Bus bunching simulation based on the lattice Boltzmann model of traffic flow

IF 1.3 4区 工程技术 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Xiaoshi Wang, Tao Liu, Meng Xu
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引用次数: 2

Abstract

Bus bunching is a typical phenomenon observed in daily public transit operations and that significantly reduces the reliability and attractiveness of transit service. Although various control strategies, such as vehicle holding, speed guidance, and signal priority, have been proposed to eliminate or alleviate bus bunching, the impact of road traffic flow on bus bunching has not been well studied. To bridge this gap, this work proposes a new mesoscopic simulation model by incorporating the lattice Boltzmann model to simulate bus bunching considering the impacts of road traffic flow. Simulation results show that by utilizing the new simulation model, different phase diagrams can be observed. Under different conditions of traffic flow-density evolution, i.e., no oscillation, single oscillation, global oscillation, and irregular oscillation, the resulting bus trajectories are significantly different. In addition, an investigation of a real-world bus line in Beijing with global positioning system (GPS)-based vehicle location data shows that some results of the model are qualitatively consistent with the actual characteristics of the bus route. It shows that the proposed new simulation model has great potential for enhancing our understanding of the impacts of road traffic flow on bus bunching.
基于点阵玻尔兹曼模型的交通流公交集群仿真
公交车拥挤是日常公共交通运行中的典型现象,严重降低了公共交通服务的可靠性和吸引力。尽管人们提出了各种控制策略,如车辆保持、速度引导和信号优先等,以消除或减轻公交车聚集,但道路交通流对公交车聚集的影响尚未得到很好的研究。为了弥补这一差距,本研究提出了一种新的介观模拟模型,通过结合晶格玻尔兹曼模型来模拟考虑道路交通流影响的公交车聚集。仿真结果表明,利用新的仿真模型可以观察到不同的相图。在不同的交通流密度演化条件下,即不振荡、单一振荡、整体振荡和不规则振荡,所得到的公交车轨迹存在显著差异。此外,利用基于全球定位系统(GPS)的车辆定位数据对北京一条真实公交线路进行了调查,结果表明,该模型的部分结果与公交线路的实际特征在质量上是一致的。结果表明,本文提出的仿真模型对提高我们对道路交通流对公交车聚集的影响的认识具有很大的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.50
自引率
31.20%
发文量
60
审稿时长
3 months
期刊介绍: SIMULATION is a peer-reviewed journal, which covers subjects including the modelling and simulation of: computer networking and communications, high performance computers, real-time systems, mobile and intelligent agents, simulation software, and language design, system engineering and design, aerospace, traffic systems, microelectronics, robotics, mechatronics, and air traffic and chemistry, physics, biology, medicine, biomedicine, sociology, and cognition.
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