladjusted circadian rhythm, or some combination of the above. And driver scheduling has long been suspected as the root cause affecting sleepiness and fatigue. As such, a fundamental question for intercity bus carriers is how to reduce crashes associated with driver schedules, while maintaining a nonstop service' This research seeks to develop a paradigm to minimize overall fleet crash risk by rescheduling. In this study, we first identified those driving schedules associated with the highest crash risks, and a rescheduling scheme is then proposed to reduce fleet crashes overall. A case-study approach was employed to identify driver scheduling associated with higher crash risk, and a mathematical program was then formulated to minimize fleet crash risk. Our results showed that several types of driver schedules would lead to higher crash risk; for example: (1) working in the afternoon or early hours in the morning for two consecutive days; and (2) commencing a driving shift in the mornings, the afternoon or the early hours of the morning after being off-duty for more than 24 h. To meet the challenge of maintaining a nonstop service while simultaneously minimizing the crash risk associated with these risk patterns, a mathematical program was developed, and it was found that rescheduling based on our algorithm could reduce the incidence of crashes by approximately 30 percent.
       
  • Associations between upper extremity injury patterns in side impact motor
           vehicle collisions with occupant and crash characteristics
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): Mireille E. Kelley, Jennifer W. Talton, Ashley A. Weaver, Andrew O. Usoro, Eric R. Barnard, Anna N. Miller IntroductionSide impact motor vehicle collisions (MVC) represent a significant burden of mortality and morbidity caused by automotive injury within the United States. The objective of this study was to evaluate the relationship between upper extremity (UE) injury patterns and contact sources in side impact MVC with occupant and crash variables.MethodsCrash Injury Research and Engineering Network data obtained from 1998 to 2012 were used to evaluate UE injuries in side impact crashes. First row drivers and passengers that were at least 16 years old with complete crash information were included. Side impact crashes were defined to have an area of deformation to the side of the vehicle and a principal direction of force between 60° and 120° or 240° and 300°. Injuries were stratified by type, anatomic location, and Abbreviated Injury Scale (AIS) severity. Occupant variables included age, sex, height, weight, body mass index, and Injury Severity Score. Vehicle and crash variables included in the analysis were change in vehicle velocity at the time of impact, maximum door intrusion, maximum B-pillar intrusion, seat track position, belt use, vehicle type, impact type, and injury source. Statistical analysis of the UE injury data included descriptive statistics, linear regression analyses with occupant variables, and logistic regression analyses with vehicle and crash variables.ResultsThere were 903 UE injuries among 408 case occupants. The most common injury type was soft tissue injury (72.5%). The majority of fractures were proximal to and including the humerus (70.3%) with the clavicle being the most common fracture location (N = 89). AIS 2+ UE injuries were associated with a significantly higher mean occupant Injury Severity Score than AIS 1 UE injuries (p = 0.01). Contact with the door was the leading cause of UE injury (34.2%). The odds (OR [95% confidence interval], p-value) of an AIS 2+ UE injury due to contact with the B-pillar (5.3 [3.1, 9.1],
       
  • Who is responsible for global road safety' A cross-cultural comparison
           of Actor Maps
    • Abstract: Publication date: January 2019Source: Accident Analysis & Prevention, Volume 122Author(s): R.C. McIlroy, K.A. Plant, M.S. Hoque, W. Jianping, G.O. Kokwaro, N.H. Vũ, N.A. Stanton The traditional three ‘E’s approach to road safety (engineering, education, enforcement) has had, and will continue to have, a significant impact on road traffic casualty rates worldwide. Nevertheless, with rising motorisation in many countries, global fatality numbers have changed little over the past decade. Following calls for the application of sociotechnical systems thinking to the problem, we widen the road safety discussion with an additional four ‘E’s; economics, emergency response, enablement, and, the umbrella term for the approach taken, ergonomics. The research presents an application of Rasmussen’s Risk Management Framework to the road safety systems of five distinct nations; Bangladesh, China, Kenya, the UK, and Vietnam. Following site visits, reviews of literature, and interviews with subject matter experts in each of the countries, a series of Actor Map models of the countries’ road safety systems were developed. These are compared and discussed in terms of the wide variety of interconnecting organisations involved, their influences on road safety outcomes, the differences between nations, and the need to look beyond road users when designing road safety interventions.
       
  • Bayesian approach to model pedestrian crashes at signalized intersections
           with measurement errors in exposure
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): S.Q. Xie, Ni Dong, S.C. Wong, Helai Huang, Pengpeng Xu This study intended to identify the potential factors contributing to the occurrence of pedestrian crashes at signalized intersections in a densely populated city, based on a comprehensive dataset of 898 pedestrian crashes at 262 signalized intersections during 2010–2012 in Hong Kong. The detailed geometric design, traffic characteristics, signal control, built environment, along with the vehicle and pedestrian volumes were elaborately collected. A Bayesian measurement errors model was introduced as an alternative method to explicitly account for the uncertainties in volume data. To highlight the role played by exposure, models with and without pedestrian volume were estimated and compared. The results indicated that the omission of pedestrian volume in pedestrian crash frequency models would lead to reduced goodness-of-fit, biased parameter estimates, and incorrect inferences. Our empirical analysis demonstrated the existence of moderate uncertainties in pedestrian and vehicle volumes. Six variables were found to have a significant association with the number of pedestrian crashes at signalized intersections. The number of crossing pedestrians, the number of passing vehicles, the presence of curb parking, and the presence of ground-floor shops were positively related with pedestrian crash frequency, whereas the presence of playgrounds near intersections had a negative effect on pedestrian crash occurrences. Specifically, the presence of exclusive pedestrian signals for all crosswalks was found to significantly reduce the risk of pedestrian crashes by 43%. The present study is expected to shed more light on a deeper understanding of the environmental determinants of pedestrian crashes.
       
  • Gaze doesn’t always lead steering
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Esko Lehtonen, Otto Lappi, Noora Koskiahde, Tuomas Mansikka, Jarkko Hietamäki, Heikki Summala In car driving, gaze typically leads the steering when negotiating curves. The aim of the current study was to investigate whether drivers also use this gaze-leads-steering strategy when time-sharing between driving and a visual secondary task.Fourteen participants drove an instrumented car along a motorway while performing a secondary task: looking at a specified visual target as long and as much as they felt it was safe to do so. They made six trips, and in each trip the target was at a different location relative to the road ahead. They were free to glance back at the road at any time. Gaze behaviour was measured with an eye tracker, and steering corrections were recorded from the vehicle’s CAN bus. Both in-car ‘Fixation’ targets and outside ‘Pursuit’ targets were used.Drivers often used a gaze-leads-steering strategy, glancing at the road ahead 200–600 ms before executing steering corrections. However, when the targets were less eccentric (requiring a smaller change in glance direction relative to the road ahead), the reverse strategy, in which glances to the road ahead followed steering corrections with 0–400 ms latency, was clearly present. The observed use of strategies can be interpreted in terms of predictive processing: The gaze-leads-steering strategy is driven by the need to update the visual information and is therefore modulated by the quality/quantity of peripheral information. Implications for steering models are discussed.
       
