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Publisher: Elsevier   (Total: 3183 journals)

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Showing 1 - 200 of 3183 Journals sorted alphabetically
Academic Pediatrics     Hybrid Journal   (Followers: 37, SJR: 1.655, CiteScore: 2)
Academic Radiology     Hybrid Journal   (Followers: 25, SJR: 1.015, CiteScore: 2)
Accident Analysis & Prevention     Partially Free   (Followers: 101, SJR: 1.462, CiteScore: 3)
Accounting Forum     Hybrid Journal   (Followers: 27, SJR: 0.932, CiteScore: 2)
Accounting, Organizations and Society     Hybrid Journal   (Followers: 38, SJR: 1.771, CiteScore: 3)
Achievements in the Life Sciences     Open Access   (Followers: 5)
Acta Anaesthesiologica Taiwanica     Open Access   (Followers: 7)
Acta Astronautica     Hybrid Journal   (Followers: 433, SJR: 0.758, CiteScore: 2)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 2)
Acta Biomaterialia     Hybrid Journal   (Followers: 27, SJR: 1.967, CiteScore: 7)
Acta Colombiana de Cuidado Intensivo     Full-text available via subscription   (Followers: 3)
Acta de Investigación Psicológica     Open Access   (Followers: 3)
Acta Ecologica Sinica     Open Access   (Followers: 11, SJR: 0.18, CiteScore: 1)
Acta Histochemica     Hybrid Journal   (Followers: 3, SJR: 0.661, CiteScore: 2)
Acta Materialia     Hybrid Journal   (Followers: 295, SJR: 3.263, CiteScore: 6)
Acta Mathematica Scientia     Full-text available via subscription   (Followers: 5, SJR: 0.504, CiteScore: 1)
Acta Mechanica Solida Sinica     Full-text available via subscription   (Followers: 9, SJR: 0.542, CiteScore: 1)
Acta Oecologica     Hybrid Journal   (Followers: 12, SJR: 0.834, CiteScore: 2)
Acta Otorrinolaringologica (English Edition)     Full-text available via subscription  
Acta Otorrinolaringológica Española     Full-text available via subscription   (Followers: 2, SJR: 0.307, CiteScore: 0)
Acta Pharmaceutica Sinica B     Open Access   (Followers: 1, SJR: 1.793, CiteScore: 6)
Acta Poética     Open Access   (Followers: 4, SJR: 0.101, CiteScore: 0)
Acta Psychologica     Hybrid Journal   (Followers: 25, 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: 7, 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: 15, 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: 9, 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: 177, 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: 9, SJR: 0.277, CiteScore: 1)
Advances in Agronomy     Full-text available via subscription   (Followers: 16, SJR: 2.384, CiteScore: 5)
Advances in Anesthesia     Full-text available via subscription   (Followers: 29, 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: 11, 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: 15, 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: 5)
Advances in Cellular and Molecular Biology of Membranes and Organelles     Full-text available via subscription   (Followers: 14)
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: 13)
Advances in Digestive Medicine     Open Access   (Followers: 12)
Advances in DNA Sequence-Specific Agents     Full-text available via subscription   (Followers: 7)
Advances in Drug Research     Full-text available via subscription   (Followers: 26)
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: 49, 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: 65, 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: 20, 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: 25, SJR: 0.368, CiteScore: 1)
Advances in Heterocyclic Chemistry     Full-text available via subscription   (Followers: 11, SJR: 0.749, CiteScore: 3)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 23)
Advances in Imaging and Electron Physics     Full-text available via subscription   (Followers: 3, 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: 20, SJR: 0.88, CiteScore: 2)
Advances in Mathematics     Full-text available via subscription   (Followers: 12, 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: 6)
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: 18, 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: 17)
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: 9, 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: 418, 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: 13, SJR: 0.555, CiteScore: 2)
Advances in the Study of Behavior     Full-text available via subscription   (Followers: 36, SJR: 2.208, CiteScore: 4)
Advances in Veterinary Medicine     Full-text available via subscription   (Followers: 20)
Advances in Veterinary Science and Comparative Medicine     Full-text available via subscription   (Followers: 15)
Advances in Virus Research     Full-text available via subscription   (Followers: 5, SJR: 2.262, CiteScore: 5)
Advances in Water Resources     Hybrid Journal   (Followers: 53, SJR: 1.551, CiteScore: 3)
Aeolian Research     Hybrid Journal   (Followers: 6, SJR: 1.117, CiteScore: 3)
Aerospace Science and Technology     Hybrid Journal   (Followers: 373, 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: 467, 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: 44, 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: 58, 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: 2, SJR: 0.604, CiteScore: 3)
Alexandria J. of Medicine     Open Access   (Followers: 1, SJR: 0.191, CiteScore: 1)
Algal Research     Partially Free   (Followers: 11, SJR: 1.142, CiteScore: 4)
Alkaloids: Chemical and Biological Perspectives     Full-text available via subscription   (Followers: 2)
Allergologia et Immunopathologia     Full-text available via subscription   (Followers: 1, SJR: 0.504, CiteScore: 1)
Allergology Intl.     Open Access   (Followers: 5, SJR: 1.148, CiteScore: 2)
Alpha Omegan     Full-text available via subscription   (SJR: 3.521, CiteScore: 6)
ALTER - European J. of Disability Research / Revue Européenne de Recherche sur le Handicap     Full-text available via subscription   (Followers: 10, SJR: 0.201, CiteScore: 1)
Alzheimer's & Dementia     Hybrid Journal   (Followers: 53, SJR: 4.66, CiteScore: 10)
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring     Open Access   (Followers: 6, SJR: 1.796, CiteScore: 4)
Alzheimer's & Dementia: Translational Research & Clinical Interventions     Open Access   (Followers: 6, SJR: 1.108, CiteScore: 3)
Ambulatory Pediatrics     Hybrid Journal   (Followers: 6)
American Heart J.     Hybrid Journal   (Followers: 58, SJR: 3.267, CiteScore: 4)
American J. of Cardiology     Hybrid Journal   (Followers: 63, SJR: 1.93, CiteScore: 3)
American J. of Emergency Medicine     Hybrid Journal   (Followers: 45, SJR: 0.604, CiteScore: 1)
American J. of Geriatric Pharmacotherapy     Full-text available via subscription   (Followers: 12)
American J. of Geriatric Psychiatry     Hybrid Journal   (Followers: 14, SJR: 1.524, CiteScore: 3)
American J. of Human Genetics     Hybrid Journal   (Followers: 35, SJR: 7.45, CiteScore: 8)
American J. of Infection Control     Hybrid Journal   (Followers: 29, 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: 50)
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: 241, 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: 30, SJR: 2.139, CiteScore: 4)
American J. of Preventive Medicine     Hybrid Journal   (Followers: 28, SJR: 2.164, CiteScore: 4)
American J. of Surgery     Hybrid Journal   (Followers: 39, 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: 64, SJR: 0.138, CiteScore: 0)
Anaesthesia Critical Care & Pain Medicine     Full-text available via subscription   (Followers: 23, 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: 44, SJR: 1.512, CiteScore: 5)
Analytica Chimica Acta : X     Open Access  
Analytical Biochemistry     Hybrid Journal   (Followers: 207, SJR: 0.633, CiteScore: 2)
Analytical Chemistry Research     Open Access   (Followers: 13, SJR: 0.411, CiteScore: 2)
Analytical Spectroscopy Library     Full-text available via subscription   (Followers: 14)
Anesthésie & Réanimation     Full-text available via subscription   (Followers: 2)
Anesthesiology Clinics     Full-text available via subscription   (Followers: 25, 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: 210, SJR: 1.58, CiteScore: 3)
Animal Feed Science and Technology     Hybrid Journal   (Followers: 6, SJR: 0.937, CiteScore: 2)
Animal Reproduction Science     Hybrid Journal   (Followers: 7, SJR: 0.704, CiteScore: 2)

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Similar Journals
Journal Cover
Accident Analysis & Prevention
Journal Prestige (SJR): 1.462
Citation Impact (citeScore): 3
Number of Followers: 101  
 
  Partially Free Journal Partially Free Journal
ISSN (Print) 0001-4575
Published by Elsevier Homepage  [3183 journals]
  • Dual-target hazard perception: Could identifying one hazard hinder a
           driver’s capacity to find a second'
    • Abstract: Publication date: October 2019Source: Accident Analysis & Prevention, Volume 131Author(s): Robert J. Sall, Jing Feng Low-level cognitive processes like visual search are crucial for hazard detection. In dual-target searches, subsequent search misses (SSMs) are known to occur when the identification of one target impedes detection of another that is concurrently presented. Despite the high likelihood of concurrent hazards in busy driving environments, SSMs have not been empirically investigated in driving. In three studies, participants were asked to identify safety-related target(s) in simulated traffic scenes that contained zero, one, or two target(s) of low or high perceptual saliency. These targets were defined as objects or events that would have prevented safe travel in the direction indicated by an arrow preceding the traffic scene. Findings from the pilot study (n = 20) and Experiment 1 (n = 29) demonstrated that detecting one target hindered drivers’ abilities to find a second from the same scene. In Experiment 2 (n = 30), explicit instructions regarding the level of risk were manipulated. It was found that search times were affected by the instructions, though SSMs persisted. Implications of SSMs in understanding the causes of some crashes are discussed, as well as future directions to improve ecological and criterion validity and to explore the roles of expertise and cognitive capabilities in multi-hazard detection.
       
