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Analysis of rear-end crash potential and driver contributing factors based on car-following driving simulation

Lerdmanus Bumrungsup, Kunnawee Kanitpong

2022Traffic Injury Prevention17 citationsDOI

Abstract

OBJECTIVE: The purpose of the study was to investigate the factors associating the car-following behavior, which could lead to rear-end crash potential. The safe distance in this study was when the traffic flow was in an asymptotic stability state. METHOD: Traffic flow observation was conducted to observe how vehicle characteristics associating car-following behavior. However, it was not possible to determine the driver characteristics and their driving habits using the traffic flow observation alone. Therefore, a driving simulation and questionnaires were used in combination to investigate how driving characteristics were associate with car-following behavior. RESULT: From the two observation methods, several factors were found to significantly associate the rear-end crash potential including vehicle types, traveling lanes, the purposes of vehicle usage, age, income, the number of driving hours per week, stress, and anger or aggressive behavior. CONCLUSION: The traffic flow observation indicated that among the different types of vehicles, sedan/hatchback cars were more likely to be involved in rear-end crashes than others type of vehicles. Vehicles using the high-speed lane typically drove closer to each other and had a higher chance of rear-end collisions. The observation of driver characteristics showed that younger and high-income drivers were more likely to drive with less gap, resulting in higher possibilities of a rear-accident. Despite being in a normal emotional state, drivers with high frequency of stress, anger or aggression while driving had shorter headway distances and were more likely to cause rear-end collisions.

Topics & Concepts

CrashHeadwayPoison controlAggressive drivingAutomotive engineeringAngerTraffic flow (computer networking)EngineeringAlertnessTransport engineeringSimulationAeronauticsHuman factors and ergonomicsComputer sciencePsychologyComputer securitySocial psychologyMedicineEnvironmental healthPsychiatryProgramming languageTraffic and Road SafetyTraffic control and managementAutonomous Vehicle Technology and Safety
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