  • Full Bayesian conflict-based models for real time safety evaluation of
           signalized intersections
    • Abstract: Publication date: Available online 5 October 2018Source: Accident Analysis & PreventionAuthor(s): Mohamed Essa, Tarek Sayed Existing advanced traffic management and emerging connected vehicles (CVs) technology can generate considerable amount of data on vehicle positions and trajectories. This data can be used for real-time safety optimization of intersections. To achieve this, it is essential to first understand how changes in signal control affect safety in real-time. This paper develops conflict-based safety performance functions (SPFs) of signalized intersections at the cycle level using multiple traffic conflict indicators. The developed SPFs relate various dynamic traffic parameters to the number of rear-end conflicts at the signal cycle. The traffic parameters included: queue length, shock wave speed and area, and the platoon ratio. The Time-to-Collision, the Modified-Time-to-Collision, and the Deceleration Rate to Avoid the Crash were used as traffic conflict indicators. Traffic video-data collected from six signalized intersections was used in the analysis. The SPFs were developed using the Full Bayesian approach to address the unobserved heterogeneity and the variation among different sites. Overall, the results showed that all the developed SPFs have good fit with all explanatory variables being statistically significant. Also, the highest conflict frequency was noticed at the beginning of the green time, while the highest conflict severity was noticed at the beginning of the red time. Lastly, the results can be used most beneficially in real-time safety optimization of signalized intersection.
       
  • Before-after safety analysis using extreme value theory: A case of
           left-turn bay extension
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Lai Zheng, Tarek Sayed, Ahmed Tageldin There is growing interest in the use of traffic conflicts in before and after safety evaluations because of well-recognized quality and quantity problems associated with historical crash records. Most of these studies apply statistical techniques to compare the number of conflicts before and after the implementation of safety countermeasures. However, to identify the number of conflicts, a specific threshold for various conflict indicators needs to be used and the results of the evaluation can vary significantly depending on the selection of this threshold. As well, there is an issue with how to account for conflict severity in the evaluation. This study proposes adopting the extreme value theory approach to overcome these two issues. The approach was applied to a case of left-turn bay extension at three signalized intersections, and the automated traffic conflict technique was used to identify conflicts with TTC values from the video data collected from treatment sites and matching control sites. Generalized extreme value (GEV) models with different covariates were developed and compared. The results show that there are apparent shape change in the GEV distribution (i.e., from narrow peak up to high severities to wide spread with fewer conflicts at high severity levels) after the treatment, indicating reduction in conflict severity. The safety improvement is further confirmed by the total reduction of 63.9% in estimated crashes. Moreover, with the aid of GEV model, the most severe conflicts that are also rare and random are included into the OR calculation, and a significant reduction of 73.2% is found in the estimated most severe conflicts.
       
  • Transitions within a safe road system
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Samuel G. Charlton, Nicola J. Starkey As drivers move through the road transport system they are exposed to a range of different situations and road conditions in a relatively short space of time. Drivers’ expectations about what will happen on different types of roads have strong effects on their speed choices, and where they look and what they attend to. As a result it is important to assist drivers to change their expectations when they transition from one road type to another. In this experiment we investigated the effectiveness of different centreline road markings in preparing for a horizontal curve as drivers moved from a motorway to a two-lane rural country road. Fifty individuals were recruited to participate in a video-based simulated driving task to compare three centreline marking types in terms of their effects on speed choice and reactions to a driving hazard (horizontal curve). Although a complex marking previously associated with high risk produced the largest speed reductions during the transition from the motorway, it was the centreline more traditionally associated with rural country roads (dashed white centreline) that was associated with the best hazard reactions post-transition (brake reaction time and speed reduction before a horizontal curve). The findings demonstrated that the look of a road needs to convey a clear and unambiguous message to drivers. The transition to a two-star rural road is best achieved by making the road look like a typical two-star road as soon as possible.
       
  • A novel method of vehicle-pedestrian near-crash identification with
           roadside LiDAR data
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Jianqing Wu, Hao Xu, Yichen Zheng, Zong Tian Safety evaluation based on historical crashes usually has a lot of limitations. In previous studies, near-crashes are considered as surrogate data for safety evaluation. One challenge for the use of near-crashes data is the difficulty of data collection. The driving simulators and naturalistic driving data may not be suitable for safety evaluation at specific sites. The observational site-based methods such as human observers and video analysis also suffer from some limitations such as long time data processing or reduced performance influenced by weather or light condition. The roadside Light Detection and Ranging (LiDAR)-enhanced infrastructure provides a new solution for real-time data collection without the impact from weather or light. The high-resolution trajectories of all road users can be obtained from roadside LiDAR data. This paper aims to fill these gaps by presenting a method for near-crash identification based on the trajectories of road users extracted from roadside LiDAR data. This paper focused on vehicle-pedestrian near-crash identification particularly considering the increased risk of vehicle-pedestrian conflicts. Three parameters: Time Difference to the Point of Intersection (TDPI); Distance between Stop Position and Pedestrian (DSPP); Vehicle-pedestrian speed-distance profile, were developed for vehicle-pedestrian near-crash identification. The authors also recommended the thresholds for risk assessment of pedestrian safety. This method was coded into an automatic procedure for near-crash identification. This method is expected to significantly improve the current evaluation of pedestrian safety.
       