  • In a heart beat: Using driver’s physiological changes to determine the
           quality of a takeover in highly automated vehicles
    • Abstract: Publication date: October 2019Source: Accident Analysis & Prevention, Volume 131Author(s): Mohamed Taher Alrefaie, Stever Summerskill, Thomas W Jackon Developing conditionally automated driving systems is on the rise. Vehicles with full longitudinal and latitudinal control will allow drivers to engage in secondary tasks without monitoring the roadway, but users may be required to resume vehicle control to handle critical hazards. The loss of driver’s situational awareness increases the potential for accidents. Thus, the automated systems need to estimate the driver’s ability to resume control of the driving task.The aim of this study was to assess the physiological behaviour (heart rate and pupil diameter) of drivers. The assessment was performed during two naturalistic secondary tasks. The tasks were the email and the twenty questions task in addition to a control group that did not perform any tasks. The study aimed at finding possible correlations between the driver’s physiological data and their responses to a takeover request. A driving simulator study was used to collect data from a total of 33 participants in a repeated measures design to examine the physiological changes during driving and to measure their takeover quality and response time.Secondary tasks induced changes on physiological measures and a small influence on response time. However, there was a strong observed correlation between the physiological measures and response time. Takeover quality in this study was assessed using two new performance measures called PerSpeed and PerAngle. They are identified as the mean percentage change of vehicle’s speed and heading angle starting from a take-over request time. Using linear mixed models, there was a strong interaction between task, heart rate and pupil diameter and PerSpeed, PerAngle and response time. This, in turn, provided a measurable understanding of a driver’s future responses to the automated system based on the driver’s physiological changes to allow better decision making. The present findings of this study emphasised the possibility of building a driver mental state model and prediction system to determine the quality of the driver's responses in a highly automated vehicle. Such results will reduce accidents and enhance the driver’s experience in highly automated vehicles.
       
  • A driving simulation study to examine the impact of available sight
           distance on driver behavior along rural highways
    • Abstract: Publication date: October 2019Source: Accident Analysis & Prevention, Volume 131Author(s): M. Bassani, L. Catani, A. Salussolia, C.Y.D. Yang The available sight distance (ASD) is the maximum length of the roadway ahead visible to the driver. It is a fundamental factor in road geometry principles and is used by road designers to ensure safe driving conditions. However, designers do not know how a specific ASD may affect the longitudinal and transversal behavior of drivers engaged in negotiating curves.This paper focuses on analyzing driver longitudinal behavior along rural highways curves with limited visibility. A number of virtual sight condition scenarios were recreated and tested in the driving simulator. Three tracks were designed with various combinations of radii and sight obstructions (a continuous wall) along the roadside located at various offsets from the lane centerline, combinations which resulted with a minimum ASD of 56.6 m. Roadside factors capable of influencing the risk perception of drivers (e.g., traffic barriers, posted speed limit signs, vegetation) were all excluded from the simulations.Results indicate that speed and trajectory dispersion from the lane centerline depend linearly on ASD in the investigated range of curve radii (from 120 to 430 m). In general, when ASD increases, so does speed and the trajectories tend to be less dispersed around the lane centerline. As a result, in safety terms, any variation in ASD will have the polar opposite effect on safety related parameters. Furthermore, different curves with similar ASD values resulted in different speed and lateral control behaviors. Analysis from ANOVA support the same findings; in addition, radius, curve direction, and distance from trajectory to sight obstruction have been identified as significant independent parameters. Road designers should adjust the ASD and these parameters when seeking to encourage drivers to adopt appropriate behaviors. To optimize safe driving conditions, ASD should be designed so that it is slightly greater than the required sight distance, since excessive ASD values may encourage drivers to drive at inappropriate speeds.
       
  • Multigroup invariance of the DAS across a random and an internet-sourced
           sample
    • Abstract: Publication date: October 2019Source: Accident Analysis & Prevention, Volume 131Author(s): M.J.M. Sullman, A.N. Stephens, J.E. Taylor It is well established that angry and, subsequently, aggressive drivers pose a problem for road safety. Over recent years, there has been an increase in the number of published studies examining driver anger, particularly using the Driving Anger Scale (DAS). The DAS measures six broad types of situations likely to provoke anger while driving (i.e., police presence, illegal driving, discourtesy, traffic obstructions, slower drivers, and hostile gestures). The majority of the recent studies have moved away from traditional paper-and-pencil methodologies, using the internet to collect data, for reasons of convenience. However, it is not yet completely clear whether data obtained from this methodology differs from more traditional methods. While research outside of the driving arena has not found substantial differences, it is important to establish whether this also applies to driving-related research and measures, such as the DAS. The present study used Multigroup Confirmatory Factor Analysis (MGCFA) to investigate the invariance of the DAS across a random sample from the electoral roll (n = 1,081: males = 45%) and an internet sourced sample (n = 627; males = 55%). The MGCFA showed the same six-factor solution was supported in both datasets. The relationships between the DAS factors and age, sex, trait anger, and annual mileage were broadly similar, although more significant differences were identified in the internet sample. This research demonstrates that driving measures administered over the internet produce similar results to those obtained using more traditional methods.
       
  • “I Snapchat and Drive!” A mixed methods approach examining snapchat
           use while driving and deterrent perceptions among young adults
    • Abstract: Publication date: October 2019Source: Accident Analysis & Prevention, Volume 131Author(s): Verity Truelove, James Freeman, Jeremy Davey This research utilised a qualitative and quantitative study to examine a sample of young drivers’ perceptions of deterrent forces, both legal and non-legal, for the behaviour of phone use while driving. First, focus groups were conducted with 60 drivers between the ages of 17 and 25 years who resided in Queensland, Australia. This qualitative study utilised an inductive approach to elicit participants’ perceptions without omitting important ideas. Legal sanctions were associated with low perceptions of enforcement certainty. Meanwhile, the only non-legal sanction to emerge was the concept of “safety”; many participants were deterred from using their phone while driving for fear of injury or death to themselves or others. The types of social media most likely to be engaged in were explored and sending videos or photos via the application Snapchat emerged as the most common social media application used among the sample. Consequently, the subsequent quantitative study focused on deterrent forces associated with Snapchat use while driving. A survey was utilised with a separate sample of young drivers aged 17–25 years (n = 503). The impact of the threat of legal sanctions on Snapchat use while driving was examined through classical deterrence theory and Stafford and Warr’s (1993) reconceptualised deterrence theory. The non-legal factor of perceived safety was also included in the quantitative study. None of the classical deterrence variables (e.g., certainty, severity and swiftness) reached significance while all the reconceptualised deterrence variables (e.g., direct and indirect punishment and punishment avoidance), as well as perceived safety, were significant predictors of Snapchat use while driving. It is suggested that perceptions of certainty of apprehension need to be increased for phone use while driving. The findings show the current impact of deterrent initiatives for phone use while driving as well as provide the first examination of deterrents for the specific mobile phone behaviour of Snapchat use while driving.
       
  • Adjusting finite sample bias in traffic safety modeling
    • Abstract: Publication date: October 2019Source: Accident Analysis & Prevention, Volume 131Author(s): Huiying Mao, Xinwei Deng, Dominique Lord, Gerardo Flintsch, Feng Guo Poisson and negative binomial regression models are fundamental statistical analysis tools for traffic safety evaluation. The regression parameter estimation could suffer from the finite sample bias when event frequency is low, which is commonly observed in safety research as crashes are rare events. In this study, we apply a bias-correction procedure to the parameter estimation of Poisson and NB regression models. We provide a general bias-correction formulation and illustrate the finite sample bias through a special scenario with a single binary explanatory variable. Several factors affecting the magnitude of bias are identified, including the number of crashes and the balance of the crash counts within strata of a categorical explanatory variable. Simulations are conducted to examine the properties of the bias-corrected coefficient estimators. The results show that the bias-corrected estimators generally provide less bias and smaller variance. The effect is especially pronounced when the crash count in one stratum is between 5 and 50. We apply the proposed method to a case study of infrastructure safety evaluation. Three scenarios were evaluated, all crashes collected in three years, and two hypothetical situations, where crash information was collected for “half-year” and “quarter-year” periods. The case-study results confirm that the magnitude of bias correction is larger for smaller crash counts. This paper demonstrates the finite sample bias associated with the small number of crashes and suggests bias adjustment can provide more accurate estimation when evaluating the impacts of crash risk factors.
       
