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Publisher: Elsevier   (Total: 3161 journals)

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Showing 1 - 200 of 3161 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: 35, SJR: 1.655, CiteScore: 2)
Academic Radiology     Hybrid Journal   (Followers: 24, SJR: 1.015, CiteScore: 2)
Accident Analysis & Prevention     Partially Free   (Followers: 96, SJR: 1.462, CiteScore: 3)
Accounting Forum     Hybrid Journal   (Followers: 27, SJR: 0.932, CiteScore: 2)
Accounting, Organizations and Society     Hybrid Journal   (Followers: 37, 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: 421, SJR: 0.758, CiteScore: 2)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 2)
Acta Biomaterialia     Hybrid Journal   (Followers: 28, 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: 276, SJR: 3.263, CiteScore: 6)
Acta Mathematica Scientia     Full-text available via subscription   (Followers: 5, SJR: 0.504, CiteScore: 1)
Acta Mechanica Solida Sinica     Full-text available via subscription   (Followers: 9, SJR: 0.542, CiteScore: 1)
Acta Oecologica     Hybrid Journal   (Followers: 12, SJR: 0.834, CiteScore: 2)
Acta Otorrinolaringologica (English Edition)     Full-text available via subscription  
Acta Otorrinolaringológica Española     Full-text available via subscription   (Followers: 3, SJR: 0.307, CiteScore: 0)
Acta Pharmaceutica Sinica B     Open Access   (Followers: 1, SJR: 1.793, CiteScore: 6)
Acta Poética     Open Access   (Followers: 4, SJR: 0.101, CiteScore: 0)
Acta Psychologica     Hybrid Journal   (Followers: 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: 8)
Acute Pain     Full-text available via subscription   (Followers: 14, SJR: 2.671, CiteScore: 5)
Ad Hoc Networks     Hybrid Journal   (Followers: 11, SJR: 0.53, CiteScore: 4)
Addictive Behaviors     Hybrid Journal   (Followers: 17, SJR: 1.29, CiteScore: 3)
Addictive Behaviors Reports     Open Access   (Followers: 8, SJR: 0.755, CiteScore: 2)
Additive Manufacturing     Hybrid Journal   (Followers: 11, SJR: 2.611, CiteScore: 8)
Additives for Polymers     Full-text available via subscription   (Followers: 23)
Advanced Drug Delivery Reviews     Hybrid Journal   (Followers: 167, SJR: 4.09, CiteScore: 13)
Advanced Engineering Informatics     Hybrid Journal   (Followers: 12, 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: 15, SJR: 2.384, CiteScore: 5)
Advances in Anesthesia     Full-text available via subscription   (Followers: 28, SJR: 0.126, CiteScore: 0)
Advances in Antiviral Drug Design     Full-text available via subscription   (Followers: 2)
Advances in Applied Mathematics     Full-text available via subscription   (Followers: 10, SJR: 0.992, CiteScore: 1)
Advances in Applied Mechanics     Full-text available via subscription   (Followers: 11, SJR: 1.551, CiteScore: 4)
Advances in Applied Microbiology     Full-text available via subscription   (Followers: 24, SJR: 2.089, CiteScore: 5)
Advances In Atomic, Molecular, and Optical Physics     Full-text available via subscription   (Followers: 14, SJR: 0.572, CiteScore: 2)
Advances in Biological Regulation     Hybrid Journal   (Followers: 4, SJR: 2.61, CiteScore: 7)
Advances in Botanical Research     Full-text available via subscription   (Followers: 2, SJR: 0.686, CiteScore: 2)
Advances in Cancer Research     Full-text available via subscription   (Followers: 33, SJR: 3.043, CiteScore: 6)
Advances in Carbohydrate Chemistry and Biochemistry     Full-text available via subscription   (Followers: 9, SJR: 1.453, CiteScore: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5, SJR: 1.992, CiteScore: 5)
Advances in Cell Aging and Gerontology     Full-text available via subscription   (Followers: 4)
Advances in Cellular and Molecular Biology of Membranes and Organelles     Full-text available via subscription   (Followers: 13)
Advances in Chemical Engineering     Full-text available via subscription   (Followers: 28, 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: 26, SJR: 1.562, CiteScore: 3)
Advances in Colloid and Interface Science     Full-text available via subscription   (Followers: 20, 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: 7)
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: 29, SJR: 1.159, CiteScore: 4)
Advances in Experimental Biology     Full-text available via subscription   (Followers: 8)
Advances in Experimental Social Psychology     Full-text available via subscription   (Followers: 46, SJR: 5.39, CiteScore: 8)
Advances in Exploration Geophysics     Full-text available via subscription   (Followers: 1)
Advances in Fluorine Science     Full-text available via subscription   (Followers: 9)
Advances in Food and Nutrition Research     Full-text available via subscription   (Followers: 60, SJR: 0.591, CiteScore: 2)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 17)
Advances in Genetics     Full-text available via subscription   (Followers: 19, SJR: 1.354, CiteScore: 4)
Advances in Genome Biology     Full-text available via subscription   (Followers: 10, 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: 24, 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: 23)
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: 10, 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: 8)
Advances in Marine Biology     Full-text available via subscription   (Followers: 18, SJR: 0.88, CiteScore: 2)
Advances in Mathematics     Full-text available via subscription   (Followers: 11, SJR: 3.027, CiteScore: 2)
Advances in Medical Sciences     Hybrid Journal   (Followers: 7, SJR: 0.694, CiteScore: 2)
Advances in Medicinal Chemistry     Full-text available via subscription   (Followers: 5)
Advances in Microbial Physiology     Full-text available via subscription   (Followers: 4, SJR: 1.158, CiteScore: 3)
Advances in Molecular and Cell Biology     Full-text available via subscription   (Followers: 23)
Advances in Molecular and Cellular Endocrinology     Full-text available via subscription   (Followers: 8)
Advances in Molecular Toxicology     Full-text available via subscription   (Followers: 7, SJR: 0.182, CiteScore: 0)
Advances in Nanoporous Materials     Full-text available via subscription   (Followers: 4)
Advances in Oncobiology     Full-text available via subscription   (Followers: 2)
Advances in Organ Biology     Full-text available via subscription   (Followers: 2)
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: 25, SJR: 0.461, CiteScore: 1)
Advances in Pharmaceutical Sciences     Full-text available via subscription   (Followers: 12)
Advances in Pharmacology     Full-text available via subscription   (Followers: 16, SJR: 1.536, CiteScore: 3)
Advances in Physical Organic Chemistry     Full-text available via subscription   (Followers: 8, SJR: 0.574, CiteScore: 1)
Advances in Phytomedicine     Full-text available via subscription  
Advances in Planar Lipid Bilayers and Liposomes     Full-text available via subscription   (Followers: 3, SJR: 0.109, CiteScore: 1)
Advances in Plant Biochemistry and Molecular Biology     Full-text available via subscription   (Followers: 10)
Advances in Plant Pathology     Full-text available via subscription   (Followers: 5)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Protein Chemistry     Full-text available via subscription   (Followers: 19)
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: 65)
Advances in Quantum Chemistry     Full-text available via subscription   (Followers: 6, SJR: 0.371, CiteScore: 1)
Advances in Radiation Oncology     Open Access   (Followers: 1, 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: 404, 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: 12, SJR: 0.555, CiteScore: 2)
Advances in the Study of Behavior     Full-text available via subscription   (Followers: 34, SJR: 2.208, CiteScore: 4)
Advances in Veterinary Medicine     Full-text available via subscription   (Followers: 18)
Advances in Veterinary Science and Comparative Medicine     Full-text available via subscription   (Followers: 14)
Advances in Virus Research     Full-text available via subscription   (Followers: 5, SJR: 2.262, CiteScore: 5)
Advances in Water Resources     Hybrid Journal   (Followers: 47, SJR: 1.551, CiteScore: 3)
Aeolian Research     Hybrid Journal   (Followers: 6, SJR: 1.117, CiteScore: 3)
Aerospace Science and Technology     Hybrid Journal   (Followers: 359, 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: 466, 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: 4)
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: 12, SJR: 1.153, CiteScore: 3)
Alcoholism and Drug Addiction     Open Access   (Followers: 11)
Alergologia Polska : Polish J. of Allergology     Full-text available via subscription   (Followers: 1)
Alexandria Engineering J.     Open Access   (Followers: 1, SJR: 0.604, CiteScore: 3)
Alexandria J. of Medicine     Open Access   (Followers: 1, SJR: 0.191, CiteScore: 1)
Algal Research     Partially Free   (Followers: 10, SJR: 1.142, CiteScore: 4)
Alkaloids: Chemical and Biological Perspectives     Full-text available via subscription   (Followers: 2)
Allergologia et Immunopathologia     Full-text available via subscription   (Followers: 1, SJR: 0.504, CiteScore: 1)
Allergology Intl.     Open Access   (Followers: 5, SJR: 1.148, CiteScore: 2)
Alpha Omegan     Full-text available via subscription   (SJR: 3.521, CiteScore: 6)
ALTER - European J. of Disability Research / Revue Européenne de Recherche sur le Handicap     Full-text available via subscription   (Followers: 10, SJR: 0.201, CiteScore: 1)
Alzheimer's & Dementia     Hybrid Journal   (Followers: 52, 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: 56, SJR: 3.267, CiteScore: 4)
American J. of Cardiology     Hybrid Journal   (Followers: 59, SJR: 1.93, CiteScore: 3)
American J. of Emergency Medicine     Hybrid Journal   (Followers: 44, SJR: 0.604, CiteScore: 1)
American J. of Geriatric Pharmacotherapy     Full-text available via subscription   (Followers: 11)
American J. of Geriatric Psychiatry     Hybrid Journal   (Followers: 13, SJR: 1.524, CiteScore: 3)
American J. of Human Genetics     Hybrid Journal   (Followers: 34, SJR: 7.45, CiteScore: 8)
American J. of Infection Control     Hybrid Journal   (Followers: 28, SJR: 1.062, CiteScore: 2)
American J. of Kidney Diseases     Hybrid Journal   (Followers: 35, SJR: 2.973, CiteScore: 4)
American J. of Medicine     Hybrid Journal   (Followers: 48)
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: 225, SJR: 2.7, CiteScore: 4)
American J. of Ophthalmology     Hybrid Journal   (Followers: 66, SJR: 3.184, CiteScore: 4)
American J. of Ophthalmology Case Reports     Open Access   (Followers: 5, SJR: 0.265, CiteScore: 0)
American J. of Orthodontics and Dentofacial Orthopedics     Full-text available via subscription   (Followers: 6, SJR: 1.289, CiteScore: 1)
American J. of Otolaryngology     Hybrid Journal   (Followers: 25, SJR: 0.59, CiteScore: 1)
American J. of Pathology     Hybrid Journal   (Followers: 28, SJR: 2.139, CiteScore: 4)
American J. of Preventive Medicine     Hybrid Journal   (Followers: 29, 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: 63, SJR: 0.138, CiteScore: 0)
Anaesthesia Critical Care & Pain Medicine     Full-text available via subscription   (Followers: 19, SJR: 0.411, CiteScore: 1)
Anales de Cirugia Vascular     Full-text available via subscription   (Followers: 1)
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: 189, SJR: 0.633, CiteScore: 2)
Analytical Chemistry Research     Open Access   (Followers: 12, SJR: 0.411, CiteScore: 2)
Analytical Spectroscopy Library     Full-text available via subscription   (Followers: 13)
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: 205, SJR: 1.58, CiteScore: 3)