  • Boundary crash data assignment in zonal safety analysis: An iterative
           approach based on data augmentation and Bayesian spatial model
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Xiaoqi Zhai, Helai Huang, Mingyun Gao, Ni Dong, N.N. Sze Boundary effect refers to the issue of ambiguous allocation of crashes occurred on or near the boundaries of neighboring zones in zonal safety analysis. It results in bias estimates for associate measure between crash occurrence and possible zonal factors. It is a fundamental problem to compensate for the boundary effect and enhance the model predictive performance. Compared to conventional approaches, it might be more reasonable to assign the boundary crashes according to the crash predisposing agents, since the crash occurrence is generally correlated to multiple sources of risk factors. In this study, we proposed a novel iterative aggregation approach to assign the boundary crashes, according to the ratio of model-based expected crash number in adjacent zones. To verify the proposed method, a case study using a dataset of 738 Traffic Analysis Zones (TAZs) from the county of Hillsborough in Florida was conducted. Using Bayesian spatial models (BSMs), the proposed approach demonstrated the capability in reasonably compensating for the boundary effect with better model estimation and predictive performance, as compared to three conventional approaches (i.e., half and half ratio method, one to one ratio method, and exposure ratio method). Results revealed that several factors including the number of intersections, road segment length with 35 mph speed limit, road segment length with 65 mph speed limit and median household income, were sensitive to the boundary effect.
       
  • Impacts of speed variations on freeway crashes by severity and vehicle
           type
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Pushpa Choudhary, Marianna Imprialou, Nagendra R. Velaga, Alok Choudhary Speed variations are identified as potentially important predictors of freeway crash rates; however, their impacts on crashes are not entirely known. Existing findings tend to be inconsistent possibly because of the different definitions for speed variations, different crash type consideration or different modelling and data aggregation approaches. This study explores the relationships of speed variations with crashes on a freeway section in the UK. Crashes split by vehicle type (heavy and light vehicles) and by severity mode (killed/serious injury and slight injury crashes) are aggregated based on the similarities of the conditions just before their occurrence (condition-based approach) and modelled using Multivariate Poisson lognormal regression. The models control for speed variations along with other traffic and weather variables as well as their interactions. Speed variations are expressed as two separate variables namely the standard deviations of speed within the same lane and between-lanes over a five-minute interval. The results, similar for all crash types (by coefficient significance and sign), suggest that crash rates increase as the within lane speed variations raise, especially at higher traffic volumes. Higher speeds coupled with greater volume and high between-lanes speed variation also increase crash likelihood. Overall, the results suggest that specific combinations of traffic characteristics increase the likelihood of crash occurrences rather than their individual effects. Identification of these specific crash prone conditions could improve our understanding of crash risk and would support the development of more efficient safety countermeasures.
       
  • Traffic crash analysis with point-of-interest spatial clustering
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Ruo Jia, Anish Khadka, Inhi Kim This paper presents a spatial clustering method for macro-level traffic crash analysis based on open source point-of-interest (POI) data. Traffic crashes are discrete and non-negative events for short-time evaluation but can be spatially correlated with long-term macro-level estimation. Thus, the method requires the evaluation of parameters that reflect spatial properties and correlation to identify the distribution of traffic crash frequency. A POI database from an open source website is used to describe the specific land use factors which spatially correlate to macro level traffic crash distribution. This paper proposes a method using kernel density estimation (KDE) with spatial clustering to evaluate POI data for land use features and estimates a simple regression model and two spatial regression models for Suzhou Industrial Park (SIP), China. The performance of spatial regression models proves that the spatial clustering method can explain the macro distribution of traffic crashes effectively using POI data. The results show that residential density, and bank and hospital POIs have significant positive impacts on traffic crashes, whereas, stores, restaurants, and entertainment venues are found to be irrelevant for traffic crashes, which indicate densely populated areas for public services may enhance traffic risks.
       
  • “Seatbelts don’t save lives”: Discovering and targeting the
           attitudes and behaviors of young Arab male drivers
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Susan Dun, Amal Zeyad Ali The paper presents a two-part study that discovered then targeted beliefs and attitudes towards seatbelt use in young Arab men. The purpose of part one was to discover their safe driving beliefs, attitudes and behaviors as well as their responses to safe driving campaigns to ascertain message elements that could incite reactance. Part two targeted selected beliefs and attitudes in a message that was designed based on the results from part one to both address relevant beliefs and attitudes as well as avoid reactance. One belief, that seatbelts are not necessary in the back seat, and two attitudes, avoidance of wearing the seatbelt to prevent clothing from being wrinkled and to avoid friends’ derision, were targeted.Because the participants reported reactance to common safe driving campaigns, the options for the message were quite limited. Using fear appeals, shocking content or depicting the consequences of accidents was deemed likely to be ineffective, rather a novel approach was called for. Utilizing the collectivist and masculine nature of the culture, the resulting message featured a group of young Arab men who are convinced by a personified Seatbelt to wear their seatbelts after an adventure. The message succeeded in eliciting statistically reliable belief and attitudinal change on all three dependent variables after one exposure, suggesting that tailored messages that avoid triggering reactance and are culturally contextualized while aimed at specific beliefs and attitudes can be persuasive. Although risk taking behavior can result from group pressure, our message used culturally specific group pressure but depicted it as being against the risky behavior and positively reinforced the less risky behavior, demonstrating that such approaches can be effective. The film was not a typical safe driving message, utilized social norms from the target audience and was carefully matched to their attitudes and beliefs while not being an overtly persuasive. We argue that message campaigners can utilize both the method and results for subsequent campaigns aimed at young Arab men.
       
  • A discrete mixture regression for modeling the duration of
           non-hospitalization medical leave of motor accident victims
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Lluís Bermúdez, Dimitris Karlis, Miguel Santolino Studies analyzing the temporary repercussions of motor vehicle accidents are scarcer than those analyzing permanent injuries or mortality. A regression model to evaluate the risk factors affecting the duration of temporary disability after injury in such an accident is constructed using a motor insurance dataset. The length of non-hospitalization medical leave, measured in days, following a motor accident is used here as a measure of the severity of temporary disability. The probability function of the number of days of sick leave presents spikes in multiples of five (working week), seven (calendar week) and thirty (month), etc. To account for this, a regression model based on finite mixtures of multiple discrete distributions is proposed to fit the data properly. The model provides a very good fit when the multiples for the working week, week, fortnight and month are taken into account. Victim characteristics of gender and age and accident characteristics of the road user type, vehicle class and the severity of permanent injuries were found to be significant when accounting for the duration of temporary disability.
       