  • Accounting for mediation in cyclist-vehicle crash models: A Bayesian
           mediation analysis approach
    • Abstract: Publication date: October 2019Source: Accident Analysis & Prevention, Volume 131Author(s): Mohamed Bayoumi Kamel, Tarek Sayed Cyclist safety is affected by many factors on the zonal level. Previous studies have found associations between cyclist-vehicle crashes and vehicle and bike exposures, network configuration, land use, road facility, and the built environment. In addition, the network configuration, land use, and road facility were found to affect bike exposure levels. The association of zonal characteristics with both exposure and crashes may bias the development of macro-level bike safety models. This paper aims to explain these associations simultaneously using a form of Structural Equation Modelling approach. The analysis assesses the mediated effects that some variables have on crashes through their effects on bike exposure (by setting bike exposure as a mediator). Data from 134 traffic analysis zones (TAZ’s) in the City of Vancouver, Canada is used as a case study. The indirect effect of network configuration, land use, and road facility on cyclist-vehicle crashes was assessed through Bayesian mediation analysis. Mediation analysis is an approach used to estimate how one variable transmits its effects to another variable through a certain mediator. These effects could be direct only, indirect only (through a certain mediator), or both direct and indirect. The results showed that the bike kilometers travelled (BKT) was a mediator of the relationship between network configuration, land use, and road facility and cyclist-vehicle crashes. The mediation analysis showed that some variables have different direct and indirect effect on cyclist-vehicle crashes. This indicates that while some variables may have negative direct association with crashes, their total crash effect can be positive after accounting for their effect through exposure. For example, bike network coverage and recreational density have negative direct association with cyclist-vehicle crashes, and positive indirect association leading to positive total effect on cyclist-vehicle crashes.
       
  • Using telematics data to find risky driver behaviour
    • Abstract: Publication date: October 2019Source: Accident Analysis & Prevention, Volume 131Author(s): Manda Winlaw, Stefan H. Steiner, R. Jock MacKay, Allaa R. Hilal Usage-based insurance schemes provide new opportunities for insurers to accurately price and manage risk. These schemes have the potential to better identify risky drivers which not only allows insurance companies to better price their products but it allows drivers to modify their behaviour to make roads safer and driving more efficient. However, for Usage-based insurance products, we need to better understand how driver behaviours influence the risk of a crash or an insurance claim. In this article, we present our analysis of automotive telematics data from over 28 million trips. We use a case control methodology to study the relationship between crash drivers and crash-free drivers and introduce an innovative method for determining control (crash-free) drivers. We fit a logistic regression model to our data and found that speeding was the most important driver behaviour linking driver behaviour to crash risk.
       
  • The association of helmet use with the risk of death for occupants of
           motorcycles involved in traffic crashes: A meta-analysis.
    • Abstract: Publication date: October 2019Source: Accident Analysis & Prevention, Volume 131Author(s): Mingming Liang, Yun Zhang, Xiaotian Zhang, Min Min, Tingting Shi, Yehuan Sun
       
  • Vulnerable road users in low-, middle-, and high-income countries:
           Validation of a Pedestrian Behaviour Questionnaire
    • Abstract: Publication date: October 2019Source: Accident Analysis & Prevention, Volume 131Author(s): Rich C. McIlroy, Katherine L. Plant, Usanisa Jikyong, Vũ Hoài Nam, Brenda Bunyasi, Gilbert O. Kokwaro, Jianping Wu, Md. Shamsul Hoque, John M. Preston, Neville A. Stanton The primary aim of this study was to validate the short version of a Pedestrian Behaviour Questionnaire across six culturally and economically distinct countries; Bangladesh, China, Kenya, Thailand, the UK, and Vietnam. The questionnaire comprised 20 items that asked respondents to rate the extent to which they perform certain types of pedestrian behaviours, with each behaviour belonging to one of five categories identified in previous literature; violations, errors, lapses, aggressive behaviours, and positive behaviours. The sample consisted of 3423 respondents across the six countries. Confirmatory factor analysis was used to assess the fit of the data to the five-factor structure, and a four-factor structure in which violations and errors were combined into one factor (seen elsewhere in the literature). For some items, factor loadings were unacceptably low, internal reliability was low for two of the sub-scales, and model fit indices were generally unacceptable for both models. As such, only the violations, lapses, and aggressions sub-scales were retained (those with acceptable reliability and factor loadings), and the three-factor model tested. Although results suggest that the violations sub-scale may need additional attention, the three-factor solution showed the best fit to the data. The resulting 12-item scale is discussed with regards to country differences, and with respect to its utility as a research tool in cross-cultural studies of road user behaviour.
       
  • A randomized trial to test the impact of parent communication on improving
           in-vehicle feedback systems
    • Abstract: Publication date: October 2019Source: Accident Analysis & Prevention, Volume 131Author(s): Corinne Peek-Asa, Michelle L. Reyes, Cara J. Hamann, Brandon D. Butcher, Joseph E. Cavanaugh This randomized controlled trial evaluated the impact of integrating Steering Teens Safe, a parent communication intervention, with feedback from an in-vehicle video recording system. In-vehicle video systems that trigger a recording when the vehicle exceeds a g-force threshold have been used to provide feedback to young drivers. Few of these programs have involved parental engagement. Parent-teen dyads were randomized to three groups and 150 dyads completed the study. All groups received an in-vehicle video system that recorded driving events. The control group received no feedback or intervention. In the first intervention group, teens received real-time feedback, and parent-teen dyads received summary feedback, based on information recorded by the in-vehicle system. The second intervention group received the same feedback, plus parents were taught strategies to improve communication with their teen about safe driving. The primary outcome variable was unsafe driving event rates per 1000 miles driven and the primary independent variable was group assignment. Generalized linear models were used to calculate effect estimates. Compared with the control group, the Event Recorder Feedback group had a rate ratio of 0.35 (95% CI = 0.24 – 0.50) and the combined intervention group (Event Recorder Feedback and parent communication) had a rate ratio of 0.21 (95% CI = 0.15 – 0.30). Furthermore, the combined intervention group had a significantly lower event rate than the Event Recorder Feedback only group (rate ratio = 0.60, 95% CI = 0.41 – 0.87). While in-vehicle feedback systems can help reduce unsafe driving events in early independent driving, teaching parents strategies for effective communication with their young driver may further improve impact.
       
  • Examining correlations between motorcyclist’s conspicuity, apparel
           related factors and injury severity score: Evidence from new motorcycle
           crash causation study
    • Abstract: Publication date: October 2019Source: Accident Analysis & Prevention, Volume 131Author(s): Behram Wali, Asad J. Khattak, Numan Ahmad Motorcyclists are vulnerable road users at a particularly high risk of serious injury or death when involved in a crash. In order to evaluate key risk factors in motorcycle crashes, this study quantifies how different “policy-sensitive” factors correlate with injury severity, while controlling for rider and crash specific factors as well as other observed/unobserved factors. The study analyzes data from 321 motorcycle injury crashes from a comprehensive US DOT FHWA’s Motorcycle Crash Causation Study (MCCS). These were all non-fatal injury crashes that are representative of the vast majority (82%) of motorcycle crashes. An anatomical injury severity scoring system, termed as Injury Severity Score (ISS), is analyzed providing an overall score by accounting for the possibility of multiple injuries to different body parts of a rider. An ISS ranges from 1 to 75, averaging at 10.32 for this sample (above 9 is considered serious injury), with a spike at 1 (very minor injury). Preliminary cross-tabulation analysis mapped ISS to the Abbreviated Injury Scale (AIS) injury classification and examined the strength of associations between the two. While the study finds a strong correlation between AIS and ISS classification (Kendall’s tau of 0.911), significant contrasts are observed in that, when compared to ISS, AIS tends to underestimate the severity of an injury sustained by a rider. For modeling, fixed and random parameter Tobit modeling frameworks were used in a corner-solution setting to account for the left-tail spike in the distribution of ISS and to account for unobserved heterogeneity. The developed random parameters Tobit framework additionally accounts for the interactive effects of key risk factors, allowing for possible correlations among random parameters. A correlated random parameter Tobit model significantly out-performed the uncorrelated random parameter Tobit and fixed parameter Tobit models. While controlling for various other factors, we found that motorcycle-specific shoes and retroreflective upper body clothing correlate with lower ISS on-average by 5.94 and 1.88 units respectively. Riders with only partial helmet coverage on-average sustained more severe injuries, whereas, riders with acceptable helmet fit had lower ISS Methodologically, not only do the individual effects of several key risk factors vary significantly across observations in the form of random parameters, but the interactions between unobserved factors characterizing random parameters significantly influence the injury severity score as well. The implications of the findings are discussed.
       
  • Safety aspects of riding with children: Descriptive analysis of adult
           riders’ self-report
    • Abstract: Publication date: October 2019Source: Accident Analysis & Prevention, Volume 131Author(s): J. Hatfield, R.G. Poulos, S.M. Murphy, L.K. Flack, C. Rissel, R. Grzebieta, A.S. McIntosh Active transport, including cycling, is promoted as an effective way of increasing children’s physical activity and health. Parents can support children’s riding by riding with them and it is important to address relevant safety issues. Little is known about parents’ experience of safety-relevant aspects of riding with children. Participants in the Safer Cycling Study in New South Wales, Australia, who reported that they had ridden with children in the last 12 months were questioned about how they ride with children, and their experience of safety issues and crashes. Among the 187 respondents who had ridden with children on their bicycle, the most common form of carrier was a rear-mounted seat (48%) followed by a trailer (29%). Many respondents (79%) identified risks specific to riding carrying children, including those linked with specific carrier types and with use of footpaths. Most (92%) indicated that they change their behaviour when carrying a child on their bicycle; for example, riding more slowly, more carefully, and away from roads. Among crashes with a child on the bicycle, most were falls. Among the 345 participants who had ridden to accompany a child on a bicycle, approximately three quarters identified risks specific to accompanying children, such as managing the child’s limited skill, awareness and predictability. Ninety-seven percent reported behavioural changes including positioning themselves as a barrier for their child and caution crossing roads. Findings suggest strategies to support parents in riding safely with children.
       
