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Author:

Liu, Lili (Liu, Lili.) | Weng, Jiancheng (Weng, Jiancheng.) | Rong, Jian (Rong, Jian.) (Scholars:荣建)

Indexed by:

EI Scopus

Abstract:

The capacity of freeway toll station directly determines the freeway capacity and generally restricts the freeway operational status. With the techniques development and application of the electronic toll collection (ETC) system, a large number of mixed toll stations with manual toll collection (MTC) lanes and ETC lanes emerge. The capacity of mixed toll station is an important issue for toll system design. This paper respectively analyzed the traffic flow characteristics of MTC lane and the ETC lane, established a VISSIM simulation model combined with field survey data and calibration of parameters. As a result, the paper obtained the reasonable traffic capacity of toll plaza in cases of different proportions of MTC lanes and ETC lanes. Besides, it gave the best ETC traffic ratio of total traffic when the overall traffic capacity is optimal. In addition, the study also estimated the capabilities in cases of ETC traffic flow accounted for 10%, 30%, 50% under a certain traffic volume input. The conclusions provide important references for a reasonable traffic capacity determination of the mixed toll stations and for setting new-open ETC lanes.

Keyword:

Street traffic control Intelligent systems Intelligent vehicle highway systems Traffic surveys Toll collection

Author Community:

  • [ 1 ] [Liu, Lili]Transportation Research Center, Beijing University of Technology, No.100 Pingleyuan, Chaoyang, Beijing, 100124, China
  • [ 2 ] [Weng, Jiancheng]Transportation Research Center, Beijing University of Technology, No.100 Pingleyuan, Chaoyang, Beijing, 100124, China
  • [ 3 ] [Rong, Jian]Transportation Research Center, Beijing University of Technology, No.100 Pingleyuan, Chaoyang, Beijing, 100124, China

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Source :

Year: 2012

Page: AP-00012

Language: English

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: 8

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