  • Influence of cyber-attacks on longitudinal safety of connected and
           automated vehicles
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Ye Li, Yu Tu, Qi Fan, Changyin Dong, Wei Wang Connected and automated vehicle (CAV) has been a remarkable focal point in recent years, since it is recognized as a potential method to reduce traffic congestion, emission and accident. However, the connectivity function makes CAVs vulnerable to cyber-attacks. An intuitive method to defend cyber-attacks on CAVs is that if the error between expected and measured behaviors exceeds a predetermined threshold, a security scheme should be activated. This study investigates another type of cyber-attack, denoted as slight attacks, in which the communicated data of CAVs are randomly deviated from the actual ones and deviations do not exceed the threshold. The primary objective is to evaluate the influence of slight cyber-attacks on longitudinal safety of CAVs. An empirical CAV model is first utilized to describe vehicle dynamics and generate trajectory data. A rear-end collision risk index (RCRI) derived from safe stopping distance is used to establish relation between longitudinal safety and trajectory data. Two attacked factors, communicated positions and speeds from preceding vehicles are tested. Extensive simulations are conducted and parameters are also tested via sensitivity analysis. Results indicate that (1) when one CAV is under slight cyber-attacks, it is more dangerous if communicated positions are attacked than speeds; (2) when multi CAVs are under attacked, it is possible that a situation with more vehicles under attack at a low severity may be more dangerous than that with fewer vehicles but under attack at a high severity; (3) the impact of slight cyber-attacks on deceleration period is more serious compared to acceleration period. The findings of this study provide useful suggestion for defending cyber-attacks on CAVs and improving longitudinal safety in the future.
       
  • Modelling driver acceptance of driver support systems
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Md Mahmudur Rahman, Lesley Strawderman, Mary F. Lesch, William J. Horrey, Kari Babski-Reeves, Teena Garrison Driver support systems are intended to enhance driver performance and improve transportation safety. Even though these systems afford safety advantages, they challenge the traditional role of drivers in operating vehicles. Driver acceptance, therefore, is essential for the adoption of new in-vehicle technologies into the transportation system. In this study, a model of driver acceptance of driver support systems was developed. A conceptual driver acceptance model, including several components, was proposed based on a review of current literature. An empirical study was subsequently carried out using an online survey approach. The study collected data on participants’ perceptions of two driver support systems (a fatigue monitoring system and an adaptive cruise control system combined with a lane-keeping system) in terms of attitude, perceived usefulness, and other components of driver acceptance. Results identified five components of driver acceptance (attitude, perceived usefulness, endorsement, compatibility, and affordability). The results also confirmed several mediating effects. The developed model was able to explain 85% of the variability in driver acceptance. The model provides an improved understanding how driver acceptance is formed, including which factors affect driver acceptance and how they affect it. The model can also help automakers and researchers to assess the design and estimate the potential use of a driver support system. The model could also be highly beneficial in developing a questionnaire to assess driver acceptance.
       
  • Comparing road safety performance across countries: Do data source and
           type of mortality indicator matter'
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Xunjie Cheng, Yue Wu, Peishan Ning, Peixia Cheng, David C. Schwebel, Guoqing Hu This study examined the impact of data source estimates (World Health Organization (WHO) versus Global Burden of Disease (GBD)) and the type of mortality indicator (population-based versus exposure-based mortality) on road safety performance evaluation. Data were derived from WHO publications and the GBD results tool, and we calculated mortality rate ratio (MRR) and differences in country ranking between the two data sources, plus differences in country rankings and in mortality changes between 2010 and 2013 for population-based and vehicle-based mortality. Of 172 countries in both datasets, 32 countries (19%) had low consistency across the two data sources (MRR ≤ 0.49 or ≥1.51). Using population-based mortality data to rank the 172 countries, 77 (45%) had ≥ 20 position difference between the two data sources. Population-based vs. vehicle-based mortality data yielded ≥ 20 position difference in 33 countries for WHO estimates and 42 for GBD estimates. Among the 80 countries having comparable population-based and vehicle-based GBD mortality rates over time, 9 countries displayed opposite changing directions – that is, the change increased in one mortality indicator but decreased in the other indicator between 2010 and 2013. Data source and type of mortality indicators yield a substantial impact on ranking road safety performance across countries, as they are widely used for decision-making by global and national policy-makers and injury researchers. The differences between WHO and GBD estimates may arise from inconsistencies in data input and estimation models. Exposure-based indicators should be preferred in road safety evaluation when data are available. Advanced research is needed to interpret large country variations in road traffic mortality and mortality progress and to develop strategies to narrow the gaps across countries.
       
  • Adapting artificial neural networks to a specific driver enhances
           detection and prediction of drowsiness
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Charlotte Jacobé de Naurois, Christophe Bourdin, Clément Bougard, Jean-Louis Vercher Monitoring car drivers for drowsiness is crucial but challenging. The high inter-individual variability observed in measurements raises questions about the accuracy of the drowsiness detection process. In this study, we sought to enhance the performance of machine learning models (Artificial Neural Networks: ANNs) by training a model with a group of drivers and then adapting it to a new individual. Twenty-one participants drove a car simulator for 110 min in a monotonous environment. We measured physiological and behavioral indicators and recorded driving behavior. These measurements, in addition to driving time and personal information, served as the ANN inputs. Two ANN-based models were used, one to detect the level of drowsiness every minute, and the other to predict, every minute, how long it would take the driver to reach a specific drowsiness level (moderately drowsy). The ANNs were trained with 20 participants and subsequently adapted using the earliest part of the data recorded from a 21st participant. Then the adapted ANNs were tested with the remaining data from this 21st participant. The same procedure was run for all 21 participants. Varying amounts of data were used to adapt the ANNs, from 1 to 30 min, Model performance was enhanced for each participant. The overall drowsiness monitoring performance of the models was enhanced by roughly 40% for prediction and 80% for detection.
       
  • Risk perception during urban cycling: An assessment of crowdsourced and
           authoritative data
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Rul von Stülpnagel, Jakub Krukar Subjective risk perception during urban cycling has been mostly investigated through questionnaire studies. However, newly available data sources promise extended possibilities for the investigation and understanding of the underlying factors. We validate the rationale for using both opportunistically available crowd-sourced data (i.e., volunteered geographic information or VGI) as well as more established but rarely investigated authoritative data as predictors of subjective cycling risk. We achieve this by correlating indicators of cycling risk extracted from both VGI and authoritative data for two different German cities with participants’ risk estimates assessed in laboratory-based virtual reality experiments. In Case 1, 15 participants (mostly undergraduate students with a mean age of 22 years old; nine of them females) were tested as a sample representing frequent and experienced cyclists, but unfamiliar with the 19 tested locations and less likely to be affected by the virtual reality setup. In Case 2, 24 new participants (mostly undergraduate students; mean age 24 years; 13 of them females) were experienced cyclists and mostly familiar with the 40 test locations located in their city of residence. For both cases, our findings provide evidence that parameters extracted from VGI (e.g., the semantic severity of the contribution and the reception by other citizens) as well as from authoritative data sources (e.g., accident statistics or Space Syntax measures) represent valid indicators for the subjectively perceived risk of cycling at a specific location. On the basis of this validation, future research can use these data sources to investigate the sources of risk perception during urban cycling in greater detail.
       