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Journal Cover
Accident Analysis & Prevention
Journal Prestige (SJR): 1.462
Citation Impact (citeScore): 3
Number of Followers: 96  
 
  Partially Free Journal Partially Free Journal
ISSN (Print) 0001-4575
Published by Elsevier Homepage  [3161 journals]
  • Comparison of Bayesian techniques for the before–after evaluation of the
           safety effectiveness of short 2+1 road sections
    • Abstract: Publication date: June 2019Source: Accident Analysis & Prevention, Volume 127Author(s): Carmelo D’Agostino, Salvatore Cafiso, Mariusz Kiec In evaluating the effectiveness of a road safety treatment, the regression to the mean phenomenon is a cause for concern because of a possible overestimation of benefits. Therefore, Bayesian approaches are usually suggested as the most appropriate methodologies for before—after studies as they account for regression to the mean effects. The empirical Bayes (EB) methodology examines the estimation of the expected number of crashes that would have occurred without treatment and compares them with the crashes observed at the treated sites. Even if there is no significant regression to the mean bias, the EB technique requires a reliable and large dataset with sufficient years of observation and number of treated sites, adequate for estimating the safety effects of a treatment with acceptable standard errors. In this framework, a full Bayesian (FB) approach can mitigate the problem of using small datasets by providing more detailed causal inferences and more flexibility in selecting crash count distributions, acknowledging that a more complex methodology must be applied. With the aim of estimating the safety improvements of new, short 2 + 1 road sections in Poland limited by the existing road network, EB and FB estimations are compared and different safety performance function (SPF) model forms are used in order to evaluate the performance of the two methodologies. Results indicated that, even if crash modification factors (CMFs) resulted in similar average values, the EB trend is to underestimate CMFs compared with the more complex methodology, while overall the FB approach provided a lower standard deviation. The differences are more pronounced between the EB and FB approaches when a simple SPF model form is used for the analysed dataset. Moreover, for this specific dataset, the difference between the FB method and the EB method using a refined regression model with more variables was negligible.
       
  • Review of average sized male and female occupant models in European
           regulatory safety assessment tests and European laws: Gaps and bridging
           suggestions
    • Abstract: Publication date: June 2019Source: Accident Analysis & Prevention, Volume 127Author(s): Astrid Linder, Wanna Svedberg There are two parts to the aim of this study. The first part comprised reviewing how men and women are represented in regulatory tests conducted to assess adult occupant safety in vehicles in Europe. This part also contains an overview of some differences between females and males that may influence dynamic responses in a crash. Based on the results of the review an outline for how to better represent the adult population in regulatory tests has been suggested.The second part was to reflect on these issues from a specific critical legal perspective, that is from a Gender Legal Studies point of view, focusing on the European legal framework that governs the tests of adult occupant safety in vehicles in Europe. Since the beginning of the 1970s legal scholars have shown in several areas of law that there is a gap between superior legislation and practice, but also between gender equality as a superior legal principle and subordinate legal rules that govern safety requirements. The same pattern can be discerned in the area of Transportation Law.The results of the review of the ECE regulations shows that the average sized male represents the adult population and that the average sized female has been excluded from regulations assessing the protection of adult vehicle occupants. The fundamental values, on which the Union is founded, including the overarching goals of the Union, seem to be rendered invisible in the laws and critically impact the safety of women in everyday life. According to the gender system theory, the interests and priorities of men are continuing to shape the law. Consequently, the law neglecting the safety of women on roads has implications on the development of society. The lack of legal provisions that demand female crash test dummies representing the female part of the population, means that there is no incentive for car manufacturers, authorities or other stakeholders to develop test methods and female crash test dummies in ways that promote political objectives expressed in legal form, i.e., the legal values expressed in general provisions and principles stated in the Treaty on European Union and the Treaty on the Functioning of the European Union, such as gender equality between women and men as well as non-discriminationThis study highlights the undeniable gap between the legal framework and legal requirements with regard to occupant safety for the whole adult population. It would be attainable to bridge this particular gender gap by providing equal representation for the female part of the population with regard to vehicle safety, as that males benefit from.Graphical abstractGraphical abstract for this article
       
  • Safety, security, and serviceability in road engineering
    • Abstract: Publication date: June 2019Source: Accident Analysis & Prevention, Volume 127Author(s): Michael S. Pritchard Road engineers have special responsibilities to design and maintain roads that are safe, secure, and serviceable. This paper explores some of the challenges such responsibilities pose, especially from the vantage point of non-engineers whose lives are deeply affected by the work of road engineers. It also supports the thesis that road engineers need to be prepared to consult and work with professionals in other fields than engineering in order to fulfill their responsibilities well.
       
  • How to trade safety against cost, time and other impacts of road safety
           measures
    • Abstract: Publication date: June 2019Source: Accident Analysis & Prevention, Volume 127Author(s): Rune Elvik Public policy, including road safety policy, involves balancing competing values against each other. Several techniques of policy analysis, most prominently cost-benefit analysis, have been developed to help policy makers prioritize between different values. Valuation studies have not produced credible monetary values of life and limb. Cost-benefit analysis therefore cannot tell when the “right” balance has been struck between road safety and other objectives of transport policy. All formal tools of policy analysis are likely to reflect analyst values to a major extent, not the values of policy makers only. It is argued that policy choices and tradeoffs can be informed simply by providing factual information about impacts and not attempting to impose any value judgements. A widely applicable metric is to state impacts as changes in human longevity and health state.
       
  • A comparison of statistical learning methods for deriving determining
           
    • Abstract: Publication date: June 2019Source: Accident Analysis & Prevention, Volume 127Author(s): Matthias Schlögl, Rainer Stütz, Gregor Laaha, Michael Melcher One of the main aims of accident data analysis is to derive the determining factors associated with road traffic accident occurrence. While current studies mainly use variants of count data regression to achieve this aim, the problem can also be considered as a binary classification task, with the dichotomous target variable indicating events (accidents) and non-events (no accidents). The effects of 45 variables – describing road condition and geometry, traffic volume and regulations, weather, and accident time – are analyzed using a dataset in high temporal (1 h) and spatial (250 m) resolution, covering the whole highway network of Austria over the period of four consecutive years. A combination of synthetic minority oversampling and maximum dissimilarity undersampling is used to balance the training dataset. We employ and compare a series of statistical learning techniques with respect to their predictive performance and discuss the importance of determining factors of accident occurrence from the ensemble of models. Findings substantiate that a trade-off between accuracy and sensitivity is inherent to imbalanced classification problems. Results show satisfying performance of tree-based methods which exhibit accuracies between 75% and 90% while exhibiting sensitivities between 30% and 50%. Overall, this analysis emphasizes the merits of using high-resolution data in the context of accident analysis.
       
  • Exploring the contribution of executive functions to on-road driving
           performance during aging: A latent variable analysis
    • Abstract: Publication date: June 2019Source: Accident Analysis & Prevention, Volume 127Author(s): Julien Adrian, Michèle Moessinger, André Charles, Virginie Postal With the aging of the population the issue of older drivers safety has gained importance in recent years. Age-related cognitive decline is frequently cited as the main cause of unsafe driving performance in older drivers. Objective: The present study investigated how executive functions (EFs), measured as latent variables, are related to on-road driving performance during aging. Method: One hundred and twenty-six participants aged from twenty to eighty-two, completed a two hundred and forty-seven km on-road driving test and a set of executive tasks selected to tap three often postulated EFs: inhibition (inhibiting prepotent responses), updating (updating working memory representations), and shifting (shifting task sets). Results: Confirmatory factor analysis reproduces previous results obtained by Miyake et al. (2000), Miyake and Friedman (2012) of unity and diversity of EFs in an adult life span sample. Structural equation modeling suggested that on-road driving performance was related to inhibition. Furthermore, findings indicate that the age-related driving performance decline in normal aging may be mediated by the inhibition function. Conclusions: The results highlight the importance of a proper method to assess executive functioning in a specific domain as well as emphasising the major role of those functions in driving performance while aging.
       
  • Impact of regulations to control alcohol consumption by drivers: An
           assessment of reduction in fatal traffic accident numbers in the Federal
           District, Brazil
    • Abstract: Publication date: June 2019Source: Accident Analysis & Prevention, Volume 127Author(s): Alam Gonçalves Guimarães, Alan Ricardo da Silva In 2008 Brazil enacted Law n° 11.705, known as the Lei Seca (in Portuguese) or Dry Law, altering the National Traffic Code by establishing zero tolerance for the presence of alcohol in drivers’ bloodstreams and toughening punishment for offenders. In 2012 the New Dry Law, Law n° 12.760 came into force in an effort to correct for legal loopholes in the earlier version and make it feasible to produce alternative forms of proof of alcohol impediment against those drivers who refused to take the breath analysis test. Sanctions for offenders were made even more severe. Ten years after the advent of the first Lei Seca this study set out to make a quantitative assessment of the two laws’ impacts regarding the reduction of lethal traffic accidents in the Federal District, Brazil. Intervention Analysis of Time Series was the technique used and transfer functions enabled the incorporation of the effects of dummy exogenous variables to the Box and Jenkins ARIMA model. Results showed that while Law n° 11.705 had no significant impact, Law 12.760 did have a statistically significant impact in reducing lethal accidents. Such results underscore the need for ex post monitoring and evaluation of Laws and confirm the premise that legislation only successfully produces its effects when compliance can be enforced.
       
