基于遗传算法和多智能体的交通拥堵解决机制研究

Zehua Zhang, Jiahao Ye, Shuoya Cheng
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引用次数: 2

摘要

近年来,中国机动车保有量快速增长,车路供需矛盾日益突出。城市交通拥堵问题日益突出,拥堵解决机制逐渐形成。目前,中国的交通拥堵控制系统还存在许多不足。城市道路拥堵的现象仍然普遍存在。现有的交通控制系统不能满足复杂的交通网络,不能缓解交通状况的恶化。本文提出了一种多智能体交通控制系统,该系统旨在控制交通网络中多个相邻交叉口交通流的红绿信号比例,从而提高交通流的行驶能力。本文从交通控制网络出发,以单个智能体为单元。通过多智能体技术,可以实现各个交叉口多个智能体之间的信息循环,每个智能体都能快速响应并自动适应交通信息的变化。采用遗传算法建立可持续优化的分布式城市交通控制系统。希望通过本文的研究,能够有效解决城市道路交通拥堵恶化的问题,从而提高车辆通行能力和社会活动效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Traffic Congestion Resolution Mechanism based on Genetic Algorithm and Multi-Agent
In recent years, the number of motor vehicles in China has grown rapidly, and the contradiction between supply and demand of vehicles and roads has become more apparent. The problem of urban traffic congestion has become increasingly prominent, and the mechanism of congestion resolution has emerged. At present, there are still many shortcomings in China's traffic congestion control system. The phenomenon of urban road congestion is still widespread. The existing traffic control system cannot meet the complicated traffic network and cannot alleviate the deterioration of traffic conditions. This paper proposes a multi-agent traffic control system, which aims to control the green-signal and red-signal ratio of traffic flow at multiple adjacent intersections in the traffic network, thereby improving the driving ability of the traffic flow. This paper starts from the traffic control network and uses a single agent as the unit. Through multi-agent technology, the information between multiple agents at each intersection can be circulated, and each agent can quickly respond and automatically adapt to changes in traffic information. A genetic algorithm is used to establish a distributed urban traffic control system that can be continuously optimized. It is hoped that through the research in this paper, the problem of urban road traffic congestion deterioration can be effectively solved, thereby improving the vehicle traffic capacity and the efficiency of social activities.
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