• Complex
  • Title
  • Keyword
  • Abstract
  • Scholars
  • Journal
  • ISSN
  • Conference
搜索

Author:

Zhao, Xiaohua (Zhao, Xiaohua.) | Li, Xuewei (Li, Xuewei.) | Chen, Yufei (Chen, Yufei.) | Li, Haijian (Li, Haijian.) | Ding, Yang (Ding, Yang.)

Indexed by:

EI Scopus

Abstract:

Purpose: Heavy fog results in low visibility, which increases the probability and severity of traffic crashes, and fog warning system is conducive to the reduction of crashes by conveying warning messages to drivers. This paper aims at exploring the effects of dynamic message sign (DMS) of fog warning system on driver performance. Design/methodology/approach: First, a testing platform was established based on driving simulator and driver performance data under DMS were collected. The experiment route was consisted of three different zones (i.e. warning zone, transition zone and heavy fog zone), and mean speed, mean acceleration, mean jerk in the whole zone, ending speed in the warning zone and transition zone, maximum deceleration rate and mean speed reduction proportion in the transition zone and heavy fog zone were selected. Next, the one-way analysis of variance was applied to test the significant difference between the metrics. Besides, drivers’ subjective perception was also considered. Findings: The results indicated that DMS is beneficial to reduce speed before drivers enter the heavy fog zone. Besides, when drivers enter a heavy fog zone, DMS can reduce the tension of drivers and make drivers operate more smoothly. Originality/value: This paper provides a comprehensive approach for evaluating the effectiveness of the warning system in adverse conditions based on the driving simulation test platform. The method can be extended to the evaluation of vehicle-to-infrastructure technology in other special scenarios. © 2021, Xiaohua Zhao, Xuewei Li, Yufei Chen, Haijian Li and Yang Ding.

Keyword:

Variable message signs Simulation platform Message passing Advanced traveler information systems Fog Automobile simulators

Author Community:

  • [ 1 ] [Zhao, Xiaohua]Beijing University of Technology, Beijing, China
  • [ 2 ] [Zhao, Xiaohua]Tsinghua University State Key Laboratory of Automotive Safety and Energy, Beijing, China
  • [ 3 ] [Li, Xuewei]Beijing University of Technology, Beijing, China
  • [ 4 ] [Li, Xuewei]Tsinghua University State Key Laboratory of Automotive Safety and Energy, Beijing, China
  • [ 5 ] [Chen, Yufei]China Automotive Engineering Research Institute, Beijing, China
  • [ 6 ] [Li, Haijian]Beijing University of Technology, Beijing, China
  • [ 7 ] [Ding, Yang]Beijing University of Technology, Beijing, China

Reprint Author's Address:

Email:

Show more details

Related Keywords:

Related Article:

Source :

Journal of Intelligent and Connected Vehicles

Year: 2021

Issue: 2

Volume: 4

Page: 41-51

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 15

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

Affiliated Colleges:

Online/Total:213/10560694
Address:BJUT Library(100 Pingleyuan,Chaoyang District,Beijing 100124, China Post Code:100124) Contact Us:010-67392185
Copyright:BJUT Library Technical Support:Beijing Aegean Software Co., Ltd.