  • How instantaneous driving behavior contributes to crashes at
           intersections: Extracting useful information from connected vehicle
           message data
    • Abstract: Publication date: June 2019Source: Accident Analysis & Prevention, Volume 127Author(s): Ramin Arvin, Mohsen Kamrani, Asad J. Khattak Connected and automated vehicles have enabled researchers to use big data for development of new metrics that can enhance transportation safety. Emergence of such a big data coupled with computational power of modern computers have enabled us to obtain deeper understanding of instantaneous driving behavior by applying the concept of “driving volatility” to quantify variations in driving behavior. This paper brings in a methodology to quantify variations in vehicular movements utilizing longitudinal and lateral volatilities and proactively studies the impact of instantaneous driving behavior on type of crashes at intersections. More than 125 million Basic Safety Message data transmitted between more than 2800 connected vehicles were analyzed and integrated with historical crash and road inventory data at 167 intersections in Ann Arbor, Michigan, USA. Given that driving volatility represents the vehicular movement and control, it is expected that erratic longitudinal/lateral movements increase the risk of crash. In order to capture variations in vehicle control and movement, we quantified and used 30 measures of driving volatility by using speed, longitudinal and lateral acceleration, and yaw-rate. Rigorous statistical models including fixed parameter, random parameter, and geographically weighted Poisson regressions were developed. The results revealed that controlling for intersection geometry and traffic exposure, and accounting unobserved factors, variations in longitudinal control of the vehicle (longitudinal volatility) are highly correlated with the frequency of rear-end crashes. Intersections with high variations in longitudinal movement are prone to have higher rear-end crash rate. Referring to sideswipe and angle crashes, along with speed and longitudinal volatility, lateral volatility is substantially correlated with the frequency of crashes. When it comes to head-on crashes, speed, longitudinal and lateral acceleration volatilities are highly associated with the frequency of crashes. Intersections with high lateral volatility have higher risk of head-on collisions due to the risk of deviation from the centerline leading to head-on crash. The developed methodology and volatility measures can be used to proactively identify hotspot intersections where the frequency of crashes is low, but the longitudinal/lateral driving volatility is high. The reason that drivers exhibit higher levels of driving volatility when passing these intersections can be analyzed to come up with potential countermeasures that could reduce volatility and, consequently, crash risk.
       
  • Middle-aged Drivers’ subjective categorization for combined alignments
           on mountainous freeways and their speed choices
    • Abstract: Publication date: June 2019Source: Accident Analysis & Prevention, Volume 127Author(s): Fan Wang, Yuren Chen, Jingqiu Guo, Chen Yu, Mark Stevenson, Haifeng Zhao Road geometric design is a fundamental factor that impacts driving speed. Previous research generally paid attentions to the influences of specific road characteristics (e.g. curvature) on driving behaviors. Limited studies have focused on how drivers identify different alignments and how they further take the varying speed choices. This study aims at filling the gap by investigating the subjective categorization of road alignments based on middle-aged driver groups. A total of sixteen participants with ages ranging from 23 to 40 years were recruited. Participants were first asked to undertake naturalistic driving tests on a four-lane divided mountainous freeway while photos of the road and the driving speed were collected. Participants were then asked to subjectively sort the photos of the road into piles, within each pile we considered their driving behaviors would be similar. Finally, questionnaire survey was conducted in terms of comfort, safety, speed choice and sight distance. The picture grouping revealed three distinct and non-overlapping subjective categories of road alignment. And driver’s ratings about comfort and safety were significantly different between these categories. The category with the largest sight distance and highest speed choice turned out to have the lowest rating in comfort and safety (note that the rating scales for comfort and safety had reversed polarity such that low numbers indicated high comfort and high safety). Statistical evidences indicated that the drivers have developed underlying mental schema about road alignment. Therefore, their speed choices on combined alignment were further investigated. The difference between actual driving speed and driver’s expected speed showed close relation to the ratings and significant difference between two of the categories. Road with large absolute value in speed difference informed inconsistency between geometric design and driver’s expectation from the aspects of drivers’ perception and expectation of the road. The findings provided insight into how middle-aged driver views and categorizes road alignment. And it was found that the drivers relied on visual characteristics of the alignment to distinguish the categories instead of separate horizontal and vertical geometric parameters. It was implied that more considerations should be taken into driver’s perception of road during alignment design to improve road safety.
       
  • An evaluation of the effects of an innovative school-based cycling
           education program on safety and participation
    • Abstract: Publication date: June 2019Source: Accident Analysis & Prevention, Volume 127Author(s): J. Hatfield, S. Boufous, T. Eveston Cycling education programs for children could play a role in promoting both cycling participation and cycling safety, and they exist in many countries – often in school settings. Evaluations have generally shown improvements in skills and knowledge, but effects on less-researched outcomes such as safety-related behaviour, crashes or injuries, cycling participation, and cycling confidence, are unclear. The present research evaluated Safe Cycle, an innovative Australian school-based program that addresses hazard awareness and overconfidence in addition to more typical content (e.g. handling skills), in terms of a comprehensive range of outcomes. Students from Years 4 to 8 (n = 108) completed online surveys in class before, immediately after, and approximately 14 weeks after, the 8-week program was delivered. Significant increases in knowledge and confidence were observed, while results also suggested increases in cycling participation. The program appeared to address illusory invulnerability effectively, but there was no evidence that the program improved safety-relevant cycling behaviours or experience of crashes. The benefits of Safe Cycle might be enhanced by including elements to increase motivation to perform safety-relevant behaviours and durability of program effects.
       
  • Sickness absence, disability pension and permanent medical impairment
           among 64 000 injured car occupants of working ages: A two-year prospective
           cohort study
    • Abstract: Publication date: June 2019Source: Accident Analysis & Prevention, Volume 127Author(s): Rasmus Elrud, Emilie Friberg, Kristina Alexanderson, Helena Stigson ObjectiveThere is a lack of knowledge regarding sickness absence (SA) and disability pension (DP) as consequences of road traffic injuries, and on the association between DP and permanent medical impairment (PMI). Therefore, the aim of this study was to investigate SA, DP, and PMI among injured passenger car occupants two years after a crash, and how they are associated, accounting for sociodemographics, crash-related factors, and previous SA/DP.MethodsThis prospective cohort study included 64 007 injured car occupants aged 17–62 years at the time of a crash occurring in 2001–2013, involving a car insured at Folksam Insurance Group in Sweden. Information on sociodemographics, crash-related factors, SA (in SA spells>14 days) and DP status at inclusion and at two-year follow-up, and PMI assessed by the insurance company was used. PMI grades were categorized as 1–4, 5–9, 10–19, or>19%. Logistic regression was performed to calculate odds ratios (OR) with 95% confidence intervals (CI) for DP at follow-up and for PMI, respectively.ResultsAt the time of the crash 13% were already on SA or DP. At follow-up two years after the crash, 6% among those not already on SA/DP at the time of the crash were on SA and 2% on DP. Furthermore, 8% of the total cohort had a determined PMI. Among those not already on DP at the crash, 3% with no PMI had DP at follow-up. This proportion was higher the higher PMI grade. Among individuals without already ongoing DP at the crash date, 10% of those with a PMI 1–4 ha d DP, compared to 76% among PMI ≥ 20. Already ongoing SA at the time of the crash (OR = 39.16, 95% CI 34.89–43.95) and PMI grade (PMI ≥ 5 OR = 27.44, 95% CI 23.88–31.52, reference group PMI 0) were found to be associated with DP at two years after crash. The factor most strongly associated with PMI was the model year of the car. The older the car, the higher the risk of PMI (Model year ≤ 1990 OR = 3.36, 95% CI 2.67–4.23, reference group model year 2006–2010). An association with the same direction was also found between the model year of the car and DP at follow-up.ConclusionsThe association between PMI grade and DP status at follow-up among occupants not on DP at the crash date indicates that both could be used to measure long-term consequences of road traffic injury. In this cohort, already ongoing SA at the crash date was associated with DP at the two-year follow-up, emphasizing the importance of accounting for this factor in future research.
       
  • Associations between emotional symptoms and self-reported aberrant driving
           behaviors in older adults
    • Abstract: Publication date: June 2019Source: Accident Analysis & Prevention, Volume 127Author(s): John P.K. Bernstein, Alyssa DeVito, Matthew Calamia ObjectiveTo examine associations between internalizing symptoms and self-reported aberrant driving behaviors in a large sample (n = 341) of older adults (mean age = 62.6 years, SD = 4.8).DesignCross-sectional survey.ResultsMultiple regression analyses revealed that greater symptoms of emotional distress (i.e., higher scores on the Expanded Version of the Inventory of Depression and Anxiety Symptoms (IDAS-II) emotional distress composite) were associated with greater aberrant driving behaviors (i.e., higher scores on the Driving Behavior Questionnaire). In contrast, neither obsessions/fears nor emotional well-being were associated with greater aberrant driving behaviors. Follow-up regression analyses examining specific IDAS-II subscales revealed that greater suicidality, appetite gain, appetite loss, panic, and ill temper were associated with greater aberrant driving behaviors. Individuals reporting greater suicidality and appetite loss reported greater tendencies to unintentionally commit errors behind the wheel, while individuals reporting greater ill temper and appetite loss reported greater tendencies to intentionally engage in unsafe driving behaviors that may put other drivers in harm’s way.ConclusionOlder adults reporting emotional distress may be at risk for engaging in aberrant driving behaviors. In particular, certain symptoms of emotional distress (e.g., suicidality, ill temper) are tied to higher rates of aberrant driving behaviors within this population.
       
  • Regulatory focus, time perspective, locus of control and sensation seeking
           as predictors of risky driving behaviors
    • Abstract: Publication date: June 2019Source: Accident Analysis & Prevention, Volume 127Author(s): Linda Lemarié, François Bellavance, Jean-Charles Chebat Empirical evidence shows that most of the road safety efforts fail to reach the most risk-prone drivers. In light of this issue, we have developed this study in order to distinguish between high-risk drivers and low-risk drivers based on variables that have already been shown to affect the effectiveness of preventive messages: regulatory focus orientation, time perspective, locus of control and sensation seeking. We sent paper and pencil questionnaires to five thousand low-risk drivers and five thousand high-risk drivers randomly selected based on their driving records. A driver who has been convicted of two or more traffic infractions with demerit points (e.g., exceeding speed limits, red light violation, no seatbelt, etc.) in the last two years was considered a high-risk driver whereas a low-risk driver had no traffic offense registered in his driving record in the last four years. We received two thousand and sixty-four completed questionnaires for a response rate of 20.6%. Seven hundred and ninety-eight belonged to the group of high-risk drivers and one thousand two hundred and sixty-six to the group of low-risk drivers. The results show that a promotion focused orientation, a present hedonistic perspective, an internal locus of control, and sensation seeking are associated with more risky driving behaviors and could therefore distinguish between high-risk and low-risk drivers. These results increase the understanding of risky drivers’ personalities and motivations. The literature review provides insight into how these findings might be considered in developing more effective road safety programs and campaigns, and the conclusion encourages researchers to explore these new avenues in future research.
       