  • Do the benefits outweigh the costs' Societal benefit-cost analysis of
           three large truck safety technologies
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Matthew C. Camden, Alejandra Medina-Flintsch, Jeffrey S. Hickman, Richard J. Hanowski, Brian Tefft Although research has found advanced safety technologies to be effective at preventing large truck crashes, limited empirical data exists regarding their cost effectiveness to the U.S. society. Without these data, carriers are hesitant to adopt costly technologies and government agencies are hesitant to create regulation mandating their use. The objective of this study was to provide scientifically-based estimates of the societal benefits and costs of large truck automatic emergency braking (AEB), lane departure warning (LDW), and video-based onboard safety monitoring (OSM). For each technology, benefit-cost analyses were performed for installing the technology on all large trucks (including retrofitting existing trucks) and for equipping new large trucks only. Sensitivity analyses examined three cost estimates (low, average, high; values technology-specific), two estimates of system efficacy (low and high; values technology-specific), and three discount rates (0%, 3%, 7%) for each technology. Equipping trucks with LDW and video-based OSM systems were found to be cost effective for all combinations of costs, efficacy, and discount rates examined, for both new and existing trucks. Results for AEB and were mixed. Only a $500 AEB system was cost effective when equipping new trucks and retrofitting existing trucks. However, all cost estimates were cost effective with a 28% efficacy rate when only equipping new large trucks. Overall, these data suggested all three technologies can be cost-effective for new large trucks provided the current costs and efficacy rates can be maintained or improved upon.
       
  • Employee safety single vs. dual priorities: When is the rate of
           work-related driving accidents lower'
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Ron Aaron Malka, Shalhevet Leibovitz-Zur, Eitan Naveh Applying both occupational safety and ambidexterity theories, we investigate which situation in organizations leads to a lower number of work-related road accidents: a single-priority situation focused on road safety, or a dual-priority situation in which both road safety and customer service are priorities. Occupational safety theory puts forward an ‘either-or’ approach in which employee safety must be the first priority, above and beyond all others. In contrast, the ambidexterity theory’s ‘both-and’ approach suggests a simultaneous coexistence of priorities. Results from forty-three units in three organizations that make intensive use of work-related driving and aim to deliver good customer service are described. The results suggest that when the level of customer service priority was low, an increase in the level of road safety priority significantly decreased the number of road accidents. However, when the level of customer service priority was high, an increase in the level of road safety priority was not associated with less road accidents. The results show that work-related road accidents would be lower in a safety-first, single-priority situation compared to a dual-priority situation encompassing both road safety and customer service. We discuss the theoretical and practical implications of these results.
       
  • The relationship between the demographic, personal, and social factors of
           Malaysian motorcyclists and risk taking behavior at signalized
           intersections
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Muhamad Nazri Borhan, Ahmad Nazrul Hakimi Ibrahim, Affan Aziz, Muhamad Razuhanfi Mat Yazid In the context of road safety, risk-taking is undoubtedly one of the main contributory factors in road accidents. The actual forces which influence individuals to take such risks, nevertheless, are still not fully understood. To address this, this study was therefore conducted to investigate the relationship of the demographic, personal, and social factors of motorcyclists, with a specific focus on their risk-taking behavior at signalized intersections in Malaysia. This study adopted the quantitative method using cross-sectional questionnaire surveys and involved 251 respondents. The demographic factors were analyzed using the t-test and an ANOVA Scheffe Post-Hoc test, while the motorcyclists’ personal and social characteristics were analyzed with multiple linear regression. The findings indicate that the individuals who were greater risk takers at signalized intersections were teenage motorcyclists (16–25 years old) who had finished their education before taking their high school diploma, and who also received a lower than average monthly income from private sector firms. The actual experience of accidents was also shown to be positively related to this risk-taking behavior. In addition, in term of personal and social factors, results showed that, for these individuals, there was a significant difference between the strength of peer influence and that of parental and spouse guidance. However, there was no significant difference in the risk-taking behavior of Malaysian motorcyclists riding at signalized intersections for the following factors: between genders, in terms of accident involvement, in terms of enforcement of traffic regulations, and prevention steps and confidence level after being involved in an accident.
       
  • The effect of gender, occupation and experience on behavior while driving
           on a freeway deceleration lane based on field operational test data
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Nengchao Lyu, Yue Cao, Chaozhong Wu, Jin Xu, Lian Xie Deceleration lanes improve traffic flow by reducing interference, increasing capacity and enhancing safety. However, accident rates are higher on these interchange segments than on other freeway segments. It is important to attempt to reduce traffic accidents on these interchange segments by further exploring the behavior of different types of drivers on a highway deceleration lane. In this study, with field operational test (FOT) data from 89 driving instances (derived from 46 participants driving the test road twice) on a typical freeway deceleration lane, section speed profiles, vehicle trajectories, lane position and other key parameters were obtained. The lane-change characteristics and speed profiles of drivers with different genders, occupations and experiences were analyzed. The significant disparities between them reflects the risk associated with different groups of drivers. The study shows that male drivers changed to the outside lane earlier; professional drivers and experienced drivers made the last lane change as early as possible to enter the deceleration lane; and the speed of the vehicles entering the exit ramp was significantly higher than the speed limit. This research work provides ground truth data for deceleration lane design, driver ability training and off-ramp traffic safety management.
       
  • Reducing traffic violations in minority localities: Designing a traffic
           enforcement program through a public participation process
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Roni Factor The current study tests an innovative public participation process for designing and implementing a tailored traffic enforcement program in minority localities. The quasi-experiment used two matched pairs of randomly selected Israeli Arab localities, where one locality in each pair was randomly assigned to the experimental group and the other to the control group. The intervention’s main features were the public participation process and implementation by police of the traffic enforcement program designed during the process. Systematic field observations on 12,236 vehicles in the four localities found a meaningful and significant reduction in traffic violations in the experimental localities following the intervention, while a small increase in violations was observed in the control localities. The most meaningful decline, indicating improvement in drivers’ behavior, was in non-use of seatbelts and small children in the front seat. The study suggests that a public participation process which identifies local road traffic problems and “dark” hot spots (places where offenses and risky behavior recur but might not be known to the police), followed by implementing tailored solutions for these problems, can reduce traffic violations. Future research should aim to separate out the independent effects of the two phases (the public participation process and tailored enforcement).
       
