Dynamic Evolution Simulation of Bus Bunching Affected by Traffic Operation State

Shaorong HU; Yuqi ZHANG; Yuefei JIN; Ziqi DOU

doi:10.1587/transinf.2022DLP0047

Dynamic Evolution Simulation of Bus Bunching Affected by Traffic Operation State

Shaorong HU, Yuqi ZHANG, Yuefei JIN, Ziqi DOU

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Bus bunching often occurs in public transit system, resulting in a series of problems such as poor punctuality, long waiting time and low service quality. In this paper, we explore the influence of the discrete distribution of traffic operation state on the dynamic evolution of bus bunching. Firstly, we use self-organizing map (SOM) to find the threshold of bus bunching and analyze the factors that affect bus bunching based on GPS data of No. 600 bus line in Xi'an. Then, taking the bus headway as the research index, we construct the bus bunching mechanism model. Finally, a simulation platform is built by MATLAB to examine the trend of headway when various influencing factors show different distribution states along the bus line. In terms of influencing factors, inter vehicle speed, queuing time at intersection and loading time at station are shown to have a significant impact on headway between buses. In terms of the impact of the distribution of crowded road sections on headway, long-distance and concentrated crowded road sections will lead to large interval or bus bunching. When the traffic states along the bus line are randomly distributed among crowded, normal and free, the headway may fluctuate in a large range, which may result in bus bunching, or fluctuate in a small range and remain relatively stable. The headway change curve is determined by the distribution length of each traffic state along the bus line. The research results can help to formulate improvement measures according to traffic operation state for equilibrium bus headway and alleviating bus bunching.

Publication: IEICE TRANSACTIONS on Information Vol.E106-D No.5 pp.746-755

Publication Date: 2023/05/01

Publicized: 2022/04/13

Online ISSN: 1745-1361

DOI: 10.1587/transinf.2022DLP0047

Type of Manuscript: Special Section PAPER (Special Section on Deep Learning Technologies: Architecture, Optimization, Techniques, and Applications)

Category: Intelligent Transportation Systems

Authors

Shaorong HU
  Chang'an University
Yuqi ZHANG
  Chang'an University
Yuefei JIN
  Chang'an University
Ziqi DOU
  Dalian Maritime University

Keyword

bus bunching, headway, SOM, dynamic evolution, simulation

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Shaorong HU, Yuqi ZHANG, Yuefei JIN, Ziqi DOU, "Dynamic Evolution Simulation of Bus Bunching Affected by Traffic Operation State" in IEICE TRANSACTIONS on Information, vol. E106-D, no. 5, pp. 746-755, May 2023, doi: 10.1587/transinf.2022DLP0047.
Abstract: Bus bunching often occurs in public transit system, resulting in a series of problems such as poor punctuality, long waiting time and low service quality. In this paper, we explore the influence of the discrete distribution of traffic operation state on the dynamic evolution of bus bunching. Firstly, we use self-organizing map (SOM) to find the threshold of bus bunching and analyze the factors that affect bus bunching based on GPS data of No. 600 bus line in Xi'an. Then, taking the bus headway as the research index, we construct the bus bunching mechanism model. Finally, a simulation platform is built by MATLAB to examine the trend of headway when various influencing factors show different distribution states along the bus line. In terms of influencing factors, inter vehicle speed, queuing time at intersection and loading time at station are shown to have a significant impact on headway between buses. In terms of the impact of the distribution of crowded road sections on headway, long-distance and concentrated crowded road sections will lead to large interval or bus bunching. When the traffic states along the bus line are randomly distributed among crowded, normal and free, the headway may fluctuate in a large range, which may result in bus bunching, or fluctuate in a small range and remain relatively stable. The headway change curve is determined by the distribution length of each traffic state along the bus line. The research results can help to formulate improvement measures according to traffic operation state for equilibrium bus headway and alleviating bus bunching.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2022DLP0047/_p

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@ARTICLE{e106-d_5_746,
author={Shaorong HU, Yuqi ZHANG, Yuefei JIN, Ziqi DOU, },
journal={IEICE TRANSACTIONS on Information},
title={Dynamic Evolution Simulation of Bus Bunching Affected by Traffic Operation State},
year={2023},
volume={E106-D},
number={5},
pages={746-755},
abstract={Bus bunching often occurs in public transit system, resulting in a series of problems such as poor punctuality, long waiting time and low service quality. In this paper, we explore the influence of the discrete distribution of traffic operation state on the dynamic evolution of bus bunching. Firstly, we use self-organizing map (SOM) to find the threshold of bus bunching and analyze the factors that affect bus bunching based on GPS data of No. 600 bus line in Xi'an. Then, taking the bus headway as the research index, we construct the bus bunching mechanism model. Finally, a simulation platform is built by MATLAB to examine the trend of headway when various influencing factors show different distribution states along the bus line. In terms of influencing factors, inter vehicle speed, queuing time at intersection and loading time at station are shown to have a significant impact on headway between buses. In terms of the impact of the distribution of crowded road sections on headway, long-distance and concentrated crowded road sections will lead to large interval or bus bunching. When the traffic states along the bus line are randomly distributed among crowded, normal and free, the headway may fluctuate in a large range, which may result in bus bunching, or fluctuate in a small range and remain relatively stable. The headway change curve is determined by the distribution length of each traffic state along the bus line. The research results can help to formulate improvement measures according to traffic operation state for equilibrium bus headway and alleviating bus bunching.},
keywords={},
doi={10.1587/transinf.2022DLP0047},
ISSN={1745-1361},
month={May},}

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TY - JOUR
TI - Dynamic Evolution Simulation of Bus Bunching Affected by Traffic Operation State
T2 - IEICE TRANSACTIONS on Information
SP - 746
EP - 755
AU - Shaorong HU
AU - Yuqi ZHANG
AU - Yuefei JIN
AU - Ziqi DOU
PY - 2023
DO - 10.1587/transinf.2022DLP0047
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E106-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2023
AB - Bus bunching often occurs in public transit system, resulting in a series of problems such as poor punctuality, long waiting time and low service quality. In this paper, we explore the influence of the discrete distribution of traffic operation state on the dynamic evolution of bus bunching. Firstly, we use self-organizing map (SOM) to find the threshold of bus bunching and analyze the factors that affect bus bunching based on GPS data of No. 600 bus line in Xi'an. Then, taking the bus headway as the research index, we construct the bus bunching mechanism model. Finally, a simulation platform is built by MATLAB to examine the trend of headway when various influencing factors show different distribution states along the bus line. In terms of influencing factors, inter vehicle speed, queuing time at intersection and loading time at station are shown to have a significant impact on headway between buses. In terms of the impact of the distribution of crowded road sections on headway, long-distance and concentrated crowded road sections will lead to large interval or bus bunching. When the traffic states along the bus line are randomly distributed among crowded, normal and free, the headway may fluctuate in a large range, which may result in bus bunching, or fluctuate in a small range and remain relatively stable. The headway change curve is determined by the distribution length of each traffic state along the bus line. The research results can help to formulate improvement measures according to traffic operation state for equilibrium bus headway and alleviating bus bunching.
ER -