  • Texting while walking: An expensive switch cost
    • Abstract: Publication date: June 2019Source: Accident Analysis & Prevention, Volume 127Author(s): Francois Courtemanche, Elise Labonté-LeMoyne, Pierre-Majorique Léger, Marc Fredette, Sylvain Senecal, Ann-Frances Cameron, Jocelyn Faubert, Francois Bellavance Texting while walking has been highlighted as a dangerous behavior that leads to impaired judgment and accidents. This impairment could be due to task switching which involves activation of the present task and the inhibition of the previous task. However, the relative contributions of these processes and their brain activity have not yet been studied. We addressed this gap by asking participants to discriminate the orientation of an oncoming human shape in a virtual environment while they were: i) walking on a treadmill, or ii) texting while walking on a treadmill. Participants’ performance (i.e., correctly identifying if a walker would pass them to their left or right) and electroencephalography (EEG) data was collected. Unsurprisingly, we found that participants performed better while they were only walking than when texting while walking. However, we also found that the diminished performance is differently related to task set inhibition and task set activation in the two conditions. The alpha oscillations, which can be used as an index of task inhibition, have a significantly different relation to performance in the two conditions, the relation being negative when subjects are texting. This may indicate that the more inhibition is needed, the more the performance is affected by texting. To our knowledge, this is the first study to investigate the brain signature of task switching in texting while walking. This finding is the first step in identifying the source of impaired judgment in texting pedestrians and in finding viable solutions to reduce the risks.
       
  • A new integrated collision risk assessment methodology for autonomous
           vehicles
    • Abstract: Publication date: June 2019Source: Accident Analysis & Prevention, Volume 127Author(s): Christos Katrakazas, Mohammed Quddus, Wen-Hua Chen Real-time risk assessment of autonomous driving at tactical and operational levels is extremely challenging since both contextual and circumferential factors should concurrently be considered. Recent methods have started to simultaneously treat the context of the traffic environment along with vehicle dynamics. In particular, interaction-aware motion models that take inter-vehicle dependencies into account by utilizing the Bayesian interference are employed to mutually control multiple factors. However, communications between vehicles are often assumed and the developed models are required many parameters to be tuned. Consequently, they are computationally very demanding. Even in the cases where these desiderata are fulfilled, current approaches cannot cope with a large volume of sequential data from organically changing traffic scenarios, especially in highly complex operational environments such as dense urban areas with heterogeneous road users. To overcome these limitations, this paper develops a new risk assessment methodology that integrates a network-level collision estimate with a vehicle-based risk estimate in real-time under the joint framework of interaction-aware motion models and Dynamic Bayesian Networks (DBN). Following the formulation and explanation of the required functions, machine learning classifiers were utilized for the real-time network-level collision prediction and the results were then incorporated into the integrated DBN model for predicting collision probabilities in real-time. Results indicated an enhancement of the interaction-aware model by up to 10%, when traffic conditions are deemed as collision-prone. Hence, it was concluded that a well-calibrated collision prediction classifier provides a crucial hint for better risk perception by autonomous vehicles.
       
  • Impact of heterogeneity of car-following behavior on rear-end crash risk
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Junjie Zhang, Yunpeng Wang, Guangquan Lu An increasing number of vehicles travel on freeways result not only in traffic congestions but also accidents. Rear-end crashes in freeways can be collectively attributed to drivers, vehicles, and road infrastructure, but driving behavior plays a key role in influencing car-following safety. This study aims to investigate the impact of heterogeneity of driving behavior on rear-end crash risk. Driving behavior depends on perceived risk levels, acceleration and deceleration habits, and driver reaction characteristics. Thus, the influencing factors of rear-end crash risk were initially analyzed by using the desired safety margin (DSM) model. Subsequently, five driving behavior parameters, including upper and lower limits of DSM, sensitivity coefficients of acceleration and deceleration, and response time, were calibrated by using the vehicle trajectories from the Next Generation Simulation I-80 datasets. Simulation experiments were designed to evaluate the impact of heterogeneity of car-following behavior on rear-end crash risk. Results showed that decreasing the lower (or upper) limit of the DSM, increasing the response time, increasing the sensitivity coefficient for acceleration, or decreasing the sensitivity coefficient for deceleration can increase rear-end crash risk. In addition, if stable and unstable driving styles coexist, then their proportions have important influences on rear-end crash risk. These results imply that two critical factors affect shock waves, namely, driving behavior characteristics and proportion of different driving styles. Thus, a potential strategy for the adjustment of the proportions of unstable driving styles can attenuate shock waves and reduce rear-end crash risk to a certain extent. Moreover, a wide extent of driving behavior heterogeneity can attenuate shock waves and subsequently reduce rear-end crash risk. Overall, driving behavior heterogeneity has an important impact on rear-end crash risk. Exploring the effect of each driving behavior parameter on rear-end crash probability is useful for urban road traffic control, and it can provide improved understanding of abnormal driving behavior characteristics to minimize rear-end crash risks.
       
  • Impact evaluation of camera enforcement for traffic violations in Cali,
           Colombia, 2008–2014
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Diana Marcela Martínez-Ruíz, Andrés Fandiño-Losada, Antonio Ponce de Leon, David Arango-Londoño, Julio Cesar Mateus, Ciro Jaramillo-Molina, Francisco Javier Bonilla-Escobar, Harvy Vivas, Ward Vanlaar, María Isabel Gutiérrez-Martínez IntroductionCameras for detecting traffic violations have been used as a measure to improve road safety in different countries around the world. In Cali, Colombia, fixed cameras were installed in March 2012 on a number of roads and intersections. All camera devices are capable of detecting simultaneously the following traffic violations: driving over the speed limit, running a red light or stop sign, violation of the traffic ban schedule, and blocking the pedestrian crosswalk.ObjectiveTo evaluate the impact of camera enforcement of traffic violations in Cali, Colombia.MethodsA quasi-experimental difference-in-differences study with before and after measurements and a comparison group was conducted. We observed 38 intervention areas and 50 comparison areas (250 m radius), during 42 months before and 34 months after the installation of cameras. Effects were estimated with mixed negative binomial regression models.ResultsIn intervention areas, after 12 months, there was a reduction of 19.2% of all crashes and a 24.7% reduction of injury and fatal crashes. In comparison areas, this reduction was 15.0% for all crashes and 20.1% for injury and fatal crashes. After adjusted comparisons, intervention sites outperformed comparison sites with an additional yearly reduction of 5.3% (p = 0.045) for all crashes.ConclusionsThe use of cameras for detecting traffic violations seems to have a positive effect on the reduction of crashes in intervention areas. A beneficial spillover effect was found as well in comparison areas; but more evaluations are needed.
       
  • Risk of automated driving: Implications on safety acceptability and
           productivity
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Vinayak Dixit, Zhitao Xiong, Sisi Jian, Neeraj Saxena Autonomous Vehicles have captured the imagination of our society and have promised a future of safe and efficient mobility. However, there is a need to understand behaviour and its consequences in the use of autonomous vehicles. Using paradigms of behavioural and experimental economics, we show that risk attitudes play a role in acceptability of autonomous vehicles, productivity in autonomous vehicles and safety under risk of failures of autonomous systems. We found that risk attitudes and age have a significant impact on these. We believe these findings will help provide guidance to insurance agencies, licensing, vehicle design, and policies around automated vehicles.
       
  • Network screening for large urban road networks: Using GPS data and
           surrogate measures to model crash frequency and severity
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Joshua Stipancic, Luis Miranda-Moreno, Nicolas Saunier, Aurélie Labbe Crash frequency and injury severity are independent dimensions defining crash risk in road safety management and network screening. Traditional screening techniques model crashes using regression and historical crash data, making them intrinsically reactive. In response, surrogate measures of safety have become a popular proactive alternative. The purpose of this paper is to develop models for crash frequency and severity incorporating GPS-derived surrogate safety measures (SSMs) as predictive variables. SSMs based on vehicle manoeuvres and traffic flow were extracted from data collected in Quebec City. The mixed multivariate outcome is estimated using two models; a Full Bayes Spatial Negative Binomial model for crash frequency estimated using the Integrated Nested Laplace Approximation approach and a fractional Multinomial Logit model for crash severity. Model outcomes are combined to generate posterior expected crash frequency at each severity level and rank sites based on crash cost. The crash frequency model was accurate at the network scale, with the majority of proposed SSMs statistically significant at 95% confidence and the direction of their effect generally consistent with previous research. In the crash severity model, fewer variables were significant, yet the direction of the effect of all significant variables was again consistent with previous research. Correlations between rankings predicted by the mixed multivariate model and by the crash data were adequate for intersections (0.46) but were poorer for links (0.25). The ability to prioritize sites based on GPS data and SSMs rather than historical crash data represents a substantial contribution to the field of road safety.
       
  • Machines versus humans: People’s biased responses to traffic accidents
           involving self-driving vehicles
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Peng Liu, Yong Du, Zhigang Xu Although self-driving vehicles (SDVs) bring with them the promise of improved traffic safety, they cannot eliminate all crashes. Little is known about whether people respond crashes involving SDVs and human drivers differently and why. Across five vignette-based experiments in two studies (total N = 1267), for the first time, we witnessed that participants had a tendency to perceive traffic crashes involving SDVs to be more severe than those involving conventionally human-driven vehicles (HDVs) regardless of their severity (injury or fatality) or cause (SDVs/HDVs or others). Furthermore, we found that this biased response could be a result of people’s reliance on the affect heuristic. More specifically, higher prior negative affect tagged with an SDV (vs. an HDV) intensifies people’s negative affect evoked by crashes involving the SDV (vs. those involving the HDV), which subsequently results in higher perceived severity and lower acceptability of the crash. Our results imply that people’s over-reaction to crashes involving SDVs may be a psychological barrier to their adoption and that we may need to forestall a less stringent introduction policy that allows SDVs on public roads as it may lead to more crashes that could possibly deter people from adopting SDVs. We discuss other theoretical and practical implications of our results and suggest potential approaches to de-biasing people’s responses to crashes involving SDVs.
       