  • The consumer-citizen duality: Ten reasons why citizens prefer safety and
           drivers desire speed
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Niek Mouter, Sander van Cranenburgh, Bert van Wee Cost-benefit analyses for transportation projects usually value impacts on safety and travel time through experiments in which consumers of mobility (‘drivers’) choose between routes which differ in safety and travel time. This approach has been criticized for failing to consider that private choices may not fully reflect citizens’ preferences over public goods and means, a concept known as the consumer-citizen duality. Recent empirical evidence has established that individuals do indeed assign comparatively more value to safety in their role as citizens than in their role as drivers. Our study aims to provide explanations for this finding by presenting four stated choice experiments in which respondents were asked to make choices, both as citizens and as drivers, between routes that differed in travel time and safety. Subsequently, respondents were asked to provide reasons for their choices. We identify five cognitive and five normative explanations. The cognitive explanations suggest that individuals make diverging choices because their perceptions of accident risk differ between the two roles. Drivers will assign a relatively low value to mitigating accident risk because they believe that: (1) such risks are trivial on an individual level; (2) their personal risk is lower than the average risk; (3) their personal risk is controllable; (4) they would not be able to distinguish relative safety levels in real life; and (5) their choices for others are more risk-averse than choices for themselves and, unlike citizens, they are not explicitly evaluating risky choices for others. The normative explanations involve that individuals believe that the government should assign more value to safety compared to individual drivers because: (6) as citizen they are more prone to base their choices on social norms which prescribe risk-averse behaviour in this context; (7) governments have a duty of care concerning the safety of the transportation network; (8) drivers have a relatively high degree of responsibility to reduce their own travel times; (9) governments should account for drivers’ tendencies to choose faster routes by building safer ones; and (10) governments should ensure the safety of the road network because this allows drivers to choose the fastest route without being concerned about the impact of their route choice on accident risk.
       
  • Safety and operational impacts of setting speed limits below engineering
           recommendations
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Vikash V. Gayah, Eric T. Donnell, Zhengyao Yu, Lingyu Li This study quantifies the operational and safety impacts of setting posted speed limits below engineering recommendations using field data from rural roads in Montana. Vehicle operating speeds and historical crash data were collected at multiple sites with posted speed limits set equal to engineering recommendations and sites with posted speed limits set lower than engineering recommendations. Linear, quantile and logistic regression models were estimated to predict mean operating speed, 85th percentile operating speed and speed limit compliance, respectively, as a function of various roadway characteristics and level of speed enforcement. The Empirical-Bayes before-after approach was also used to develop crash modification factors (CMFs) that describe the expected change in total and fatal + injury crash frequency when setting posted speed limits lower than engineering recommendations. Because safety data were collected over a long time period, temporal adjustments were incorporated to account for yearly changes in crash reporting, traffic characteristics and other variables. The results revealed that speed limit compliance worsened as the difference between the engineering recommended and posted speed limits increased. The presence of verified heavy police enforcement reduced both mean and 85th-percentile operating speeds by approximately 4 mph and increased speed limit compliance. The safety analysis found a statistically significant reduction in total, fatal + injury, and property damage only (PDO) crash frequency at locations with posted speed limits set 5 mph lower than engineering recommendations. Locations with posted speed limits set 10 mph lower than engineering recommendations experienced a decrease in total and PDO crash frequency, but an increase in fatal + injury crash frequency. The safety effects of setting speed limits 15 to 25 mph lower than engineering recommendations were less clear, as the results were not statistically significant, likely due to the small sample of sites included in the evaluation. Overall, the results suggest that setting posted speed limits 5 mph lower than the engineering recommended practice may result in operating speeds that are more consistent with the posted speed limits and overall safety benefits.
       
  • From partial and high automation to manual driving: Relationship between
           non-driving related tasks, drowsiness and take-over performance
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Frederik Naujoks, Simon Höfling, Christian Purucker, Kathrin Zeeb BackgroundUntil the level of full vehicle automation is reached, users of vehicle automation systems will be required to take over manual control of the vehicle occasionally and stay fallback-ready to some extent during the drive. Both, drowsiness caused by inactivity and the engagement in distracting non-driving related tasks (NDRTs) such as entertainment or office work have been suggested to impair the driver’s ability to safely handle these transitions of control. Thus, it is an open question whether engagement in NDRTs will impair or improve take-over performance.MethodIn a motion-based driving simulator, 64 participants completed an automated drive that lasted either one or two hours using either a partially or highly automated driving system. In the partially automated driving condition, a warning was issued after several seconds when drivers took both hands off the steering wheel, while the highly automated driving system allowed hands-off driving permanently. Drivers were allowed to bring along their smartphones and to use them during the drive. They engaged in a wide variety of NDRTs such as reading or using social media. At the end of the session, drivers had to react to a sudden lead vehicle braking event. In the partial automation condition, there was no take-over request (TOR) to notify the drivers of the braking vehicle, while in the highly automated condition, the situation happened right after the drivers had deactivated the automation in response to a TOR. The lead time of the TOR was set at 8 s. Driver’s level of drowsiness, workload (visual, mental and motoric) from carrying out the NDRT and motivational appeal of the NDRT right before the control transition were video-coded and used to predict the outcome of the braking event (i.e., reaction and system deactivation times, minimal Time-to-collision (TTC) and self-reported criticality) with a multiple regression approach.ResultsIn the partial automation condition, reaction times to the braking vehicle and situation criticality as measured by the minimum TTC could be well predicted. Main predictors for increased reaction time were drowsiness and motivational appeal of the NDRT. However, visual and mental demand associated with NDRTs did decrease reaction time, suggesting that the NDRT helped the drivers to maintain alertness during the partially automated drive. Accordingly, drowsiness and motivational appeal of the NDRT increased situation criticality, while cognitive load due to the NDRT decreased it. In the highly automated condition, however, it was not possible to predict system deactivation time (in reaction to the TOR), brake reaction time to the braking vehicle and situation criticality by observed drowsiness and NDRT engagement.DiscussionThe results suggest a relationship between the driver’s drowsiness and NDRT engagement in partial automation but not in highly automated driving. Several explanations for this finding are discussed. It could be possible that the lead time of 8 s might have given the drivers enough time to complete the driver state transition process from executing NDRTs to manual driving, putting them in a position to be able to cope with the driving event, while this was not possible in the partial automation condition. Methodological issues that might have led to a non-detection of an effect of drowsiness or NDRT engagement in the highly automated driving condition, such as the sample size and sensitivity of the observer ratings, are also discussed.
       
