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Author:

Li, Haijian (Li, Haijian.) | Zhao, Guoqiang (Zhao, Guoqiang.) | Yang, Yanfang (Yang, Yanfang.) | Chang, Xin (Chang, Xin.) | Zhao, Xiaohua (Zhao, Xiaohua.)

Indexed by:

EI Scopus CSCD

Abstract:

Emergency braking event of the vehicle in front is one of the main causes of a forward collision. If the driver can sense the emergency braking event of the vehicle in front timely, the coping behavior can be changed from passive visual stimulation to active coping behavior based on psychological expectation, which will greatly reduce the accident rate. Based on driving simulation technology, an emergency braking event in the cooperative vehicle infrastructure system was designed to provide the emergency braking warning information of the vehicle in front with the vehicle-mounted Human Machine Interface (HMI) at the distance of 360 m and 290 m. Driving behavior data and evaluation indexes were obtained from driving behaviors of qualified drivers in the driving simulation experi-ment. After a comparative analysis of driving behavior data with and without HMI warning information, a method was proposed for analyzing the driving characteristics of the emergency braking event of the vehicle in front in the cooperative vehicle infrastructure system based on spatiotemporal diagram. The driving confidence characteristics of 35 drivers in emergency braking event were analyzed based on their average acceleration characteristics. The results show that when the HMI warning information is available, the drivers tend to decelerate earlier with lower speed control intensity than that when the HMI warning information is not available. According to the curvature index, the speed control intensity is reduced by 39.4%. When the HMI warning information is available, the speed control is more leisurely, and the drivers can proactively respond to the risk environment with the characteristics of driving confidence. © 2020, Editorial Department, Journal of South China University of Technology. All right reserved.

Keyword:

Braking Speed control Speed regulators Vehicles Behavioral research Accidents

Author Community:

  • [ 1 ] [Li, Haijian]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Zhao, Guoqiang]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Yang, Yanfang]Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, China Academy of Transportation Sciences, MOT, Beijing; 100029, China
  • [ 4 ] [Chang, Xin]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 5 ] [Zhao, Xiaohua]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing; 100124, China

Reprint Author's Address:

  • [yang, yanfang]key laboratory of transport industry of big data application technologies for comprehensive transport, china academy of transportation sciences, mot, beijing; 100029, china

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Source :

Journal of South China University of Technology (Natural Science)

ISSN: 1000-565X

Year: 2020

Issue: 7

Volume: 48

Page: 76-84

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 3

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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