  • Macro-level traffic safety analysis in Shanghai, China
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Xuesong Wang, Qingya Zhou, Junguang Yang, Shikai You, Yang Song, Meigen Xue Continuing rapid growth in Shanghai, China, requires traffic safety to be considered at the earliest possible stage of transport planning. Macro-level traffic safety studies have been carried out extensively in many countries, but to date, few have been conducted in China. This study developed a macro-level safety model for 263 traffic analysis zones (TAZs) within the urban area of Shanghai in order to examine the relationship between traffic crash frequency and road network, traffic, socio-economic characteristics, and land use features. To account for the spatial correlations among TAZs, a Bayesian conditional autoregressive negative binomial model was estimated, linking crash frequencies in each TAZ to several independent variables. Modeling results showed that higher crash frequencies are associated with greater populations, road densities, total length of major and minor arterials, trip frequencies, and with shorter intersection spacing. The results from this study can help transportation planners and managers identify the crash contributing factors, and can lead to the development of improved safety planning and management.
       
  • Crash causes, countermeasures, and safety policy implications
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): David Shinar, Ben Gurion There are interrelationships between crash causes, countermeasures, and policy implications, but they are not necessarily direct and obvious. Part of the problem is the definition of a cause. The seminal 1979 Indiana University “Study of Accident Causes” has cemented some false assumptions that must be overcome to yield an effective crash countermeasures policy. The taxonomy of crash causes and the prevalence of different causes are determined by the investigators, who are biased in different ways. The prevalent notion that approximately 90 percent of the crashes are due to human errors or failures is due to a threshold bias, and the implied notion that 90 percent of the countermeasures should be directed at changing these behaviors is based on an erroneous assumption that the cure must be directly linked to the stated cause. A more balanced approach to the definition of a cause and to the search for crash countermeasures is needed, and the safe system approach appears to be a most promising one.
       
  • Powered two-wheeler crash scenario development
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Deniz Atalar, Pete Thomas Powered two wheeler (PTW) riders are a group of vulnerable road users that are overrepresented compared to other road user groups with regards to crash injury outcomes. The understanding of the dynamics that occur before a crash benefits in providing suitable countermeasures for said crashes. A clearer interpretation of which factors interact to cause collisions allows an understanding of the mechanisms that produce higher risk in specific situations in the roadway.Real world in-depth crash data provides detailed data which includes human, vehicular and environmental factors collected on site for crash analysis purposes. This study used macroscopic on-scene crash data collected in the UK between the years 2000–2010 as part of the “Road Accident In-depth Study” to analyse the factors that were prevalent in 428 powered two-wheeler crashes.A descriptive analysis and latent class cluster analysis was performed to identify the interaction between different crash factors and develop PTW scenarios based on this analysis. The PTW rider was identified as the prime contributor in 36% of the multiple vehicle crashes. Results identified seven specific scenarios, the main types of which identified two particular ‘looked but failed to see’ crashes and two types of single vehicle PTW crashes. In cases where the PTW lost control diagnosis failures were more common, for road users other than the PTW rider detection issues were of particular relevance.
       
  • Multivariate copula temporal modeling of intersection crash consequence
           metrics: A joint estimation of injury severity, crash type, vehicle damage
           and driver error
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Kai Wang, Tanmoy Bhowmik, Shamsunnahar Yasmin, Shanshan Zhao, Naveen Eluru, Eric Jackson This study employs a copula-based multivariate temporal ordered probit model to simultaneously estimate the four common intersection crash consequence metrics – driver error, crash type, vehicle damage and injury severity – by accounting for potential correlations due to common observed and unobserved factors, while also accommodating the temporal instability of model estimates over time. To this end, a comprehensive literature review of relevant studies was conducted; four different copula model specifications including Frank, Clayton, Joe and Gumbel were estimated to identify the dominant factors contributing to each crash consequence indicator; the temporal effects on model estimates were investigated; the elasticity effects of the independent variables with regard to all four crash consequence indicators were measured to express the magnitude of the effects of an independent variable on the probability change for each level of four indicators; and specific countermeasures were recommended for each of the contributing factors to improve the intersection safety.The model goodness-of-fit illustrates that the Joe copula model with the parameterized copula parameters outperforms the other models, which verifies that the injury severity, crash type, vehicle damage and driver error are significantly correlated due to common observed and unobserved factors and, accounting for their correlations, can lead to more accurate model estimation results. The parameterization of the copula function indicates that their correlation varies among different crashes, including crashes that occurred at stop-controlled intersections, four-leg intersections and crashes which involved drivers younger than 25. The model coefficient estimates indicate that the driver’s age, driving under the influence of drugs and alcohol, intersection geometry and control types, and adverse weather and light conditions are the most critical factors contributing to severe crash consequences. The coefficient estimates of four-leg intersections, yield and stop-controlled intersections and adverse weather conditions varied over time, which indicates that the model estimation of crash data may not be stable over time and should be accommodated in crash prediction analysis. In the end, relevant countermeasures corresponding to law enforcement and intersection infrastructure design are recommended to all of the contributing factors identified by the model. It is anticipated that this study can shed light on selecting valid statistical models for crash data analysis, identifying intersection safety issues, and helping develop effective countermeasures to improve intersection safety.
       
  • Examining traffic conflicts of up stream toll plaza area using
           vehicles’ trajectory data
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Lu Xing, Jie He, Mohamed Abdel-Aty, Qing Cai, Ye Li, Ou Zheng Despite the recognized benefits of electronic toll collection (ETC) system as an important part of toll plaza area, the mixed traffic of electronic toll collection (ETC) vehicles and manual toll collection (MTC) vehicles in the toll plaza diverging area are considered risky to vehicles, in which complex diverging and crossing behavior of vehicles would increase the collision risks. Therefore, it is vitally important to investigate the vehicle collision risk in the up stream toll plaza area. Video data are collected from a typical toll plaza in Nanjing, China, and vehicle trajectory data are extracted using an automated analysis system based on OpenCV. An extended Time-To-Collision (TTC) is proposed to evaluate the vehicle collision risk. Subsequently, the different effects on vehicle collision risk of vehicles with different toll collection types, target lanes and locations are compared. Furthermore, the random parameters logistic model is developed to investigate the effects of explanatory factors on the collision risk of vehicles diverging or adjusting their lane position. The results suggested that the MTC vehicles have the highest collision risk in the toll plaza diverging area and there are significant different effects on collision risk among vehicles with different target toll collection lanes. Further, more dangerous situations could be found for a vehicle if it is closer to the toll collection lanes and surrounded by heavy traffic. It is also confirmed that mixed traffic with MTC and ETC vehicles could increase the crash risk in the toll plaza diverging area. It is expected that the findings could help engineers and operators select the appropriate engineering and traffic control solutions to enhance the safety at the toll plaza diverging area.
       
  • Organization is also a “life form”: Organizational-level personality,
           job satisfaction, and safety performance of high-speed rail operators
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Fulei Chu, Yue Fu, Shuzhen Liu Although studies have suggested that personality can forecast safety performance at the individual level, the link between organizational-level personality and safety performance is rarely considered. On the basis of the Attraction-Selection-Attrition (ASA) theory, the present study investigated the direct and indirect effects of the organizational emergence of personality (Five-Factor Model) on individual-level outcomes (safety performance) in the high-speed rail industry. The sample consisted of 1035 high-speed rail operators in China. The results indicated that the effects of organizational-level personality on safety performance are similar to or stronger than the effects of individual-level personality. Specifically, organizational-level extraversion, agreeableness, and conscientiousness have significantly positive relationships with individual-level safety compliance and safety participation, while neuroticism has a significantly negative relationship with safety compliance and safety participation; the effect of openness to experience was not significant. Moreover, in terms of indirect effects, job satisfaction mediated the links of the four personality constructs (extraversion, agreeableness, neuroticism, and conscientiousness) with safety compliance and safety participation. These findings highlight the importance of organizational personality to improving employees’ safety performance in safety-critical organizations.
       
  • Game theoretic model for lane changing: Incorporating conflict risks
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): David Arbis, Vinayak V. Dixit The study employs a Quantal Response Equilibrium framework to model lane changing manoeuvres. Prior game theoretic studies in lane changing have pre-eminently assumed Nash equilibrium solutions with deterministic payoffs for actions. The study method involves developing expected utility models for drivers’ merge and give-way decisions. These utility models incorporate explanatory variables representing driver trajectories during a lane changing manoeuvre. The model parameters are estimated using maximum likelihood on lane changing data at a freeway on-ramp using the NGSIM dataset. Based on the estimated parameters it was concluded that longer acceleration lanes and reduction of speed limits on on-ramps could help significantly reduce likelihood of conflict. To demonstrate the robustness of the model, predictions of lane changing on an out-of-sample data were found to be reasonably accurate.
       
  • Effects of simulated mild vision loss on gaze, driving and interaction
           behaviors in pedestrian crossing situations
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Christian Lehsing, Florian Ruch, Felix M. Kölsch, Georg N. Dyszak, Christian Haag, Ilja T. Feldstein, Steven W. Savage, Alex R. Bowers PurposeInteraction is the process of behavior adaption between two or more participants primarily based on what they visually perceive. It is an important aspect of traffic participation and supports a safe and efficient flow of traffic. However, prior driving simulator studies investigating the effects of vision impairment have typically used pre-programmed pedestrians that did not interact with the human driver. In the current study we used a linked pedestrian and driving simulator setting to increase the ecological validity of the experimental paradigm. We evaluated the effects of mild vision loss on interactions between drivers and human-controlled, interactive pedestrians compared to preprogrammed, non-interactive pedestrians.MethodYoung subjects (mean age 31 years) wore safety goggles with diffusing filters that reduced visual acuity to 20/50 Snellen and contrast sensitivity to 1.49 log units. Two types of crossings (zebra vs. free lane) and two types of pedestrians (non-interactive vs. interactive) were presented to the driver using a multiple simulator setting. Gaze, safety and time series measures were analyzed to quantify the behavior of the participants during the different crossing situations.ResultsSimulated vision impairment significantly increased the time taken to first fixate on the pedestrian, but only had mild adverse effects on safety measures and subsequent interactions. By comparison, pedestrian type and crossing type were found to significantly affect interaction measures. In crossings with the interactive pedestrians the behavior adaption between the driver and the pedestrian took longer and was less correlated in contrast to the situations with the non-interactive pedestrian.ConclusionMild vision impairment (slightly worse than the common 20/40 requirement for driving) had little effect on interactions with pedestrians once they were detected and only had mild adverse consequences on driving safety. Time series measures were sensitive to differences in behavior adaption between road users depending on the level of interaction and type of crossing situation.
       