  • Multivariate random parameter Tobit modeling of crashes involving aging
           drivers, passengers, bicyclists, and pedestrians: Spatiotemporal
           variations
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Mehmet Baran Ulak, Eren Erman Ozguven, Omer Arda Vanli, Maxim A. Dulebenets, Lisa Spainhour The increase in 65 years and older population in the United States compels the investigation of the crashes involving all aging (65+) roadway users (drivers, passengers, bicyclists, and pedestrians) in order to ensure their safety. As such, the objective of this research is to provide a spatiotemporal comparative investigation of the crashes involving these aging roadway users in Florida via concurrently using the same set of predictors in order to obtain comparable findings among them. First, a new metric, namely Crash Rate Difference (CRD) approach is developed, which enables one to capture potential spatial and temporal (e.g., weekend and weekday) variations in crash rates of aging user-involved crashes. Second, a multivariate random parameter Tobit model is utilized to determine the factors that drive both the crash occurrence probability and the crash rate of 65+ roadway users, accounting for the unobserved heterogeneity. Findings show that there are statistically significant heterogeneous effects of predictors on the crash rates of different roadway users, which evidences the unobserved heterogeneity across observations. Results also indicate that the presence of facilities such as hospitals, religious facilities, or supermarkets is very influential on crash rates of 65+ roadway users, advocating that roadways around these facilities should be particularly scrutinized by road safety stakeholders. Interestingly, the effect of these facilities on crashes also differs significantly between weekdays and weekends. Moreover, the roadway segments with high crash rates vary temporally depending on whether it is a weekday or a weekend. These findings regarding the spatiotemporal variations clearly indicate the need to develop and design better traffic safety measures and plans addressing these specific roadway segments, which can be tailored to alleviate traffic safety problems for 65+ roadway users.
       
  • The effects of personality types on self-reported safety behavior: Focused
           on plant workers in Korea
    • Abstract: Publication date: December 2018Source: Accident Analysis & Prevention, Volume 121Author(s): Lee Jong-Hyun, So Soo-Hyun, Min Seung-Nam, Lee Kyung-Sun We sought to validate a safety behavior tool used in South Korean nuclear power plants, and to investigate the effects of HEXACO personality types on safety behaviors. The participants were 242 individuals employed in corporate safety management who answered the questionnaires on safety behaviors checklist, impulsiveness, affectivity, job burnout, and perfectionism. An exploratory factor analysis was conducted on the safety behavior items, and the convergent and discriminant validity were confirmed through correlational analyses with the existing related variables. To examine the individual effects of personality variables on the validated safety behavior questionnaire, we introduced control variables into a subsequent hierarchical regression analysis. The analyses revealed that the personality variables had significant effects on the subscales of the safety behavior scale. The present study is significant in that it revealed that personality, a broad construct, can predict human errors and safety behaviors, which have had previously been found to associate with only specific variables, such as stress, impulsiveness, and perfectionism.
       
  • Comparison of univariate and two-stage approaches for estimating crash
           frequency by severity—Case study for horizontal curves on two-lane rural
           roads
    • Abstract: Publication date: Available online 1 September 2018Source: Accident Analysis & PreventionAuthor(s): Alireza Jafari Anarkooli, Bhagwant Persaud, Mehdi Hosseinpour, Taha Saleem The Highway Safety Manual (HSM) procedures apply specific safety performance functions (SPFs) and crash modification factors (CMFs) appropriate for estimating the safety effects of design and operational changes to a roadway. Although the applicability of the SPFs and CMFs may significantly vary by crash severity, they are mainly based on total crash counts, with different approaches for estimation of crashes by crash severity. The variety of approaches in the HSM and in the literature in general suggests that there may be no one best approach for all situations, and that there is a need to develop and compare alternative approaches for each potential application. This paper addresses this need by demonstrating the development and comparison of alternative approaches using horizontal curves on two-lane roads as a case study. This site type was chosen because of the high propensity for severe crashes and the potential for exploring a wide range of variables that affect this propensity. To facilitate this investigation, a two-stage modeling approach is developed whereby the proportion of crashes for each severity level is estimated as a function of roadway-specific factors and traffic attributes and then applied to an estimate of total crashes from an SPF. Using Highway Safety Information System (HSIS) curve data for Washington state, a heterogeneous negative binomial (HTNB) regression model is estimated for total crash counts and then applied with severity distribution functions (SDFs) developed by a generalized ordered probit model (GOP). To evaluate the performance of this two-stage approach, a comparison is made with predictions directly obtained from estimated univariate SPFs for crash frequency by severity and also from a fixed proportion method that has been suggested in the HSM. The results revealed that, while the two-stage SDF approach and univariate approach adopt different procedures for model estimation, their prediction accuracies are similar, and both are superior to the fixed proportion method. In short, this study highlights the potential of the two-stage SDF approach in accounting for crash frequency variations by severity levels, at least for curved two-lane road sections, and especially for the all too frequent cases where samples are too small to estimate viable univariate crash severity models.
       
  • Forecasting German crash numbers: The effect of meteorological variables
    • Abstract: Publication date: Available online 18 August 2018Source: Accident Analysis & PreventionAuthor(s): Kevin Diependaele, Heike Martensen, Markus Lerner, Andreas Schepers, Frits Bijleveld, Jacques J.F. Commandeur At the end of each year, the German Federal Highway Research Institute (BASt) publishes the road safety balance of the closing year. They describe the development of accident and casualty numbers disaggregated by road user types, age groups, type of road and the consequences of the accidents. However, at the time of publishing, these series are only available for the first eight or nine months of the year. To make the balance for the whole year, the last three or four months are forecasted. The objective of this study was to improve the accuracy of these forecasts through structural time-series models that include effects of meteorological conditions. The results show that, compared to the earlier heuristic approach, root mean squared errors are reduced by up to 55% and only two out of the 27 different data series yield a modest rise of prediction errors. With the exception of four data series, prediction accuracies also clearly improve incorporating meteorological data in the analysis. We conclude that our approach provides a valid alternative to provide input to policy makers in Germany.
       