  • Reducing the time loss bias: Two ways to improved driving safety and
           energy efficiency
    • Abstract: Publication date: October 2019Source: Accident Analysis & Prevention, Volume 131Author(s): Mario Herberz, Celina Kacperski, Florian Kutzner The time loss bias describes the systematic overestimation of time lost when decelerating from a relatively high speed. In the present study, we investigated the debiasing effect of two educational interventions, the Paceometer (Peer and Gamliel, 2013) and a newly designed Pop-up assistant, in a video-based controlled-access highway driving scenario. The Paceometer provides participants with pace information (min/km) added to the common speedometer. The Pop-up assistant informs about the time lost when decreasing speed according to a specific situation. A mixed-design ANOVA confirmed the improvement of time loss estimations for both debiasing tools and the superiority of the Pop-up assistant, which produced temporal spillover effects. We discuss potential explanations in terms of simplifying information and anchoring and the potential benefits of both tools to reduce risky driving, fuel costs and range restrictions of electric vehicles.
       
  • A safety assessment of mixed fleets with Connected and Autonomous Vehicles
           using the Surrogate Safety Assessment Module
    • Abstract: Publication date: October 2019Source: Accident Analysis & Prevention, Volume 131Author(s): Navreet Virdi, Hanna Grzybowska, S. Travis Waller, Vinayak Dixit The transportation network can provide additional utility by addressing the safety concerns on roads. On-road fatalities are an unfortunate loss of life and lead to significant costs for society and the economy. Connected and Autonomous Vehicles (CAVs), envisaged as operating with idealised safety and cooperation, could be a means of mitigating these costs. This paper intends to provide insights into the safety improvements to be attained by incrementally transitioning the fleet to CAVs. This investigation is done by constructing a calibrated microsimulation environment in Vissim and deploying the custom developed Virdi CAV Control Protocol (VCCP) algorithm for CAV behaviour. The CAV behaviour is implemented using an application programming interface and a dynamic linking library. CAVs are introduced to the environment in 10% increments, and safety performance is assessed using the Surrogate Safety Assessment Module (SSAM). The results of this study show that CAVs at low penetrations result in an increase in conflicts at signalised intersections but a decrease at priority-controlled intersections. The initial 20% penetration of CAVs is accompanied by a +22%, −87%, −62% and +33% change in conflicts at the signalised, priority, roundabout and DDI intersection respectively. CAVs at high penetrations indicate a global reduction in conflicts. A 90% CAV penetration is accompanied by a −48%, −100%, −98% and −81% change in conflicts at the signalised, priority, roundabout and DDI intersection respectively.
       
  • Unsafe riding behaviors of shared-bicycle riders in urban China: A
           retrospective survey
    • Abstract: Publication date: October 2019Source: Accident Analysis & Prevention, Volume 131Author(s): Xiaolin Wu, Wangxin Xiao, Conghui Deng, David C. Schwebel, Guoqing Hu Shared-bicycle use has skyrocketed in urban China, but little is known about the safety of bicycle users. The Chinese popular media reports multiple risky riding behaviors among shared bicycle riders, but scientific research on the topic is lacking. Therefore, we conducted a retrospective WeChat-based online survey to examine how often shared bicycle riders report engaging in risky cycling behaviors in urban China. Eight unsafe shared bicycle riding behaviors were assessed: not wearing helmets, running red lights, cycling against the traffic flow, riding in lanes designed for motor vehicles, riding in lanes designed for pedestrians, carrying passengers on bicycles, using cell phones while riding, and eating while riding. In total, 1960 valid questionnaires were collected. The proportion of participants who reported always or often having unsafe riding behavior in the past month, ranged from 1.1% for carrying passengers on the bicycles to 97.6% for failing to wear a helmet. Demographic characteristics were associated with unsafe behaviors through multivariate logistic regression, with male riders and riders aged 25 years or younger more likely to ride while using cell phones than females (AOR = 2.94) and those 36 years or older (AOR = 3.57). Cyclists with undergraduate education were more likely to wear helmets than those with postgraduate education or higher (AOR = 0.21). Compared to riders from central municipalities governed directly by the central government, riders from provincial capitals, deputy provincial cities, and smaller cities were at higher risks of riding in lanes for pedestrians, respectively (AOR = 1.59, 2.82 and 1.61). Riders who rode over 5 h a week and who rode on weekends were more likely to carry passengers than those who rode less than 1 h a week (AOR = 4.72) and those who rode only on weekdays (AOR = 3.93). We conclude that shared-bicycle riders frequently engage in some unsafe riding behaviors in urban China. Younger age, lower level of education, and longer hours of riding each week are associated with greater risks of some unsafe riding behaviors. Shared bicycles offer substantial benefit to societal health and transportation, but evidence-based interventions should be considered to reduce risks from unsafe shared bicycle riding behaviors. A well-designed road infrastructure with dedicated on-road bicycle lanes and readily-accessible comfortable, low-cost, and safe helmets may also reduce unsafe riding behaviors and unwanted crashes and injuries for shared bicycle riders.
       
  • 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: August 2019Source: Accident Analysis & Prevention, Volume 129Author(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.
       
  • Full Bayesian conflict-based models for real time safety evaluation of
           signalized intersections
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(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.
       
  • 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: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Gustav Markkula, Johan Engström, Johan Lodin, Jonas Bärgman, Trent Victor
       
  • Young driver fatal motorcycle accident analysis by jointly maximizing
           accuracy and information
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Dan Halbersberg, Boaz Lerner While young drivers (YDs) constitute ∼10% of the driver population, their fatality rate in motorcycle accidents is up to three times higher. Thus, we are interested in predicting fatal motorcycle accidents (FMAs), and in identifying their key factors and possible causes. Accurate prediction of YD FMAs from data by risk minimization using the 0/1 loss function (i.e., the ordinary classification accuracy) cannot be guaranteed because these accidents are only ∼1% of all YD motorcycle accidents, and classifiers tend to focus on the majority class of minor accidents at the expense of the minority class of fatal ones. Also, classifiers are usually uninformative (providing no information about the distribution of misclassifications), insensitive to error severity (making no distinction between misclassification of fatal accidents as severe or minor), and limited in identifying key factors. We propose to use an information measure (IM) that jointly maximizes accuracy and information and is sensitive to the error distribution and severity. Using a database of ∼3600 motorcycle accidents, a Bayesian network classifier optimized by IM predicted FMAs better than classifiers maximizing accuracy or other predictive or information measures, and identified fatal accident key factors and causal relations.
       
  • Road Safety on Five Continents – Conference in Jeju, South Korea
           2018
    • Abstract: Publication date: Available online 14 June 2019Source: Accident Analysis & PreventionAuthor(s): Anna Vadeby
       
  • Scenarios of crashes involving light mopeds on urban bicycle paths
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): R.J. Davidse, K. van Duijvenvoorde, M.J. Boele-Vos, W.J.R. Louwerse, A. Stelling-Konczak, C.W.A.E. Duivenvoorden, A.J. Algera In the Netherlands, cyclists have to share the bicycle path with light moped riders. These riders are allowed to ride 25 km/h and do not have to wear a helmet (Dutch regulation). Due to several trends such as traffic congestion and the introduction of the scooter model, light mopeds have become more popular, both among older and younger people. This has led to an increased traffic density on bicycle paths as well as concerns about the safety of cyclists. In response to these concerns, several Dutch cities would like to ban light moped riders (LMRs) from the bicycle path and let them ride on the carriageway. However, it is uncertain what the consequences would be for the safety of light moped riders. Moreover, it is not clear to what extent the shared use of bicycle paths leads to serious crashes between cyclists and LMRs. Therefore, an in-depth crash investigation study was carried out to gain more insight into the factors and circumstances that influence the occurrence and consequences of light moped crashes on bicycle paths.A dedicated team for in-depth road crash investigation collected and analyzed detailed information on 36 light moped crashes that occurred on an urban bicycle path. This resulted in a description of the course of events for every crash that was analyzed, including a list of factors that contributed to the occurrence of the crash and possible injuries. Crashes with a similar course of events and a comparable combination of contributory factors were grouped into (sub)types of light moped crashes.Six types of crashes were identified. Based on the contributory crash factors of the identified crash types, remedial measures can be developed to prevent similar crashes from occurring in the future. Moving the LMR to the carriageway is only advisable on 30 km/h roads. Alternative measures to improve the safety of both cyclists and light moped riders include: 1) removing obstacles such as poles from the bicycle path, 2) following guidelines on the minimum width of bicycle paths given traffic volumes, 3) improving sight distances at intersections, 4) traffic light control without conflicts between traffic flows, and 5) introducing a helmet law for light moped riders and their passengers.
       