  • Cognitive failures in response to emotional contagion: Their effects on
           workplace accidents
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Laura Petitta, Tahira M. Probst, Valerio Ghezzi, Claudio Barbaranelli The purpose of this study was to examine contagion of positive and negative emotions among employees as an antecedent of cognitive failures and subsequent workplace accidents. Using emotional contagion theory and the neural model of emotion and cognition, we tested the proposition that higher contagion of anger (i.e., a negative emotion accompanied by dysfunctional cognition) would be associated with greater cognitive failures, whereas higher contagion of joy (i.e., a positive emotion accompanied by pleasant information processing, attention and positive cognition) would be associated with fewer cognitive failures. In turn, cognitive failures were predicted to be related to higher rates of subsequent workplace accidents. Using a two-wave lagged design, anonymous survey data collected from N = 390 working adults in the U.S. supported the hypothesized mediation model. Specifically, emotional contagion of anger positively predicted cognitive failures, whereas emotional contagion of joy negatively predicted cognitive failures. Furthermore, cognitive failures positively predicted experienced accidents and fully mediated the relationship between contagion of joy/anger and experienced accidents. These findings suggest that lapses in cognitive functioning may be prevented by positive emotions (and enhanced by negative emotions) that employees absorb during social interactions at work and represent a more proximal source of accidents in comparison to emotions. Theoretical and practical implications of these results are discussed in light of the globally rising rates of workplace accidents and related costs for safety.
       
  • The effects of auditory satellite navigation instructions and visual blur
           on road hazard perception
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): P. Lacherez, S. Virupaksha, J.M. Wood, M.J. Collins The distracting effects of mobile telephone use while driving are well known, however the effects of other sources of distraction, such as auditory navigation devices, are less well understood. Whether the effects of auditory distraction might interact with other sensory impairments, such as vision impairment, is of interest given that visual impairment is relatively common within the population, particularly as a result of uncorrected refractive error. In this experiment, 20 current drivers (mean age of 29.4 ± 3.2 years), binocularly viewed video recordings of traffic scenes presented as part of the Hazard Perception Test and responded to potential hazards within the traffic scenes. Half of the presented scenes included auditory navigation instructions as an auditory distractor. Additionally, some of the scenes were viewed through optical lenses to induce different levels of refractive blur (+0.50 DS, +1.00 DS and +2.00 DS). Hazard perception response times increased significantly (p 
       
  • Is the safety-in-numbers effect still observed in areas with low
           pedestrian activities' A case study of a suburban area in the United
           States
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Jaeyoung Lee, Mohamed Abdel-Aty, Pengpeng Xu, Yaobang Gong In previous studies, the safety-in-numbers effect has been found, which is a phenomenon that when the number of pedestrians or cyclists increases, their crash rates decrease. The previous studies used data from highly populated areas. It is questionable that the safety-in-numbers effect is still observed in areas with a low population density and small number of pedestrians. Thus, this study aims at analyzing pedestrian crashes in a suburban area in the United States and exploring if the safety-in-numbers effect is also observed. We employ a Bayesian random-parameter Poisson-lognormal model to evaluate the safety-in-numbers effects of each intersection, which can account for the heterogeneity across the observations. The results show that the safety-in-numbers effect were found only at 32 intersections out of 219. The intersections with the safety-in-numbers effect have relatively larger pedestrian activities whereas those without the safety-in-numbers effect have extremely low pedestrian activities. It is concluded that just encouraging walking might result in serious pedestrian safety issues in a suburban area without sufficient pedestrian activities. Therefore, it is plausible to provide safe walking environment first with proven countermeasures and a people-oriented policy rather than motor-oriented. After safe walking environments are guaranteed and when people recognize that walking is safe, more people will consider walking for short-distance trips. Eventually, increased pedestrian activities will result in the safety-in-numbers effects and walking will be even further safer.
       
  • Self-reported handheld device use while driving
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Karl Kim, Jiwnath Ghimire, Pradip Pant, Eric Yamashita In spite of research and awareness of the hazards associated with handheld mobile device use while driving, many motorists continue to engage in this risky behavior. The mobile device use while driving has a detrimental effect on the operation of the vehicle. It contributes significantly to distraction which is a leading cause of accidents. Especially, the use of text messaging and the dialing of a 10-digit number while driving can be attributable to crash risks. Phone use bans have a positive role in reducing mobile phone use for texting while operating vehicles. There are limited studies on whether drivers admit to the use of handheld devices while driving. The aim of this study was to identify the experiences, practices, and attitudes of handheld device use while driving. A total of 337 respondents nationwide replied to the survey on the attitudes and self-reported behaviors of handheld device use while driving. In the survey, the characteristics of handheld device users, use of handheld devices, and the differences in self-reported behaviors across states with and without device use restrictions were compared. The perceptions and experiences of device users are also examined. Based on the background of device users and their attitudes, a multivariate logistic regression is used to identify the characteristics of those who use handheld devices while driving. The model is relevant to this research because it allows the consideration and comparison of many variables to identify the attitudes of people towards distracted driving. The affirmative self-reporting of 59 percent of the respondents is a surprising result given that there are state bans on texting and the use of handheld mobile phones while driving. Older drivers are least likely to engage in these behaviors, compared to younger drivers and adult drivers. Based on the findings, targeted educational and enforcement campaigns to reduce device use during driving are suggested. Additional promising areas for further inquiry and research are also proposed.
       
  • Mobile phone involvement, beliefs, and texting while driving in Ukraine
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): T. Hill, M.J.M. Sullman, A.N. Stephens There is extensive evidence that using a mobile phone whilst driving is one of the biggest contributors to driver distraction, which in turn increases the risk of motor vehicle collisions. Whilst most of the developed countries have been trying to deter this behaviour through legislation, enforcement and educational campaigns, in Ukraine, where the road fatality rate is the highest in Europe, this issue has only recently become publicised. The present study examined psychological factors that are associated with hand-held mobile phone use while driving among a sample of Ukrainian drivers, in particular writing or reading a text message while driving. This included drivers’ behavioural, normative, and control beliefs relating to mobile phone use while driving, as well as the degree to which using a mobile phone is integral to one’s everyday life (measured using the Mobile Phone Involvement Questionnaire; MPIQ). Almost one quarter to one third of the sample reported using their phone on a daily basis to write (22.2%) or read (38.2%) text messages while driving. A binary logistic regression showed that gender, higher MPIQ scores, perceived approval from family members, lower perceived likelihood of receiving traffic fines and less demanding traffic conditions were all significantly associated with mobile phone use while driving. These results suggest that dependence upon a mobile phone in everyday life may be an important factor to consider when developing interventions to reduce hand-held mobile phone use while driving.
       
  • Review and ranking of crash risk factors related to the road
           infrastructure
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Eleonora Papadimitriou, Ashleigh Filtness, Athanasios Theofilatos, Apostolos Ziakopoulos, Claire Quigley, George Yannis The objective of this paper is the review and comparative assessment of infrastructure related crash risk factors, with the explicit purpose of ranking them based on how detrimental they are towards road safety (i.e. crash risk, frequency and severity). This analysis was carried out within the SafetyCube project, which aimed to identify and quantify the effects of risk factors and measures related to behaviour, infrastructure or vehicles, and integrate the results in an innovative road safety Decision Support System (DSS). The evaluation was conducted by examining studies from the existing literature. These were selected and analysed using a specifically designed common methodology. Infrastructure risk factors were structured in a hierarchical taxonomy of 10 areas with several risk factors in each area (59 specific risk factors in total), examples include: alignment features (e.g. horizontal-vertical alignment deficiencies), cross-section characteristics (e.g. superelevation, lanes, median and shoulder deficiencies), road surface deficiencies, workzones, junction deficiencies (interchange and at-grade) etc. Consultation with infrastructure stakeholders (international organisations, road authorities, etc.) took place in dedicated workshops to identify user needs for the DSS, as well as “hot topics” of particular importance. The following analysis methodology was applied to each infrastructure risk factor: (i) A search for relevant international literature, (ii) Selection of studies on the basis of rigorous criteria, (iii) Analysis of studies in terms of design, methods and limitations, (iv) Synthesis of findings - and meta-analysis, when feasible. In total 243 recent and high quality studies were selected and analysed. Synthesis of results was made through 39 ‘Synopses’ (including 4 original meta-analyses) on individual risk factors or groups of risk factors. This allowed the ranking of infrastructure risk factors into three groups: risky (11 risk factors), probably risky (18 risk factors), and unclear (7 risk factors).
       
  • What is the difference in driver’s lateral control ability during
           naturalistic distracted driving and normal driving' A case study on a
           real highway
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Chang Wang, Zhen Li, Rui Fu, Yingshi Guo, Wei Yuan Driver distraction is widely recognized as a major contributor to traffic crashes. Although the effect of distraction on simulated driving performance has been studied extensively, comparatively little research based on field tests has been performed on the effects of high driving speeds on lateral driving performance during naturalistic distraction (the driver was unaware of the research topic). In this study, an instrumented vehicle is used to examine the impact of speed and naturalistic visual distraction (rear vehicle’s velocity and relative distance estimation) on a driver’s ability to keep in the lane. Similar to results from previous studies, visual distraction resulted in an impaired ability to keep in a lane compared to normal driving. Further investigation of steering control parameters showed an increase in steering wheel reversal rates (SRRs at 1.3° and 2.5° levels) and the standard deviation of steering wheel acceleration (SDSWA). The results of this study indicated that the standard deviation of lane positioning (SDLP) and trajectory offset (TO) increased as speed increased. As speed increased, the growth rates of SDLP and TO in the visual distraction task were the same as that in normal driving. Moreover, the SRRs and steering wheel acceleration (SWA) decreased with increased speed. As speed increased, the growth rates of SRRs and SWA during a visual distraction task were the same as that during normal driving. These results suggest that driving speed has a similar effect on driving performance during both distracted driving and normal driving.
       
  • Exploring crash mechanisms with microscopic traffic flow variables: A
           hybrid approach with latent class logit and path analysis models
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Rongjie Yu, Yin Zheng, Mohamed Abdel-Aty, Zhen Gao Understanding the occurrence mechanisms of crashes is critical for traffic safety improvement. Efforts have been investigated to reveal the crash mechanisms and analyze the contributing factors from the aspects of vehicle, driver, and operational perspectives. In this study, special attention has been paid to the operational level analyses while bridging the research gaps of: (1) failing to identify the heterogeneous impact of microscopic traffic flow variables on crash occurrence, and (2) focusing on correlation effects without further investigations for the causal relationships. A hybrid modeling approach with latent class logit (LCL) and path analysis (PA) models was proposed to account for the heterogeneous influencing effects and reveal the causal relationships between crash occurrence and microscopic traffic flow variables. Data from Shanghai urban expressway system were utilized for the empirical analyses. First, the LCL model has concluded four latent subsets of crash occurrence influencing factors. Then, PA models were conducted to identify the concurrent relationships (direct and indirect eff ;ects) for the four sets of crash occurrence influencing factors separately. Finally, the results of the LCL model and PA models were compared and the crash-prone scenarios were inferred. And the potential safety improvement countermeasures were discussed.
       
