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Author:

Huang, Lihua (Huang, Lihua.) | Zhao, Xiaohua (Zhao, Xiaohua.) | Li, Yang (Li, Yang.) | Rong, Jian (Rong, Jian.) (Scholars:荣建)

Indexed by:

SSCI EI Scopus SCIE

Abstract:

Many diagrammatic guide signs in China have become much more complex and more difficult to read than those in other countries. Furthermore, there are few regulations or studies regarding diagrammatic guide signs in China. A driving simulator experiment was conducted to analyze the influence of five typical diagrammatic guide signs with different complexities on driving behavior and to evaluate their comprehensive guidance effectiveness via the Technique for Order of Preference by Similarity to Ideal Solution. The rANOVA results indicated that different diagrammatic guide signs have significantly different impacts on driving behavior. A higher complexity of the diagrammatic guide signs negatively impacted the subjective perception, operating status and maneuvering behavior. With increasing diagrammatic guide sign complexity, the gas pedal power significantly decreased at distances of 150-200 m and 50-100 m prior to the signs, the deceleration rapidly increased 150-200 m prior to the signs, the standard deviation of deceleration increased 100-150 m prior to the signs, the standard deviation of speed increased 50-100 m prior to the signs, and the speed decreased and driving time increased 0-50 m prior to the signs. Eight indicators were used to synthetically evaluate the comprehensive guidance effectiveness of the five types of diagrammatic guide signs. The final ranking (from best to worst) of the five diagrammatic guide signs with regard to their effectiveness was obtained. On the whole, a negative correlation relationship exists between the complexity and the comprehensive guidance effectiveness of the five types of diagrammatic guide signs. This relationship should be taken into account when designing new diagrammatic guide signs and optimizing complex diagrammatic guide signs in the future.

Keyword:

Diagrammatic guide sign Urban expressway TOPSIS Driving simulator experiment Driving behavior

Author Community:

  • [ 1 ] [Huang, Lihua]Beijing Univ Technol, Beijing Collaborat Innovat Ctr Metropolitan Trans, Beijing Key Lab Traff Engn, Coll Metropolitan Transportat, Beijing 100124, Peoples R China
  • [ 2 ] [Zhao, Xiaohua]Beijing Univ Technol, Beijing Collaborat Innovat Ctr Metropolitan Trans, Beijing Key Lab Traff Engn, Coll Metropolitan Transportat, Beijing 100124, Peoples R China
  • [ 3 ] [Rong, Jian]Beijing Univ Technol, Beijing Collaborat Innovat Ctr Metropolitan Trans, Beijing Key Lab Traff Engn, Coll Metropolitan Transportat, Beijing 100124, Peoples R China
  • [ 4 ] [Huang, Lihua]Beijing Res Ctr Urban Syst Engn, Urban Safety Res Dept, Beijing 100089, Peoples R China
  • [ 5 ] [Li, Yang]Beijing Police Coll, Beijing 102202, Peoples R China

Reprint Author's Address:

  • [Zhao, Xiaohua]Beijing Univ Technol, Beijing Collaborat Innovat Ctr Metropolitan Trans, Beijing Key Lab Traff Engn, Coll Metropolitan Transportat, Beijing 100124, Peoples R China

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Source :

COGNITION TECHNOLOGY & WORK

ISSN: 1435-5558

Year: 2019

Issue: 4

Volume: 22

Page: 843-860

2 . 6 0 0

JCR@2022

ESI Discipline: PSYCHIATRY/PSYCHOLOGY;

ESI HC Threshold:109

JCR Journal Grade:4

Cited Count:

WoS CC Cited Count: 5

SCOPUS Cited Count: 6

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 15

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