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Author:

Liu, X. (Liu, X..) | Zhao, X. (Zhao, X..) | Bian, Y. (Bian, Y..) | Wu, C. (Wu, C..) | Dong, W. (Dong, W..)

Indexed by:

EI Scopus SCIE

Abstract:

Traffic conflict commonly occurs in intersections with offset lane lines because of mismatched choices of entrance and exit lanes. This conflict drives down overall traffic efficiency and can cause crashes. At such intersections, the driver’s lane choice behavior seriously affects the traffic system. The theory of planned behavior (TPB) was used in this study to excavate the impact mechanism of drive-by-lane behavior at offset intersections. A scale incorporating TPB constructs and additional variables (risk perception [RP], traffic environment [TE], optimization measures [OM], and driving style [DS]) was developed to collect empirical data with 557 valid samples in China. A structural equation model of drivers’ drive-by-lane behavior was established to explore the causal relationship between behavior and influencing factors, as well as the interrelationships between TPB variables. TE, behavior intention (BI), subjective norms (SN), and RP show the most significant effects on drive-by-lane behavior. DS, perceived behavior control, attitude (ATT), and OM have little impact on drive-by-lane behavior. BI, TE, RP, and DS have significant, direct effects on drive-by-lane behavior. The TE, OM, and DS variables significantly affect drive-by-lane behavior through mediators. RP, BI, and ATT mediate the influence of other variables as well as affecting drive-by-lane behavior. We put forward suggestions to improve driving behavior at offset intersections including changing external factors, education, and training. The direct and indirect relationships between the influencing factors and drive-by-lane behavior are discussed in this paper to provide technical and reference support for future research on managing irregular urban traffic intersections. © National Academy of Sciences: Transportation Research Board 2024.

Keyword:

pedestrians statistical methods analysis human factors of infrastructure design and operations data and data science human factors cognitive workload bicycles modeling driver perception

Author Community:

  • [ 1 ] [Liu X.]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing, China
  • [ 2 ] [Zhao X.]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing, China
  • [ 3 ] [Bian Y.]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing, China
  • [ 4 ] [Wu C.]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing, China
  • [ 5 ] [Dong W.]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing, China

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Source :

Transportation Research Record

ISSN: 0361-1981

Year: 2024

Issue: 8

Volume: 2678

Page: 837-855

1 . 7 0 0

JCR@2022

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 11

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