  • Incorporating behavioral variables into crash count prediction by
           severity: A multivariate multiple risk source approach
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Mohammad Razaur Rahman Shaon, Xiao Qin, Amir Pooyan Afghari, Simon Washington, Md Mazharul Haque The frequency and severity of traffic crashes have commonly been used as indicators of crash risk on transport networks. Comprehensive modeling of crash risk should account for both frequency and injury severity—capturing both the extent and intensity of transport risk for designing effective safety improvement programs. Previous research has revealed that crashes are correlated across severity categories because of the combined influence of risk factors, observed or unobserved. Moreover, crashes are the outcomes of a multitude of factors related to roadway design, traffic operations, pavement conditions, driver behavior, human factors, and environmental characteristics, or in more general terms: factors reflect both engineering and non-engineering risk sources. Perhaps not surprisingly, engineering risk sources have dominated the list of variables in the mainstream modeling of crashes whereas non-engineering sources, in particular, behavioral factors, are crucially omitted. It is plausible to assume that crash contributing factors from the same risk source affect crashes in a similar manner, but their influences vary across different risk sources. Conventional crash frequency modeling hypothesizes that the total crash count at any roadway site is well-approximated by a single risk source to which several explanatory variables contribute collaboratively. The conventional formulation is not capable of accounting for variations between risk sources; therefore, is unable to discriminate distinct impacts between engineering variables and non-engineering variables. To address this shortcoming, this study contributes to the development of multivariate multiple risk source regression, a robust modeling technique to model crash frequency and severity simultaneously.The multivariate multiple risk source regression method applied in this study can effectively capture the correlation between severity levels of crash counts while identifyinging the varying effects of crash contributing factors originated from distinct sources. Using crashes on Wisconsin rural two-lane highways, two risk sources – engineering and behavioral – were employed to develop proposed models. The modeling results were compared with a single equation negative binomial (NB) model, and a univariate multiple risk source model. The results show that the multivariate multiple risk source model significantly outperforms the other models in terms of statistical fit across several measures. The study demonstrates a unique approach to explicitly incorporating behavioral factors into crash prediction models while taking crash severity into consideration. More importantly, the parameter estimates provide more insight into the distinct sources of crash risk, which can be used to further inform safety practitioners and guide roadway improvement programs.
       
  • Transferability of real-time safety performance functions for signalized
           intersections
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Mohamed Essa, Tarek Sayed, Passant Reyad Optimizing traffic signals in real-time for safety performance can be executable in the era of Connected Vehicles (CVs) when real-time information on vehicle positions and trajectories is available. To achieve this, real-time safety models are needed to understand how changes in signal controllers affect safety in real-time. Recently, several real-time safety models were developed for signalized intersections that relate various dynamic traffic parameters to the number of rear-end traffic conflicts at the signal cycle level. The traffic parameters included: traffic volume, maximum queue length, shock wave speed and area, and platoon ratio. For wider application of these models to other jurisdictions, the transferability of these models needs to be examined. Therefore, this paper aims to investigate the transferability of several signalized intersections real-time safety models to new jurisdictions. Two corridors of signalized intersections in California and Atlanta were used in the analysis as destination jurisdictions. Detailed vehicle trajectories for these corridors were obtained from the Next Generation Simulation (NGSIM) data. Various transferability analysis approaches were applied. The transferability of the real-time safety models was evaluated with and without a local calibration for the model parameters at the new jurisdictions. Several goodness-of-fit measures were examined to assess the ability of the developed models to predict traffic conflicts. Overall, the results showed that the real-time safety models are transferable, which confirms the validity of using them for real-time safety evaluation of signalized intersections.
       
  • Using trajectory-level SHRP2 naturalistic driving data for investigating
           driver lane-keeping ability in fog: An association rules mining approach
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Anik Das, Mohamed M. Ahmed, Ali Ghasemzadeh The presence of fog has a significant adverse impact on driving. Reduced visibility due to fog obscures the driving environment and greatly affects driver behavior and performance. Lane-keeping ability is a lateral driver behavior that can be very crucial in run-off-road crashes under reduced visibility conditions. A number of data mining techniques have been adopted in previous studies to examine driver behavior including lane-keeping ability. This study adopted an association rules mining method, a promising data mining technique, to investigate driver lane-keeping ability in foggy weather conditions using big trajectory-level SHRP2 Naturalistic Driving Study (NDS) datasets. A total of 124 trips in fog with their corresponding 248 trips in clear weather (i.e., 2 clear trips: 1 foggy weather trip) were considered for the study. The results indicated that affected visibility was associated with poor lane-keeping performance in several rules. Furthermore, additional factors including male drivers, a higher number of lanes, the presence of horizontal curves, etc. were found to be significant factors for having a higher proportion of poor lane-keeping performance. Moreover, drivers with more miles driven last year were found to have better lane-keeping performance. The findings of this study could help transportation practitioners to select effective countermeasures for mitigating run-off-road crashes under limited visibility conditions.
       
  • The relationship between impact speed and the probability of pedestrian
           fatality during a vehicle-pedestrian crash: A systematic review and
           meta-analysis
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Qinaat Hussain, Hanqin Feng, Raphael Grzebieta, Tom Brijs, Jake Olivier BackgroundPedestrians struck in motorised vehicle crashes constitute the largest group of traffic fatalities worldwide. Excessive speed is the primary contributory factor in such crashes. The relationship between estimated impact speed and the risk of a pedestrian fatality has generated much debate concerning what should be a safe maximum speed limit for vehicles in high pedestrian active areas.MethodsFour electronic databases (MEDLINE, EMBASE, COMPENDEX, and SCOPUS) were searched to identify relevant studies. Records were assessed, and data retrieved independently by two authors in adherence with the PRISMA statement. The included studies reported data on pedestrian fatalities from motorised vehicle crashes with known estimated impact speed. Summary odds ratios (OR) were obtained using meta-regression models. Time trends and publication bias were assessed.ResultsFifty-five studies were identified for a full-text assessment, 27 met inclusion criteria, and 20 were included in a meta-analysis. The analyses found that when the estimated impact speed increases by 1 km/h, the odds of a pedestrian fatality increases on average by 11% (OR = 1.11, 95% CI: 1.10–1.12). The risk of a fatality reaches 5% at an estimated impact speed of 30 km/h, 10% at 37 km/h, 50% at 59 km/h, 75% at 69 km/h and 90% at 80 km/h. Evidence of publication bias and time trend bias among included studies were found.ConclusionsThe results of the meta-analysis support setting speed limits of 30–40 km/h for high pedestrian active areas. These speed limits are commonly used by best practice countries that have the lowest road fatality rates and that practice a Safe System Approach to road safety.
       
  • Using latent class analysis and mixed logit model to explore risk factors
           on driver injury severity in single-vehicle crashes
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Zhenning Li, Qiong Wu, Yusheng Ci, Cong Chen, Xiaofeng Chen, Guohui Zhang The single-vehicle crash has been recognized as a critical crash type due to its high fatality rate. In this study, a two-year crash dataset including all single-vehicle crashes in New Mexico is adopted to analyze the impact of contributing factors on driver injury severity. In order to capture the across-class heterogeneous effects, a latent class approach is designed to classify the whole dataset by maximizing the homogeneous effects within each cluster. The mixed logit model is subsequently developed on each cluster to account for the within-class unobserved heterogeneity and to further analyze the dataset. According to the estimation results, several variables including overturn, fixed object, and snowing, are found to be normally distributed in the observations in the overall sample, indicating there exist some heterogeneous effects in the dataset. Some fixed parameters, including rural, wet, overtaking, seatbelt used, 65 years old or older, etc., are also found to significantly influence driver injury severity. This study provides an insightful understanding of the impacts of these variables on driver injury severity in single-vehicle crashes, and a beneficial reference for developing effective countermeasures and strategies for mitigating driver injury severity.
       
  • Quantifying visual road environment to establish a speeding prediction
           model: An examination using naturalistic driving data
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Bo Yu, Yuren Chen, Shan Bao Speeding is one of the major contributors to traffic crashes. To solve this problem, speeding prediction is recognized as a critical step in a pre-warning system. While previous studies have shown that speeding is affected by road environmental design, research in predicting speeding behavior through road environment features has not yet been conducted. Furthermore, there is a large discrepancy between actual and perceived road environmental information given that a driver’s visual perception plays a crucial role as the dominant source of information in determining driver’s behavior. Thus, this paper aims to establish a speeding prediction model based on quantifying the visual road environment to improve the design of pre-waring systems, which can predict whether drivers are going to speed and provide them with visual or/and audio warnings about their current driving speed and the speed limit prior to the occurrence of speeding behavior. Twenty input variables derived from three categories including visual road environment parameters, vehicle kinematic features, and driver characteristics were considered in the proposed speeding prediction model. Especially, the road environmental design factors consisting of the visual road geometry and visual roadside environment as perceived by the driver’s eyes were quantified using a visual road environment model. Field experiments were conducted to collect naturalistic driving data concerning speeding behavior on the typical two-lane mountainous rural highways in five provinces of China. Random Forests, an ensemble learning method for regression and classification, were applied to build the speeding prediction model and variable importance was calculated. Additionally, logistic regression was used as a supplement to further investigate factors impacting on speeding behavior. A speeding criterion was defined with two levels in this study: a lower level (exceeding the posted speed limit) and a higher level (10% above the posted speed limit). Under both levels of the speeding criterion, the speeding prediction model performed well with high accuracy (over 85%). This model could use the value of the variables obtained from the current position to predict drivers’ speeding behavior at the future position located a sighting distance away. This interval was sufficient for a pre-warning system to give a speeding warning that a driver with normal perception-reaction time (around 2.5 s) could respond to. Findings in this study can be used to effectively predict speeding in advance and help to reduce speeding-related traffic accidents.
       