  • The European road safety decision support system on risks and measures
    • Abstract: Publication date: Available online 18 August 2018Source: Accident Analysis & PreventionAuthor(s): Heike Martensen, Kevin Diependaele, Stijn Daniels, Wouter Van den Berghe, Eleonora Papadimitriou, George Yannis, Ingrid Van Schagen, Wendy Weijermars, Wim Wijnen, Ashleigh Filtness, Rachel Talbot, Pete Thomas, Klaus Machata, Eva Aigner Breuss, Susanne Kaiser, Thierry Hermitte, Rob Thomson, Rune Elvik The European Road Safety Decision Support System (roadsafety-dss.eu) is an innovative system providing the available evidence on a broad range of road risks and possible countermeasures. This paper describes the scientific basis of the DSS. The structure underlying the DSS consists of (1) a taxonomy identifying risk factors and measures and linking them to each other, (2) a repository of studies, and (3) synopses summarizing the effects estimated in the literature for each risk factor and measure, and (4) an economic efficiency evaluation instrument (E3-calculator). The DSS is implemented in a modern web-based tool with a highly ergonomic interface, allowing users to get a quick overview or go deeper into the results of single studies according to their own needs.
       
  • Validation of the influencing factors associated with traffic violations
           and crashes on freeways of developing countries: A case study of Iran
    • Abstract: Publication date: Available online 9 August 2018Source: Accident Analysis & PreventionAuthor(s): Mansour Hadji Hosseinlou, Alireza Mahdavi, Mehdi Jabbari Nooghabi Among the rural roads, freeways have the maximum allowable speed limit. This subject increases the tendency of drivers to use these kinds of roads, and despite its positive effects, it has caused numerous problems. One of them is the increase in the rate of traffic violations and crashes. The amount of crashes per kilometer in Iran’s freeways is almost twice the other rural roads. Hence, finding a solution to this problem is of particular importance. This research intends to validate some of the influencing factors which cause traffic violations and crashes in freeways and determine their amount of influence through statistical models. For this purpose, the authors considered violations and crashes for 36 road segments as dependent variables and other factors as independent ones. Since dependent variables were count, discrete, and non-zero, the proposed models were Poisson and Zero-truncated Poisson. The processing of the models indicated that the amounts of Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) indices for the Zero-truncated Poisson model are less than those of the Poisson model and the result of the Pseudo-R2 test for this model is within the acceptable range. Moreover, the result of Chi-square test which shows the proximity of expected and observed amounts was better for Zero-truncated Poisson model. Thus, this model has a considerable advantage against Poisson model. Final models indicated that the average speed has a positive correlation with the number of violations and crashes and as it increases, they increase too. Besides, peripheral landscapes, number of interchanges, number of passing lanes, and exemption from paying toll have an opposite relationship with violations and crashes.
       
  • Safety assessment of control design parameters through vehicle dynamics
           model
    • Abstract: Publication date: Available online 20 July 2018Source: Accident Analysis & PreventionAuthor(s): Stergios Mavromatis, Alexandra Laiou, George Yannis An existing vehicle dynamics model was utilized to define design parameters up to which steady state cornering conditions apply and consequently lift the restrictions of the point mass model. Aiming to assess critical safety concerns in terms of vehicle skidding, the motion of a passenger car was examined over a range of design speed values paired with control design elements from AASHTO 2011 Design Guidelines as well as certain values of poor pavement friction coefficients.Two distinct cases were investigated; the determination of the maximum attainable constant speed (termed as safe speed) at impending skid conditions as well as the case of comfortable curve negotiation where lower constant speed values were utilized. The overall objective was to define the safety margins for each examined case.From the interaction between road geometry, pavement friction and vehicle characteristics, many interesting findings are reported, where some of them are beyond the confined field of road geometry parameters; such as demanded longitudinal and lateral friction values and horse-power utilization rates. From the road geometry point of view, it was found that control alignments on steep upgrades consisting of low design speed values and combined with poor friction pavements are critical in terms of safety. Such cases should be treated very cautiously through certain actions. These actions include the adoption of acceptable arrangements for the above values regarding new alignments, posted speed management for existing but also scheduling friction improvement programmes more accurately for both cases.
       
  • A novel method for imminent crash prediction and prevention
    • Abstract: Publication date: Available online 12 July 2018Source: Accident Analysis & PreventionAuthor(s): Zhi Chen, Xiao Qin A crash prediction and prevention method was proposed to detect imminent crash risk and help recommend traffic control strategies to prevent crashes. The method consists of two modules, the crash prediction module and the crash prevention module. The crash prediction module detects crash-prone conditions when the predicted crash probability exceeds a specified threshold. Then the crash prevention module would simulate the safety effect of traffic control alternatives and recommend the optimal one. The proposed method was demonstrated in a case study with variable speed limit (VSL). Results showed that the proposed crash prediction and prevention method could effectively detect crash-prone conditions and evaluate the safety and mobility impacts of various safety countermeasures.
       
  • Road safety data considerations
    • Abstract: Publication date: Available online 11 July 2018Source: Accident Analysis & PreventionAuthor(s): Loukas Dimitriou, Constantinos Antoniou
       
  • Use of real-world connected vehicle data in identifying high-risk
           locations based on a new surrogate safety measure
    • Abstract: Publication date: Available online 6 July 2018Source: Accident Analysis & PreventionAuthor(s): Kun Xie, Di Yang, Kaan Ozbay, Hong Yang Traditional methods for the identification of high-risk locations rely heavily on historical crash data. Rich information generated from connected vehicles could be used to obtain surrogate safety measures (SSMs) for risk identification. Conventional SSMs such as time to collision (TTC) neglect the potential risk of car-following scenarios in which the following vehicle’s speed is slightly less than or equal to the leading vehicle’s but the spacing between two vehicles is relatively small that a slight disturbance would yield collision risk. To address this limitation, this study proposes time to collision with disturbance (TTCD) for risk identification. By imposing a hypothetical disturbance, TTCD can capture rear-end conflict risks in various car following scenarios, even when the leading vehicle has a higher speed. Real-world connected vehicle pilot test data collected in Ann Arbor, Michigan is used in this study. A detailed procedure of cleaning and processing the connected vehicle data is presented. Results show that risk rate identified by TTCD can achieve a higher Pearson’s correlation coefficient with rear-end crash rate than other traditional SSMs. We show that high-risk locations identified by connected vehicle data from a relatively shorter time period are similar to the ones identified by using the historical crash data. The proposed method can substantially reduce the data collection time, compared with traditional safety analysis that generally requires more than three years to get sufficient crash data. The connected vehicle data has thus shown the potential to be used to develop proactive safety solutions and the risk factors can be eliminated in a timely manner.
       
  • 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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