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Author:

Zhang, Jianhua (Zhang, Jianhua.) | Zhao, Xiaohua (Zhao, Xiaohua.) (Scholars:赵晓华) | Li, Haijian (Li, Haijian.) | Qi, Jianyu (Qi, Jianyu.) | Xing, Guanyang (Xing, Guanyang.)

Indexed by:

EI Scopus SCIE

Abstract:

The change of space environment at the tunnel entrance which the light changes from bright to dark will lead to frequent traffic accidents. To explore whether the connected vehicle environment will improve the driving performance and traffic safety at the tunnel entrance, this paper first of all designed a driving simulation experiment and provided driving aids through the Human-Machine Interface (HMI). Then 35 drivers were invited to take a driving simulation under two different driving conditions: traditional driving environment (HMI-OFF) and connected vehicle environment (HMI-ON). Finally, the effectiveness and safety of HMI can be evaluated from two aspects of driver response efficiency and deceleration process, and further explore the causes of driving behavior changes by Cox model. The results show that the driver's response efficiency and deceleration behavior are both improved in the connected vehicle environment. The warning information provided by in-vehicle HMI enables the driver to know the road conditions ahead earlier and adjust the speed through more gentle acceleration so that the vehicle can enter the tunnel at a more stable speed. At the same time, there are significant differences in the brake-movement time of different driving ages, which the brake-movement time increases with the driving age. This indicates that experienced drivers usually adopt a soft way to adjust the speed, so that the vehicle speed change process is more stable on the premise of ensuring driving safety, so as to avoid the potential danger brought by drastic speed change. In this paper, a validity evaluation method based on survival analysis is proposed for tunnel entrance scenarios, which provides a reference for the realization of connected vehicle evaluation.

Keyword:

transport survival analysis human-machine interface Connected vehicle environment

Author Community:

  • [ 1 ] [Zhang, Jianhua]Beijing Univ Technol, Beijing Key Lab Traff Engn, Beijing 100124, Peoples R China
  • [ 2 ] [Zhao, Xiaohua]Beijing Univ Technol, Beijing Key Lab Traff Engn, Beijing 100124, Peoples R China
  • [ 3 ] [Li, Haijian]Beijing Univ Technol, Beijing Key Lab Traff Engn, Beijing 100124, Peoples R China
  • [ 4 ] [Qi, Jianyu]China Merchants New Intelligence Technol Co Ltd, Beijing 100124, Peoples R China
  • [ 5 ] [Xing, Guanyang]Southeast Univ, Sch Transportat, Jiangsu Key Lab Urban ITS, Nanjing 211189, Peoples R China

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Source :

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

ISSN: 1524-9050

Year: 2023

Issue: 11

Volume: 24

Page: 11699-11709

8 . 5 0 0

JCR@2022

ESI Discipline: ENGINEERING;

ESI HC Threshold:19

Cited Count:

WoS CC Cited Count: 6

SCOPUS Cited Count: 9

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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