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Author:

Wei, Zhonghua (Wei, Zhonghua.) | Liu, Sheng (Liu, Sheng.) | Qiu, Shi (Qiu, Shi.) | Zhang, Tongyang (Zhang, Tongyang.) | Wang, Shaofan (Wang, Shaofan.)

Indexed by:

SSCI EI Scopus SCIE

Abstract:

Freeway landscape design is closely related to driver performance. How to stimulate drivers' positive physiological condition and improve overall driving performance by adopting ideal landscape design has become a research interest in recent years. This study explores the impact of changing the landscape pattern at appropriate intervals on driver fatigue and negative mental workload. Drivers' mental performance was evaluated under three types of spatial patterns: open, semi-open, and vertical. Thirty drivers, 15 Type A Behavior Pattern (TABP) and 15 Type B Behavior Pattern (TBBP) drivers, respectively, were recruited to conduct the driving simulator experiment. Data on drivers' physiological variation trends show that the mental workload of TABP and TBBP drivers varied under different spatial patterns. The principal factor high frequency (HF) was used to investigate the distance threshold for different freeway landscape patterns based on the analysis of physiological data collected by electrocardiogram (ECG). This study reveals that changing landscape pattern at a certain interval can benefit drivers' physical and mental status. It is suggested that, when the design speed is 100 km/h, changing landscape pattern every 11 km can reduce fatigue and improve driving performance in both TABP and TBBP drivers. The conclusions of this study provide a rationale and guidance for agencies to adopt different spatial patterns in future freeway landscape design.

Keyword:

Author Community:

  • [ 1 ] [Wei, Zhonghua]Beijing Univ Technol, Beijing Key Lab Traff Engn, Beijing, Peoples R China
  • [ 2 ] [Liu, Sheng]Beijing Univ Technol, Beijing Key Lab Traff Engn, Beijing, Peoples R China
  • [ 3 ] [Qiu, Shi]Beijing Univ Technol, Beijing Key Lab Traff Engn, Beijing, Peoples R China
  • [ 4 ] [Zhang, Tongyang]China Highway Engn Consulting Corp, Beijing, Peoples R China
  • [ 5 ] [Wang, Shaofan]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Multimedia & Intelligent Software, Beijing, Peoples R China

Reprint Author's Address:

  • [Wang, Shaofan]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Multimedia & Intelligent Software, Beijing, Peoples R China

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Source :

TRANSPORTATION RESEARCH RECORD

ISSN: 0361-1981

Year: 2018

Issue: 39

Volume: 2672

Page: 52-60

1 . 7 0 0

JCR@2022

ESI Discipline: ENGINEERING;

ESI HC Threshold:156

JCR Journal Grade:4

Cited Count:

WoS CC Cited Count: 1

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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