  • A comprehensive and unified framework for analysing the effects on
           injuries of measures influencing speed
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Rune Elvik This paper proposes a comprehensive and unified framework for analysing the impacts on traffic injury of measures influencing speed. The key tool for analysis is a specification of the speed distribution, which in most cases closely approximates a standard normal distribution. The speed distribution can be represented, for example, by twelve intervals each comprising one half standard deviation. The exponential model of the relationship between speed and the number of injured road users is applied to estimate the expected injury rate for drivers travelling at the mean speed of any part of the distribution. The relationship between individual driver speed and accident involvement is then incorporated into the speed distribution. A speed distribution specified this way represents both the mean speed of traffic and the variation in speed-related risk between drivers. Impacts of changes in speed that can be modelled include: (1) Shifting the whole speed distribution, (2) Compressing the upper end of the speed distribution, (3) Enlarging or reducing the variance of the speed distribution, (4) Selective changes in specific regions of the speed distribution. Examples are given of how knowledge of the impacts of measures on speed can be translated into expected changes in the number of injured road users by relying on the analytic framework.
       
  • Exploring the impact of "soft blocking" on smartphone usage of young
           drivers
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Gila Albert, Tsippy Lotan Smartphone usage while driving, and particularly texting, are well recognized as a major road safety concern. This paper presents an attempt to evaluate the effect of countermeasures aimed at mitigating this usage. These countermeasures, which are automatically activated, may be considered "soft blockers": silencing and hiding notifications, as well as sending an automatic reply to the person trying to contact the driver. A naturalistic study was conducted with 167 young Israeli drivers, who installed a research-oriented smartphone app, which continuously monitored their smartphones usage while driving and, in addition, activated “soft blocking” in the study’s intervention stage. The evaluation is based on measures which capture the number of times drivers "touch" their smartphone screens, and on the vehicle’s speed when these screen-touches occur. The results, based on 6633 hours of driving logged on 23,019 trips, indicate that a reduction of approximately 20% was obtained in the average number of screen-touches during the intervention stage of the study; that is, in the experimental groups but also in the control group, which was merely monitored. In addition, when young drivers touched the screen, the vehicle was more likely not in motion. The current paper highlights the potential of “soft blockers”, as well as the awareness of being monitored, for mitigating smartphone usage while driving.
       
  • Regional disparities in road traffic injury rates involving elementary and
           junior high school children while commuting among Japan’s 47 prefectures
           between 2004 and 2013
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Haruhiko Inada, Jun Tomio, Masao Ichikawa, Shinji Nakahara ObjectivesTo investigate the extent and patterns of regional disparities of road traffic injury rates involving elementary and junior high school children while commuting among Japan’s 47 prefectures.MethodsWe conducted a cross-sectional ecological study using the national police data for 2004–2013 on the number of children who were killed or seriously injured (KSI) in traffic collisions stratified by prefecture, grade, mode of transport, and purpose of trip (commuting or non-commuting). We calculated stratified KSI rates by dividing the number of KSI cases by the corresponding number of children and presented these rates for the 47 prefectures. Also, for pedestrian elementary school children and cyclist junior high school children, we regressed the KSI rates while commuting by prefecture on the non-commuting KSI rates and the proportion of people who live in the urban, densely inhabited districts.ResultsThere were 6463 KSI cases while commuting. The ratios of the highest KSI rate to the lowest KSI rate among prefectures were 12, 30, and 58 for pedestrian elementary school children and pedestrian and cyclist junior high school children, respectively. The non-commuting KSI rates and the proportion of those living in densely inhabited districts were positively and inversely associated with the commuting KSI rates, respectively. The analysis of the residuals of the regression models did not identify prefectures with significantly higher or lower KSI rates while commuting than others.ConclusionsThere were large inter-prefecture disparities in the KSI rates while commuting, and the disparity was especially large among cyclist junior high school children.
       
  • Drinking and driving among adults in the United States: Results from the
           2012–2013 national epidemiologic survey on alcohol and related
           conditions-III
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Amy Z. Fan, Bridget F. Grant, W. June Ruan, Boji Huang, S. Patricia Chou Despite the seriousness of alcohol-impaired driving (A-ID) very few national surveys on reported A-ID have been conducted since the early 2000s. This study examined 12-month prevalences of driver-based A-ID and passenger-based alcohol-related practices in a large representative sample of the U.S. population. Twelve-month prevalences of drinking while driving and driving after drinking too much were 5.7% and 3.9%, respectively. Corresponding prevalences of having an accident while intoxicated and having an accident with an injury while intoxicated were 0.6% and 0.2%, respectively. Twelve-month prevalences of riding as a passenger with a drinking driver and riding as a passenger while drinking were 7.0% and 10.7%, respectively. In general, sociodemographic characteristics of individuals more vulnerable to all of these A-ID practices were similar: men, Whites, Blacks and Native Americans, younger and middle-aged adults, upper socioeconomic status, being never or previously married, and residing in the Midwest. Results of this study underscore the importance of assessing driver-based A-ID and passenger-based alcohol-related practices and the need to target prevention and intervention programs to reduce these practices among those subgroups of the U.S. population most vulnerable to them.
       
  • Spatial variation in teens’ crash rate reduction following the
           implementation of a graduated driver licensing program in Michigan
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Jason E. Goldstick, Patrick M. Carter, Farideh Almani, Shannon J. Brines, Jean T. Shope Motor vehicle crashes are a leading cause of injury, and teen drivers contribute disproportionately to that burden. Graduated Driver Licensing (GDL) programs are effective at reducing teen crash risk, but teen crash rates remain high. Between-state variation in the teen crash rate reduction following GDL implementation has been documented, but this is the first study to examine small-area variation in such a reduction. Fusing together crash data from the Michigan State Police, census data, and organizational data (alcohol outlet, movie theatre, and school locations), we analyzed spatial correlates of teen injury crash, and place-based features that modified the injury crash rate difference following GDL implementation. Specifically, using census-based units, we estimated changes in injury crash rates among teens using negative binomial regression controlling for spatial autocorrelation, and tested whether any measured spatial characteristics modified the crash rate change in the pre versus post GDL periods. There was a substantial reduction in teen crashes after GDL implementation (RR = 0.66, 95%CI: [0.65, 0.67]), and this effect was robust across gender and time-of-day (light/dark). We found evidence that this reduction varied across space; areas with more alcohol outlets corresponded to a larger daytime crash rate reduction post-GDL, while areas near schools corresponded to a smaller daytime crash rate reduction. Concentrations of movie theatres corresponded to larger post-GDL crash rate reductions after dark. Maximizing the substantial successes of GDL programs requires understanding why crash rate reductions were larger in some areas following GDL implementation, and harnessing that understanding to improve its effectiveness across a state, focusing on identifying priorities for improving driver training (e.g., by parents and driver educators), law enforcement, and future policy changes to current GDL laws.
       
  • Factors impacting bicyclist lateral position and velocity in proximity to
           commercial vehicle loading zones: Application of a bicycling simulator
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Masoud Ghodrat Abadi, David S. Hurwitz, Manali Sheth, Edward McCormack, Anne Goodchild There is little research on the behavioral interaction between bicycle lanes and commercial vehicle loading zones (CVLZ) in the United States. These interactions are important to understand, to preempt increasing conflicts between truckers and bicyclists. In this study, a bicycling simulator experiment examined bicycle and truck interactions. The experiment was successfully completed by 48 participants. The bicycling simulator collected data regarding a participant’s velocity and lateral position. Three independent variables reflecting common engineering approaches were included in this experiment: pavement marking (L1: white lane markings with no supplemental pavement color, termed white lane markings, L2: white lane markings with solid green pavement applied on the conflict area, termed solid green, and L3: white lane markings with dashed green pavement applied on the conflict area, termed dashed green), signage (L1: No sign and L2: a truck warning sign), and truck maneuver (L1: no truck in CVLZ, L2: truck parked in CVLZ, and L3: truck pulling out of CVLZ).The results showed that truck presence does have an effect on bicyclist’s performance, and this effect varies based on the engineering and design treatments employed. Of the three independent variables, truck maneuvering had the greatest impact by decreasing mean bicyclist velocity and increasing mean lateral position. It was also observed that when a truck was present in a CVLZ, bicyclists had a lower velocity and lower divergence from right-edge of bike lane on solid green pavement, and a higher divergence from the right-edge of bike lane was observed when a warning sign was present.Graphical abstractGraphical abstract for this article
       
  • Effects of time of day and taxi route complexity on navigation errors: An
           experimental study
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Xiaoyan Zhang, Xingda Qu, Hongjun Xue, Da Tao, Tao Li This study aimed to evaluate the effects of time of day and taxi route complexity on navigation errors. Nine pilots participated in the experiment. Four testing conditions defined by time of day conditions (i.e., nighttime versus daytime) and taxi route complexity (i.e., more complex versus less complex) were examined. Participants were instructed to perform simulated taxiing tasks in each of the testing conditions. Navigation errors during taxiing were counted. In addition, eye movement measures can reflect pilots’ attention allocation, situation awareness and mental workload that are closely related to the risk of navigation errors. Thus, eye movement measures including fixation rate, average fixation duration and average pupil area were also selected as dependent variables. We found that navigation errors were fewer at night compared to in daytime. This could be explained by the finding that pilots paid more attention to the environmental clues out of the window at night, inducing better situation awareness for accurate taxiing. More complex taxi route was found to be associated with more navigation errors, but participants' visual behaviors were consistent between route complexity conditions, indicating that pilots’ visual operation strategies did not contribute to the increased number of navigation errors in the more complex taxi route condition.
       
  • Temporal patterns of driving fatigue and driving performance among male
           taxi drivers in Hong Kong: A driving simulator approach
    • Abstract: Publication date: April 2019Source: Accident Analysis & Prevention, Volume 125Author(s): Fanyu Meng, S.C. Wong, Wei Yan, Y.C. Li, Linchuan Yang This study uses a questionnaire survey and a driving simulator test to investigate the temporal patterns of variations in driving fatigue and driving performance in 50 male taxi drivers in Hong Kong. Each driver visited the laboratory three times: before, during, and after a working shift. The survey contained a demographic questionnaire and the Brief Fatigue Inventory. A following-braking simulator test session was conducted at two speeds (50 and 80 km/h) by each driver at each of his three visits, and the driver’s performance in brake reaction, lane control, speed control, and steering control were recorded. A random-effects modeling approach was incorporated to address the unobserved heterogeneity caused by the repeated measures. In the results, a recovery effect and a lagging effect were defined for the driving fatigue and performance measures because their temporal patterns were concavely quadratic and had a 1-hour delay compared to the temporal patterns of occupied taxi trips and taxi crash risk in Hong Kong. Demographic variables, such as net income and driver age, also had significant effects on the measured driving fatigue and performance. Policies regarding taxi management and operation based on the modeling results are proposed to alleviate the taxi safety situation in Hong Kong and worldwide.
       