  • Integration of hazard rectification efficiency in safety assessment for
           proactive management
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Mei Liu, Pin-Chao Liao ObjectiveSafety assessment is crucial for the development of continuous improvement strategies. However, most studies assess construction safety with cross-sectional information and thus management tends to be passive. This study proposes an evidence-based methodology incorporating hazard rectification efficiency for project safety assessment.MethodFirst, we theoretically introduced hazard rectification efficiency as a proxy for hazard exposure. Later, based on set-pair analysis, we proposed a safety assessment model that incorporates hazard occurrence and rectification efficiency. Subsequently, we collected site investigation records from seven building projects in Qingdao, Shandong. The data were used to develop a safety performance index (SPI) with the proposed model and a default model. The results were compared and discussed according to industrial practices for validation purposes.ResultsThe proposed model provides conservative indications of project safety performance; more importantly, the index calculated with the model provides advance warning when necessary. In the proposed method, in terms of the SPI, hazard and rectification indicators provide actionable information to address failures and improve safety conditions.ImplicationsThis research describes a new perspective (rectification efficiency) for safety assessment, which supplements the current body of knowledge on safety assessment. The proposed index, SPI, promotes the adoption of proactive hazard identification, monitoring, and control in construction.
       
  • A bivariate probit analysis of child passenger’s sitting behaviour and
           restraint use in motor vehicle
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Eric N. Aidoo, Williams Ackaah, Simon K. Appiah, Ernest K. Appiah, Joseph Addae, Haruna Alhassan Motor vehicle injuries are a leading cause of death among children worldwide, though many of these deaths are preventable. Buckling young children in age- and size-appropriate car seats, booster seats, or seat belts and also seating them in appropriate position can lead to a significant reduction of serious and fatal injuries. This study investigated sitting behaviour and restraint use among child passengers through cross-sectional observational surveys conducted in Kumasi, Ghana. A bivariate probit model was developed for simultaneous determination of the contributing factors influencing child passenger’s sitting behaviour and restraint use. The results showed that 26% of the child passengers observed were occupying the front seat and the prevalence rate of restraint use was 4.5%. The developed bivariate probit model clearly highlights the existence of interrelationship between child passenger’s sitting position and restraint use. The key factors simultaneously influencing child passenger’s sitting position and restraint use include vehicle type, driver’s gender, driver’s belt use, child’s age, and the presence of other child or adult passenger. Furthermore, time of day and day of week also influence child passenger sitting behaviour but not their restraint use. These findings provide insight for better understanding of child transporting practices and the contributing factors influencing their sitting behaviour and restraint use. The findings also highlight the need for policy makers to design effective countermeasures to promote rear sitting and restraint use among child passengers.
       
  • Real-time accident detection: Coping with imbalanced data
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Amir Bahador Parsa, Homa Taghipour, Sybil Derrible, Abolfazl (Kouros) Mohammadian Detecting accidents is of great importance since they often impose significant delay and inconvenience to road users. This study compares the performance of two popular machine learning models, Support Vector Machine (SVM) and Probabilistic Neural Network (PNN), to detect the occurrence of accidents on the Eisenhower expressway in Chicago. Accordingly, since the detection of accidents should be as rapid as possible, seven models are trained and tested for each machine learning technique, using traffic condition data from 1 to 7 min after the actual occurrence. The main sources of data used in this study consist of weather condition, accident, and loop detector data. Furthermore, to overcome the problem of imbalanced data (i.e., underrepresentation of accidents in the dataset), the Synthetic Minority Oversampling TEchnique (SMOTE) is used. The results show that although SVM achieves overall higher accuracy, PNN outperforms SVM regarding the Detection Rate (DR) (i.e., percentage of correct accident detections). In addition, while both models perform best at 5 min after the occurrence of accidents, models trained at 3 or 4 min after the occurrence of an accident detect accidents more rapidly while performing reasonably well. Lastly, a sensitivity analysis of PNN for Time-To-Detection (TTD) reveals that the speed difference between upstream and downstream of accidents location is particularly significant to detect the occurrence of accidents.
       
  • Assessing right-turning vehicle-pedestrian conflicts at intersections
           using an integrated microscopic simulation model
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Peng Chen, Weiliang Zeng, Guizhen Yu Frequent vehicle-pedestrian conflicts deserve special attention for safety assessment at intersections. This study helps verify how the simulation as an innovative approach can be utilized for right-turning vehicle-pedestrian conflict assessment at intersection crosswalks prior to implementation. Various behavior models such as vehicle turning path, turning speed, gap acceptance model and pedestrian behavior model, have been established. Through integrating the calibrated models into one simulation platform, the stochastic behavior of vehicles and pedestrians under different geometric layouts and operational conditions can be reproduced. Based on the field data collected by an unmanned aerial vehicle (UAV) at two urban intersections in Beijing, China, it was demonstrated through validation of surrogate safety measures (SSMs), i.e., Post Encroachment Time (PET) and vehicle passing speed at conflict points, that the simulation model can reasonably represent the frequency and severity of conflict occurrence at signalized crosswalks. The sensitivity analysis results indicated that large dimensions and turning angles of intersections tend to result in undesirable safety performance.
       
  • Safety citizenship behavior (SCB) in the workplace: A stable
           construct' Analysis of psychometric invariance across four European
           countries
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Matteo Curcuruto, Stacey M. Conchie, Mark A. Griffin Safety citizenship behaviors (SCBs) are important participative organizational behaviors that emerge in work-groups. SCBs create a work environment that supports individual and team safety, encourages a proactive management of workplace safety, and ultimately, prevents accidents. In spite of the importance of SCBs, little consensus exists on research issues like the dimensionality of safety citizenship, and if any superordinate factor level of safety citizenship should be conceptualized, and thus measured. The present study addressed this issue by examining the dimensionality of SCBs, as they relate to behaviors of helping, stewardship, civic virtue, whistleblowing, voice, and initiating change in current practices. Data on SCBs were collected from four industrial plants (N = 1065) in four European countries (Italy, Russia, Switzerland, United Kingdom). The results show that SCBs structure around two superordinate second-order factors that reflect affiliation and challenge. Multi-group analyses supported the structure and metric invariance of the two-factor model across the four national subsamples.
       
  • Analytical observational study of nonfatal motor vehicle collisions and
           incidents in a light-vehicle sales and service fleet
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Stephanie G. Pratt, Jennifer L. Bell Motor vehicle crashes (MVCs) are a significant cause of lost-workday injuries, and consistently the leading cause of work-related fatalities in the United States for all industries combined. Prevention research has focused mainly on collisions fatal to the drivers of large trucks. This analytical observational study addresses gaps in the literature by: conducting a descriptive analysis of motor vehicle claim events involving light-vehicle drivers in a large health care industry fleet; identifying risk factors for work-related MVCs and injuries based on vehicle miles traveled; and providing details on circumstances of these events.The study examined 8068 motor vehicle events resulting in vehicle damage, property damage, or injury reported by 6680 U.S.-based drivers in a light-vehicle sales and service fleet operated by a health care company over a 4 ½-year period (January 2010 through June 2014). Thirty-three percent (n = 2660) of the events were collisions. Collisions were segmented as recoverable or non-recoverable according to whether the company could recover costs from another party, and mileage-based collision and injury rates were calculated by gender, age, tenure, and vehicle type. Differences in collision and injury rates between groups of interest (for example, tenure and age categories) were assessed with Poisson regression techniques adjusted using generalized estimating equations (GEE) for repeated observations on the same employee over time.Age, gender, and job tenure were significant collision risk factors, and risk patterns for recoverable and non-recoverable collisions were similar to those for total collisions. Collisions per million miles (CPMM) were significantly higher for drivers 21–24.9 years of age compared to drivers age 25–54.9 years (9.58 CPMM vs 4.96 CPMM, p = .025), drivers employed for less than 2 years compared to those employed 2 or more years (6.22 CPMM vs 4.82 CPMM, p 
       
  • Engineering judgment and road safety
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Ezra Hauer Decisions that highway and traffic engineers make significantly affect the safety of road users. The documents that guide highway and traffic engineering practice suggest that many of these decisions be made by ‘engineering judgment’. One would like this judgment to be informed by evidence-based anticipation of their likely safety consequences and by a professional ability to balance safety against mobility and other dimensions of ‘utility’. I show that these desiderata are largely unfulfilled. The many implications of this finding are discussed.
       
