4.2 Article

Dynamic Evolution Simulation of Bus Bunching Affected by Traffic Operation State

Journal

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
Volume E106D, Issue 5, Pages 746-755

Publisher

IEICE-INST ELECTRONICS INFORMATION COMMUNICATION ENGINEERS
DOI: 10.1587/transinf.2022DLP0047

Keywords

bus bunching; headway; SOM; dynamic evolution; simulation

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This paper investigates the influence of the discrete distribution of traffic operation state on bus bunching, using GPS data of the No. 600 bus line in Xi'an. The study finds that inter vehicle speed, queuing time at intersection, and loading time at station have a significant impact on headway between buses. The research results provide insights for formulating improvement measures to balance bus headway and alleviate bus bunching based on the traffic operation state.
Bus bunching often occurs in public transit system, re-sulting 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 dis-crete 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 sig-nificant impact on headway between buses. In terms of the impact of the distribution of crowded road sections on headway, long-distance and con-centrated 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 distri-bution 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.

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