  • 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.
       
  • Full Bayesian conflict-based models for real time safety evaluation of
           signalized intersections
    • Abstract: Publication date: Available online 5 October 2018Source: Accident Analysis & PreventionAuthor(s): Mohamed Essa, Tarek Sayed Existing advanced traffic management and emerging connected vehicles (CVs) technology can generate considerable amount of data on vehicle positions and trajectories. This data can be used for real-time safety optimization of intersections. To achieve this, it is essential to first understand how changes in signal control affect safety in real-time. This paper develops conflict-based safety performance functions (SPFs) of signalized intersections at the cycle level using multiple traffic conflict indicators. The developed SPFs relate various dynamic traffic parameters to the number of rear-end conflicts at the signal cycle. The traffic parameters included: queue length, shock wave speed and area, and the platoon ratio. The Time-to-Collision, the Modified-Time-to-Collision, and the Deceleration Rate to Avoid the Crash were used as traffic conflict indicators. Traffic video-data collected from six signalized intersections was used in the analysis. The SPFs were developed using the Full Bayesian approach to address the unobserved heterogeneity and the variation among different sites. Overall, the results showed that all the developed SPFs have good fit with all explanatory variables being statistically significant. Also, the highest conflict frequency was noticed at the beginning of the green time, while the highest conflict severity was noticed at the beginning of the red time. Lastly, the results can be used most beneficially in real-time safety optimization of signalized intersection.
       
  • Comparison of univariate and two-stage approaches for estimating crash
           frequency by severity—Case study for horizontal curves on two-lane rural
           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.
       
  • 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.
       
  • Corrigendum to “A farewell to brake reaction times'
           Kinematics-dependent brake response in naturalistic rear-end
           emergencies” [Accid. Anal. Prev. 95 (2016) 209–226]
    • Abstract: Publication date: Available online 15 June 2018Source: Accident Analysis & PreventionAuthor(s): Gustav Markkula, Johan Engström, Johan Lodin, Jonas Bärgman, Trent Victor
       
  • Evaluation of safety effect of turbo-roundabout lane dividers using
           floating car data and video observation
    • Abstract: Publication date: Available online 1 June 2018Source: Accident Analysis & PreventionAuthor(s): Mariusz Kieć, Jiří Ambros, Radosław Bąk, Ondřej Gogolín Roundabouts are one of the safest types of intersections. However, the needs to meet the requirements of operation, capacity, traffic organization and surrounding development lead to a variety of design solutions. One of such alternatives are turbo-roundabouts, which simplify drivers’ decision making, limit lane changing in the roundabout, and induce low driving speed thanks to raised lane dividers. However, in spite of their generally positive reception, the safety impact of turbo-roundabouts has not been sufficiently studied. Given the low number of existing turbo-roundabouts and the statistical rarity of accident occurrence, the prevalent previously conducted studies applied only simple before-after designs or relied on traffic conflicts in micro-simulations. Nevertheless, the presence of raised lane dividers is acknowledged as an important feature of well performing and safe turbo-roundabouts.Following the previous Polish studies, the primary objective of the present study was assessment of influence of presence of lane dividers on road safety and developing a reliable and valid surrogate safety measure based on field data, which will circumvent the limitations of accident data or micro-simulations. The secondary objective was using the developed surrogate safety measure to assess and compare the safety levels of Polish turbo-roundabout samples with and without raised lane dividers.The surrogate safety measure was based on speed and lane behaviour. Speed was obtained from video observations and floating car data, which enabled the construction of representative speed profiles. Lane behaviour data was gathered from video observations.The collection of the data allowed for a relative validation of the method by comparing the safety performance of turbo-roundabouts with and without raised lane dividers. In the end, the surrogate measure was applied for evaluation of safety levels and enhancement of the existing safety performance functions, which combine traffic volumes, and speeds as a function of radii). The final models may help quantify the safety impact of different turbo-roundabout solutions.
       
  • Evaluation of surrogate measures for pedestrian trips at intersections and
           crash modeling
    • Abstract: Publication date: Available online 31 May 2018Source: Accident Analysis & PreventionAuthor(s): Jaeyoung Lee, Mohamed Abdel-Aty, Imran Shah Pedestrians are considered the most vulnerable road users who are directly exposed to traffic crashes. With a view to addressing the growing concern of pedestrian safety, Federal and local governments aim at reducing pedestrian-involved crashes. Nevertheless, pedestrian volume data are rarely available even though they among the most important factors to identify pedestrian safety. Thus, this study aims at identifying surrogate measures for pedestrian exposure at intersections. A two-step process is implemented: the first step is the development of Tobit and generalized linear models for predicting pedestrian trips (i.e., exposure models). In the second step, negative binomial and zero inflated negative binomial models were developed for pedestrian crashes using the predicted pedestrian trips. The results indicate that among various exposure models the Tobit model performs the best in describing pedestrian exposure. The identified exposure-relevant factors are the presence of schools, car-ownership, pavement condition, sidewalk width, bus ridership, intersection control type and presence of sidewalk barrier. It was also found that the negative binomial model with the predicted pedestrian trips and that with the observed pedestrian trips perform equally well for estimating pedestrian crashes. Also, the difference between the observed and the predicted pedestrian trips does not appear as statistically significant, according to the results of the t-test and Wilcoxon signed-rank test. It is expected that the methodologies using predicted pedestrian trips or directly including pedestrian surrogate exposure variables can estimate safety performance functions for pedestrian crashes even though when pedestrian trip data is not available.
       
  • 10th International Conference on managing fatigue: Managing fatigue to
           improve safety, wellness, and effectiveness
    • Abstract: Publication date: Available online 19 May 2018Source: Accident Analysis & PreventionAuthor(s): Jeffrey S. Hickman, Richard J. Hanowski, Jana Price, J. Erin Mabry
       
  • How much is left in your “sleep tank”' Proof of concept for a
           simple model for sleep history feedback
    • Abstract: Publication date: Available online 7 May 2018Source: Accident Analysis & PreventionAuthor(s): Jillian Dorrian, Steven Hursh, Lauren Waggoner, Crystal Grant, Maja Pajcin, Charlotte Gupta, Alison Coates, David Kennaway, Gary Wittert, Leonie Heilbronn, Chris Della Vedova, Siobhan Banks Technology-supported methods for sleep recording are becoming increasingly affordable. Sleep history feedback may help with fatigue-related decision making – Should I drive' Am I fit for work' This study examines a “sleep tank” model (SleepTank™), which is analogous to the fuel tank in a car, refilled by sleep, and depleted during wake. Required inputs are sleep period time and sleep efficiency (provided by many consumer-grade actigraphs). Outputs include suggested hours remaining to “get sleep” and percentage remaining in tank (Tank%). Initial proof of concept analyses were conducted using data from a laboratory-based simulated nightshift study. Ten, healthy males (18–35y) undertook an 8h baseline sleep opportunity and daytime performance testing (BL), followed by four simulated nightshifts (2000 h–0600 h), with daytime sleep opportunities (1000 h–1600 h), then an 8 h night-time sleep opportunity to return to daytime schedule (RTDS), followed by daytime performance testing. Psychomotor Vigilance Task (PVT) and Karolinska Sleepiness Scale were performed at 1200 h on BL and RTDS, and at 1830 h, 2130 h 0000 h and 0400 h each nightshift. A 40-minute York Driving Simulation was performed at 1730 h, 2030 h and 0300 h on each nightshift. Model outputs were calculated using sleep period timing and sleep efficiency (from polysomnography) for each participant. Tank% was a significant predictor of PVT lapses (p 
       
  • Effects of strategic early-morning caffeine gum administration on
           association between salivary alpha-amylase and neurobehavioural
           performance during 50 h of sleep deprivation
    • Abstract: Publication date: Available online 7 May 2018Source: Accident Analysis & PreventionAuthor(s): Maja Pajcin, Jason M White, Siobhan Banks, Jill Dorrian, Gemma M Paech, Crystal L Grant, Kayla Johnson, Katie Tooley, Eugene Aidman, Justin Fidock, Gary H Kamimori, Chris B Della Vedova Self-assessment is the most common method for monitoring performance and safety in the workplace. However, discrepancies between subjective and objective measures have increased interest in physiological assessment of performance. In a double-blind placebo-controlled study, 23 healthy adults were randomly assigned to either a placebo (n = 11; 5 F, 6 M) or caffeine condition (n = 12; 4 F, 8 M) while undergoing 50 h (i.e. two days) of total sleep deprivation. In previous work, higher salivary alpha-amylase (sAA) levels were associated with improved psychomotor vigilance and simulated driving performance in the placebo condition. In this follow-up article, the effects of strategic caffeine administration on the previously reported diurnal profiles of sAA and performance, and the association between sAA and neurobehavioural performance were investigated. Participants were given a 10 h baseline sleep opportunity (monitored via standard polysomnography techniques) prior to undergoing sleep deprivation (total sleep time: placebo = 8.83 ± 0.48 h; caffeine = 9.01 ± 0.48 h). During sleep deprivation, caffeine gum (200 mg) was administered at 01:00 h, 03:00 h, 05:00 h, and 07:00 h to participants in the caffeine condition (n = 12). This strategic administration of caffeine gum (200 mg) has been shown to be effective at maintaining cognitive performance during extended wakefulness. Saliva samples were collected, and psychomotor vigilance and simulated driving performance assessed at three-hour intervals throughout wakefulness. Caffeine effects on diurnal variability were compared with previously reported findings in the placebo condition (n = 11). The impact of caffeine on the circadian profile of sAA coincided with changes in neurobehavioural performance. Higher sAA levels were associated with improved performance on the psychomotor vigilance test during the first 24 h of wakefulness in the caffeine condition. However, only the association between sAA and response speed (i.e. reciprocal-transform of mean reaction time) was consistent across both days of sleep deprivation. The association between sAA and driving performance was not consistent across both days of sleep deprivation. Results show that the relationship between sAA and reciprocal-transform of mean reaction time on the psychomotor vigilance test persisted in the presence of caffeine, however the association was relatively weaker as compared with the placebo condition.
       
  • 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.
       
  • 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.
       
 
 
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