  • A feature learning approach based on XGBoost for driving assessment and
           risk prediction
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Xiupeng Shi, Yiik Diew Wong, Michael Zhi-Feng Li, Chandrasekar Palanisamy, Chen Chai This study designs a framework of feature extraction and selection, to assess vehicle driving and predict risk levels. The framework integrates learning-based feature selection, unsupervised risk rating, and imbalanced data resampling. For each vehicle, about 1300 driving behaviour features are extracted from trajectory data, which produce in-depth and multi-view measures on behaviours. To estimate the risk potentials of vehicles in driving, unsupervised data labelling is proposed. Based on extracted risk indicator features, vehicles are clustered into various groups labelled with graded risk levels. Data under-sampling of the safe group is performed to reduce the risk-safe class imbalance. Afterwards, the linkages between behaviour features and corresponding risk levels are built using XGBoost, and key features are identified according to feature importance ranking and recursive elimination. The risk levels of vehicles in driving are predicted based on key features selected. As a case study, NGSIM trajectory data are used in which four risk levels are clustered by Fuzzy C-means, 64 key behaviour features are identified, and an overall accuracy of 89% is achieved for behaviour-based risk prediction. Findings show that this approach is effective and reliable to identify important features for driving assessment, and achieve an accurate prediction of risk levels.
       
  • Mobile phone conversation distraction: Understanding differences in impact
           between simulator and naturalistic driving studies
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Kasun P. Wijayaratna, Mitchell L. Cunningham, Michael A. Regan, Sisi Jian, Sai Chand, Vinayak V. Dixit A current issue within the driver distraction community centres around different findings regarding the impact of mobile phone conversation on driving found in driving simulators versus instrumented vehicles employed in real-world naturalistic driving studies (NDSs). This paper compares and contrasts the two types of studies and aims to provide reasons for the differences in findings that have been documented. A comprehensive review of literature and consultations with human factors experts highlighted that simulator studies tend to show degradation in driving performance, suggestive of increased crash risk as a result of mobile phone conversation. Whilst NDSs, at times, present data suggesting that mobile phone conversation distraction actually reduces crash risk. This study identifies that these differences may be attributed to behavioural hypotheses associated with driver self-regulation, arousal from cognitive loading, task displacement and gaze concentration – all of which need to be explicitly tested in future driving studies.Metric estimation and application was also revealed to be polarising results and the subsequent assessment of the crash risk. A common metric applied in this domain is the ‘Odds Ratio’, particularly prevalent in NDSs. This study presents a detailed investigation into the assumptions and application of the Odds Ratio which revealed the potential for over- and under-estimation of the metric depending on the core data and sampling assumptions. Furthermore, this research presents a comparative analysis of select driving simulator studies and an NDS considering only driving behaviour data as a means to consistently compare the findings of both methodologies. The findings from this investigation implores the need for greater consistency in the application of analysis methods and metrics across both simulator and NDSs. Improvements can yield a more robust platform to systematically compare and interpret data across both approaches, ultimately leading to enhanced planning and safety regarding mobile phone use while driving.
       
  • Comparison of empirical Bayes and propensity score methods for road safety
           evaluation: A simulation study
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Haojie Li, Daniel J. Graham, Hongliang Ding, Gang Ren Statistical evaluation of road safety interventions can be undertaken using a variety of different approaches, typically requiring different assumptions to obtain causal identification. In this paper, we conduct a simulation study to compare the performance of empirical Bayes (EB) and propensity score (PS) based methods, which have featured prominently in the recent literature, in settings with and without violation of key assumptions. The estimators considered include EB, inverse probability weighting (IPW), and Doubly Robust (DR) estimation. We find that while the EB approach has good finite sample properties when model assumptions are met, the consistency of this estimator is substantially diminished when the reference and treated sites follow different functions. The IPW estimator performs well in large samples, but requires a correctly specified PS model with sufficient overlap in covariate distributions between treated and control units. The DR estimator allows for violation of assumptions in either the regression or PS model, but not both. We find that this added level of robustness affords overall better performance than attained via EB or IPW estimation.
       
  • Engineering ethics within accident analysis models
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Sakineh Haghighattalab, An Chen, Yunxiao Fan, Reza Mohammadi The purpose of this paper is to further investigate engineering ethics and its gap within accident analysis models. In this paper, at first, the role of human factors in the occurrence of accidents is presented. Then engineering ethics as an element of human factors is proposed. It is suggested that engineering ethics can provide engineers with the necessary guidelines to avoid possible accidents arising from their decisions and actions. In addition, the Challenger and Columbia space shuttle case studies that demonstrate the role of engineering ethics in the prevention and occurrence of accidents are discussed. Then sequential, epidemiological, and systemic accident analysis models are briefly investigated and negligence of engineering ethics as a gap in the accident analysis models is described. At the end, we suggest that by implementing engineering ethics as a controller within the system boundary in systemic accident models we may be able to identify and prevent the ethical causes of accidents.
       
  • Key feature selection and risk prediction for lane-changing behaviors
           based on vehicles’ trajectory data
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Tianyi Chen, Xiupeng Shi, Yiik Diew Wong Risky lane-changing (LC) behavior of vehicles on the road has negative effects on traffic safety. This study presents a research framework for key feature selection and risk prediction of car’s LC behavior on the highway based on vehicles’ trajectory dataset. To the best of our knowledge, this is the first study that focuses on key feature selection and risk prediction for LC behavior on the highway. From the vehicles’ trajectory dataset, we extract car’s candidate features and apply fault tree analysis and k-Means clustering algorithm to determine the LC risk level based on the performance indicator of Crash Potential Index (CPI). Random Forest (RF) classifier is applied to select key features from car’s candidate features and predict LC risk level. This study also proposes a method to evaluate the resampling methods to resample the LC risk dataset in terms of fitness performance and prediction performance. The cars’ trajectory data collected from the Next Generation Simulation (NGSIM) dataset is used for framework development and verification. The sensitivity analysis of CPI indicates that the following cars in the original lane and target lane are respectively the safest and riskiest cars of the surrounding cars in an LC event. The results of resampling method evaluation show that SMOTETomek, which is less likely to be overfitting and has high prediction performance, is well suited for resampling the LC risk dataset on which RF classifier is trained. The results of key feature selection imply that the individual behaviors of the LC car and its surrounding cars in the original lane, the interactions between the LC car and its surrounding cars, and the interactions between the surrounding cars in the target lane (especially the interaction of the cars’ accelerations) are of importance to the LC risk.
       
  • Potential benefits of controlled vehicle braking to reduce pedestrian
           ground contact injuries
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Tiefang Zou, Shi Shang, Ciaran Simms Protecting struck pedestrians during the ground contact phase has been a challenge for decades. Recent studies have shown how ground related injury is influenced by pedestrian kinematics. In this paper we further developed this approach by assessing the potential of controlling vehicle braking to reduce pedestrian ground contact injuries. Applying a recently proposed Simulation Test Sample, a series of simulations were run using the MADYMO software environment. The approach considered 6 vehicle shapes, 4 pedestrian models, 3 impact velocities and 2 pedestrian gaits and each case was considered with two different vehicle braking approaches. The first was full braking, while the second applied controlled braking, for which a strategy based on pedestrian kinematics was applied. The effect of vehicle braking was evaluated using the Weighted Injury Cost (WIC) of overall pedestrian injuries and the pedestrian-ground impact velocity change. The proximity of the vehicle and pedestrian at the instant of ground contact was also evaluated to assess the potential of future vehicle based intervention methods to cushion the ground contact. Finally real-world videos of pedestrian collisions were analyzed to estimate the available free vehicle stopping distances. Results showed substantial median reductions in WIC and head impact velocity for all vehicle shapes except the Van. The proximity of the pedestrian to the vehicle front at the instant of ground contact under controlled braking is less than 1.5 m in most cases, and the required stopping distance for the vehicle under controlled braking was within the available stopping distance estimated from the video footage in about 74% of cases. It is concluded that controlled braking has significant potential to reduce the overall burden of pedestrian ground contact injuries, but future efforts are required to establish an optimized braking strategy as well as a means to handle those cases where controlled braking is not beneficial or even harmful.
       
  • A pedestrian serious injury risk prediction method based on posted speed
           limit
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Tetsuya Nishimoto, Kazuhiro Kubota, Giulio Ponte The purpose of this study was to develop a serious injury risk prediction algorithm for pedestrians, using data from the South Australian Traffic Accident Reporting System. Two algorithms were developed to estimate serious injury risk, using a logistic regression analysis of 6,868 vehicle-pedestrian crashes extracted from TARS data. In this study, an optimal model based on the best combination of risk factors according to the Akaike information criterion (AIC) was developed. Additionally, a secondary GPS model using only crash site characteristics that can be derived from GPS coordinates from the crash scene was also developed. The optimal model is based on site and environmental conditions that could be derived from GPS data (posted speed limit, distance from crash site, natural lighting conditions, road geometry, road horizontal alignment and road vertical alignment) as well as pedestrian age/gender, driver age/gender and vehicle model year. The second model only included features that could be derived from GPS data. The optimal model was reasonable in accuracy and gave an under-triage rate of 10% when the injury threshold was set to 15%, with a corresponding over-triage rate of around 60%. The GPS model, despite not being as accurate as the optimal model may be adequate in the absence of all the risk factors required for the optimal model, requiring an injury threshold of 20% to give an under-triage rate of 10%, with the corresponding over-triage rate being around 70%. Both models can potentially be used for serious injury risk prediction (SIRP) for pedestrians involved in a collision with a vehicle.
       
