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author:

Wang, Haolin (Wang, Haolin.) [1] | Zou, Fumin (Zou, Fumin.) [2] | Tian, Junshan (Tian, Junshan.) [3] | Guo, Feng (Guo, Feng.) [4] | Cai, Qiqin (Cai, Qiqin.) [5]

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EI

Abstract:

Toll stations are bottlenecks in the traffic flow of expressways, and the evaluation of their capacity is essential for the operation of the expressway. Traditional capacity studies are mostly based on theoretical modelling of traffic engineering or simulation, with a focus on parameter tuning and idealized hypotheses, resulting in poor reliability. In view of the coexistence of electronic toll collection lanes and compound toll collection lanes at toll stations of expressways in China, the present study analyses the capacity of entrance and exit lanes of toll stations under mixed traffic conditions using a real toll data-driven approach. Firstly, the service time of a single vehicle during the saturation period was taken as the starting point for the capacity estimates. Secondly, the variation in service time for multiple categories of vehicles is modelled using lognormal distribution. Finally, the capacity of the two types of toll lanes at the designated toll station is determined. The important outcome of this study is the calculation of authentic capacity at the toll stations and the discussion of individual special toll lanes. Accordingly, it contributes to the development of appropriate policies to manage the operation of the toll plaza effectively. © 2022 Haolin Wang et al.

Keyword:

Highway engineering Toll highways Traffic control

Community:

  • [ 1 ] [Wang, Haolin]Fujian Key Laboratory of Automotive Electronics and Electric Drive, Fujian University of Technology, Fujian, Fuzhou; 350118, China
  • [ 2 ] [Zou, Fumin]Fujian Key Laboratory of Automotive Electronics and Electric Drive, Fujian University of Technology, Fujian, Fuzhou; 350118, China
  • [ 3 ] [Tian, Junshan]Fujian Expressway Science & Technology Innovation Research Institute Co. Ltd., Fujian, Fuzhou; 350001, China
  • [ 4 ] [Guo, Feng]College of Mathematics and Computer Science, Fuzhou University, Fujian, Fuzhou; 350118, China
  • [ 5 ] [Cai, Qiqin]College of Mechanical Engineering and Automation, Huaqiao University, Fujian, Xiamen; 361021, China

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Source :

Journal of Advanced Transportation

ISSN: 0197-6729

Year: 2022

Volume: 2022

2 . 3

JCR@2022

2 . 0 0 0

JCR@2023

ESI HC Threshold:66

JCR Journal Grade:3

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 11

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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