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Author:

Chang, Xin (Chang, Xin.) | Rong, Jian (Rong, Jian.) | Li, Haijian (Li, Haijian.) | Wu, Yiping (Wu, Yiping.) | Zhao, Xiaohua (Zhao, Xiaohua.)

Indexed by:

SSCI EI Scopus SCIE

Abstract:

In view of the benefits and a promising prospect of the emerging connected vehicles (CV), more and more vehicles will be equipped with the in-vehicle human-machine interface (HMI). This study aims to assess the comprehensive impacts of HMIs on individual driving performance, traffic safety, and eco-driving behaviour based on a driving simulator. In order to explore how a driver responds to warnings when approaching a tunnel, this study divided the experimental road into five zones according to warning positions. A comparative analysis was conducted to examine the changes in driving comfort, speeding behaviour, the standard deviation of speed, time headway (THW), fuel consumption, and emissions. Results showed that the HMI could be beneficial to speed adjustment before entering a tunnel. Meanwhile, HMI may affect the THW of vehicles. Drivers were usually more cautious when the HMI was on. However, no significant effects of the HMI for driving comfort and eco-driving behaviour can be observed. It is expected that more efficient technology and different warning strategies can be developed to enhance eco-safe driving for different zones because they have different effects. The findings of this study are also helpful for active safety management and for evaluating the effectiveness of CV systems.

Keyword:

Author Community:

  • [ 1 ] [Chang, Xin]Beijing Univ Technol, Beijing Key Lab Traff Engn, 100 Pingleyuan, Beijing, Peoples R China
  • [ 2 ] [Rong, Jian]Beijing Univ Technol, Beijing Key Lab Traff Engn, 100 Pingleyuan, Beijing, Peoples R China
  • [ 3 ] [Li, Haijian]Beijing Univ Technol, Beijing Key Lab Traff Engn, 100 Pingleyuan, Beijing, Peoples R China
  • [ 4 ] [Wu, Yiping]Beijing Univ Technol, Beijing Key Lab Traff Engn, 100 Pingleyuan, Beijing, Peoples R China
  • [ 5 ] [Zhao, Xiaohua]Beijing Univ Technol, Beijing Key Lab Traff Engn, 100 Pingleyuan, Beijing, Peoples R China

Reprint Author's Address:

  • [Li, Haijian]Beijing Univ Technol, Beijing Key Lab Traff Engn, 100 Pingleyuan, Beijing, Peoples R China

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Source :

IET INTELLIGENT TRANSPORT SYSTEMS

ISSN: 1751-956X

Year: 2021

Issue: 3

Volume: 15

Page: 423-431

2 . 7 0 0

JCR@2022

ESI Discipline: ENGINEERING;

ESI HC Threshold:87

JCR Journal Grade:3

Cited Count:

WoS CC Cited Count: 29

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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