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Aug 12, 2020
Exploring Driver’s Deceleration Behavior in Car-Following: A Driving Simulator Study
Authors: Junyu Hang [email protected], Xuedong Yan [email protected], Ke Duan [email protected], Xiaomeng Li [email protected], and Jingsi Yang [email protected]Author Affiliations
Publication: CICTP 2020
ABSTRACT
Rear-end collisions are very common, usually occurring when a lead vehicle brakes suddenly and a following driver responds too slowly. To reduce collision rates, collision avoidance systems (CASs) have been adopted. The CAS uses a series of algorithms to trigger an alert and/or brake control to help drivers avoid collisions. However, key variables have been considered fixed values in algorithms. Detecting vehicles’ deceleration might also take seconds, extending the judgement time of CASs. The study explored following drivers’ deceleration behavior patterns. A driving simulator experiment with forty-six participants was conducted in which a leading vehicle decelerated at different rates. Results showed that change of deceleration rate was a key variable representing drivers’ deceleration urgency, correlating with the leading vehicle’s deceleration rate. More than 90% of drivers reached a maximum change of deceleration rate within 0.5 s. The study supports using change of deceleration rate as an indicator in CAS.
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© 2020 American Society of Civil Engineers.
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Published online: Aug 12, 2020
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1MOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong Univ., Beijing 100044, PR China. Email: [email protected]
2MOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong Univ., Beijing 100044, PR China. Email: [email protected]
3MOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong Univ., Beijing 100044, PR China. Email: [email protected]
4Centre for Accident Research and Road Safety-Queensland (CARRS-Q), Institute of Health and Biomedical Innovation (IHBI), Queensland Univ. of Technology, 130 Victoria Park Rd., Kelvin Grove, QLD 4059, Australia. Email: [email protected]
5MOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong Univ., Beijing 100044, PR China. Email: [email protected]
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