一种新的人群运输仿真框架

Q2 Decision Sciences International Journal of Crowd Science Pub Date : 2021-11-01 DOI:10.1108/IJCS-07-2021-0019
Zhihui Li;Hongbo Sun
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引用次数: 0

摘要

目的随着现代经济的发展,车辆不再是人们的奢侈品,极大地方便了人们的日常生活,但同时也带来了交通拥堵。如何缓解交通拥堵,提高通行能力是目前研究的热点。本文旨在提出一种新的人群交通模拟框架,以缓解交通拥堵。设计/方法论/方法本文建立了相关的仿真模型,如车辆、红绿灯和顾问。然后描述了它们之间的关系,给出了它们的交互机制,并将其固化为一个软件实现框架。发现本文提出了一个用于人群运输的仿真框架。独创性/价值在这个框架中,红绿灯被用作控制道路网络的控制方法,道路状况被用作影响个人行为的因素。车辆通过率由禀赋和红绿灯启动时间之间的相关性来定义。在这个框架中,成员是相关的,根据路况进行动态调整,并动态优化成员决策。最佳路径是动态的,每向前走一步都会进行实时调整。它不同于只有一个固定路径的传统最优路径,也不同于不存在的宏观最优路径。
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A novel simulation framework for crowd transportations
Purpose – With the development of the modern economy, vehicles are no longer a luxury for people, which greatly facilitate people's daily life, but at the same time bring traffic congestion. How to relieve traffic congestion and improve its capacity is a hot research area. This paper aims to propose a new simulation framework for crowd transportations to ease traffic congestion. Design/methodology/approach – This paper establishes related simulation models such as vehicles, traffic lights and advisers. Then the paper describes their relationships, gives their interaction mechanism and solidifies the above into a software implementation framework. Findings – This paper proposes a simulation framework for crowd transportations. Originality/value – In this framework, traffic lights are used as a control method to control the road network and road conditions are used as an Affecter to influence individual behavior. The vehicle passing rate is defined by the correlation between endowment and the start time of the traffic lights. In this framework, members are related, dynamically adjusted according to road conditions and dynamically optimized member decisions. The optimal path is dynamic and real-time adjustments are made for each step forward. It is different from the traditional optimal path in which there is only one fixed one and it is different from the macroscopic optimal path that does not exist.
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来源期刊
International Journal of Crowd Science
International Journal of Crowd Science Decision Sciences-Decision Sciences (miscellaneous)
CiteScore
2.70
自引率
0.00%
发文量
20
审稿时长
24 weeks
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