  • Traverses, delays and fatalities at railway level crossings in Great
           Britain
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Andrew W. Evans, Peter Hughes This paper investigates relationships between traverses, delays and fatalities to road users at railway level crossings in Great Britain. A ‘traverse’ means a passage across a level crossing by a road user, who may be a pedestrian, cyclist, or occupant of a road vehicle. The paper finds that the road users with the highest fatality rate per traverse are pedestrians at passive crossings. Their rate is about three orders of magnitude higher than that of users with the lowest risk, who are road vehicle occupants at railway-controlled crossings. The paper considers the choice between automatic and railway-controlled crossings on public roads. Railway-controlled crossings are widely used in Britain. They are about one order of magnitude safer than automatic crossings, but they impose greater delays on users. A formula is developed to give the overall delay to road users at either type of crossing in terms of the numbers of road users and trains per day, and in terms of the length of time that the crossing must be closed to the road to allow the passage of one train. It is found that automatic level crossings cause substantially less delay than railway-controlled level crossings. The official monetary values of road user delay and of preventing a fatality were used to estimate the valuations of delays and fatalities at hypothetical but representative automatic and railway-controlled crossings. These valuations were then used to explore the effect of replacing representative railway-controlled with automatic crossings or vice-versa. It is found that the valuation of the reduced delays from adopting automatic crossings typically outweighs the valuation of the losses from the increased casualties. However, in practice Britain has chosen to retain a large number of railway-controlled crossings, which implies accepting the delays in return for a good level crossing safety record. Finally, an analysis is carried out to determine the additional risk of typical car and walk journeys that involve traversing a level crossing compared with similar journeys that do not. It is found that the additional risk is small for motor vehicle journeys, but substantial for walk journeys.
       
  • Gap acceptance probability model for pedestrians at unsignalized mid-block
           crosswalks based on logistic regression
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Jing Zhao, Jairus Odawa Malenje, Yu Tang, Yin Han Gap acceptance represents a pedestrian’s assessment of how safe it may be to use an available gap in traffic flow at a particular point in time. Though walking is a major component of urban mobility, the high rate of fatal interaction with motor vehicle traffic raises safety issues around how pedestrians decide to accept the available gap. This paper explored these interactions by modeling gap acceptance behavior at the midblock crosswalks. Unlike other pedestrian gap acceptance studies that focus on individual psychological and sociological factors that are difficult to control or manage, this study focused on six environmental factors that we considered important and as having the potential to affect the pedestrians’ gap acceptance decision at the crosswalks, i.e. gap size, crossing distance, number of waiting pedestrians, waiting time, vehicle traffic volume and position of pedestrian (whether on street kerb or median). Video data was collected on pedestrian gap acceptance from 13 midblock crosswalk locations in Shanghai, China. A Logit model with 96% accuracy was developed to describe and predict the pedestrian gap acceptance behaviors. The results show that gap size and crossing distance have the highest effect on the pedestrian gap acceptance decision. Pedestrians waiting at the kerbside could confidently accept gaps (with a 95% probability) when the gap is longer than 2.2s, 5.9s, and 9.6s under the condition that the crossing distance is 4 m (one lane), 7.5 m (two lanes), and 11 m (three lanes), respectively while pedestrians waiting at the median could confidently accept gaps when the gap is longer than 1.6s, 5.3s, and 8.5s respectively under the same conditions. The recommendations on improving the crossing safety are proposed accordingly.
       
  • Effects of globally obtained informative priors on bayesian safety
           performance functions developed for Australian crash data
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Amir Pooyan Afghari, Md. Mazharul Haque, Simon Washington, Tanya Smyth The precision and bias of Safety Performance Functions (SPFs) heavily rely on the data upon which they are estimated. When local (spatially and temporally representative) data are not sufficiently available, the estimated parameters in SPFs are likely to be biased and inefficient. Estimating SPFs using Bayesian inference may moderate the effects of local data insufficiency in that local data can be combined with prior information obtained from other parts of the world to incorporate additional evidence into the SPFs. In past applications of Bayesian models, non-informative priors have routinely been used because incorporating prior information in SPFs is not straightforward. The previous few attempts to employ informative priors in estimating SPFs are mostly based on local prior knowledge and assuming normally distributed priors. Moreover, the unobserved heterogeneity in local data has not been taken into account. As such, the effects of globally derived informative priors on the precision and bias of locally developed SPFs are essentially unknown.This study aims to examine the effects of globally informative priors and their distribution types on the precision and bias of SPFs developed for Australian crash data. To formulate and develop global informative priors, the means and variances of parameter estimates from previous research were critically reviewed. Informative priors were generated using three methods: 1) distribution fitting, 2) endogenous specification of dispersion parameters, and 3) hypothetically increasing the strength of priors obtained from distribution fitting. In so doing, the mean effects of crash contributing factors across the world are significantly different than those same effects in Australia. A total of 25 Bayesian Random Parameters Negative Binomial SPFs were estimated for different types of informative priors across five sample sizes. The means and standard deviations of posterior parameter estimates as well as SPFs goodness of fit were compared between the models across different sample sizes. Globally informative prior for the dispersion parameter substantially increases the precision of a local estimate, even when the variance of local data likelihood is small. In comparison with the conventional use of Normal distribution, Logistic, Weibull and Lognormal distributions yield more accurate parameter estimates for average annual daily traffic, segment length and number of lanes, particularly when sample size is relatively small.
       
  • A forward collision avoidance algorithm based on driver braking behavior
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Xiaoxia Xiong, Meng Wang, Yingfeng Cai, Long Chen, Haneen Farah, Marjan Hagenzieker Measuring risk is critical for collision avoidance. The paper aims to develop an online risk level classification algorithm for forward collision avoidance systems. Assuming risk levels are reflected by braking profiles, deceleration curves from critical evasive braking events from the Virginia “100-car” database were first extracted. The curves are then clustered into different risk levels based on spectrum clustering, using curve distance and curve changing rate as dissimilarity metrics among deceleration curves. Fuzzy logic rules of safety indicators at critical braking onset for risk classification were then extracted according to the clustered risk levels. The safety indicators include time to collision, time headway, and final relative distance under emergency braking, which characterizes three kinds of uncertain critical conditions respectively. Finally, the obtained fuzzy risk level classification algorithm was tested and compared with other Automatic Emergency Braking (AEB) algorithms under Euro-NCAP testing scenarios in simulation. Results show the proposed algorithm is promising in balancing the objectives of avoiding collision and reducing interference with driver’s normal driving compared with other algorithms.
       
  • Age-related differences in the perception of gap affordances: Impact of
           standardized action capabilities on road-crossing judgements
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): James Stafford, Caroline Whyatt, Cathy M. Craig Recent road-crossing literature has found that older adults show performance differences between estimation and perception-action tasks suggesting an age-related difficulty in accurately calibrating the information picked up from the surrounding environment to their action capabilities (Lobjois and Cavallo, 2009). The present study investigated whether participants could accurately perceive gap affordances via information that specifies the time-to-arrival of the approaching cars. To ensure the opportunities for action were the same across different age groups, independent of the actor’s action capabilities, the action of crossing the road was standardised. A total of 45 participants (15 children, aged 10–12, 15 adults aged 19–39, 15 older adults aged 65+) were asked to judge, by pressing a button in a head-mounted display, whether the gap between oncoming cars afforded crossing. When the participant pressed the button, they moved across the road at a fixed speed. Adherence to a time-based variable (namely tau) explained 85% and 84% of the variance in both the children and adults’ choices, respectively. Older adults tuned less into the time-based variable (tau) with it only accounting for 59% of the variance in road-crossing decisions. These findings suggest that, the ability to use tau information which specifies whether a gap affords crossing or not, deteriorates with age.
       
  • An approach for evaluating the effectiveness of traffic guide signs at
           intersections
    • Abstract: Publication date: August 2019Source: Accident Analysis & Prevention, Volume 129Author(s): Xianglin Yao, Xiaohua Zhao, Hao Liu, Lihua Huang, Jianming Ma, Jizhou Yin Traffic guide signs play important roles in people’s daily lives. However, the effectiveness and performance of traffic guide signs at intersections are significantly impacted by many factors, such as the types of information on traffic signs, their information volume and comprehensibility, the behavioral attributes of drivers, the geometric features of roadways, and weather and visibility conditions. When deploying traffic guide signs, efforts are needed to clarify whether the installation of a traffic guide sign is warranted. In this study, a generic approach is developed to examine and evaluate the effectiveness of traffic guide signs using simulation experiments. A traffic guide sign evaluation method (TGSEM) is developed and illustrated using examples of traffic guide sign schemes in suburban Beijing. The questionnaires showed that most drivers feel that the current traffic guide signs in suburban Beijing are insufficient and need to be rectified. Then, simulation experiments were conducted. Based on subjective experiments, the ergonomic evaluation model (DCI, the abbreviation of demand, comprehension, and information volume) was obtained. Of the four schemes, scheme 3 was shown to be the most popular. During driving simulation experiments, the analyses of average speed, standard deviation (SD) of speed, average acceleration, standard deviation of acceleration, travel time, braking frequency and throttle power showed that scheme 2 had a better impact on drivers’ behavioral data. Finally, Grey relational analysis showed that scheme 2 has the highest degree of correlation and can be recommended to traffic management departments. The experimental tests and analysis results revealed that the TGSEM is suitable. The proposed approach provides a generic framework with which to assess the performance of traffic guide signs and their effectiveness at intersections, including their experimental design, data analysis, the implementation of simulation models, and data interpretation.
       
 
 
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