An intelligent multi-agent approach for road traffic management systems

Khaled Almejalli, K. Dahal, M. A. Hossain
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引用次数: 20

Abstract

Due to the strong interrelations between traffic situations at different locations of a road network the traffic control actions applied for solving a local traffic problem can create another traffic congestion at a different location in the network. This can result the average travel time on the network level, even after the application of the control actions, to be the same or worse. Therefore, coordinative control strategies are required to make sure that all available control actions serve the same objective. In this paper, an intelligent decision support system based on multi-agent approach is proposed to assist the human operator of the road traffic control centre to manage the current traffic state. In the proposed system, the total network is divided in sub-networks, each of which has its own evaluation agent. In the proposed system the agent will be able to react with other (affected) agents through a high level agent called coordinator to find the optimal global traffic control action using an intelligent traffic control. The capability of the proposed multi-agent-based decision support system was tested for a case study of a part of the traffic network in the Riyadh city of Saudi Arabia. The obtained results show the ability of the proposed multi-agent-based system to identify the optimal global control action.
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道路交通管理系统的智能多智能体方法
由于路网不同位置的交通状况之间具有很强的相互关系,为解决一个局部交通问题而采取的交通控制措施可能会在网络的不同位置造成另一个交通拥堵。这可能导致在网络层面上的平均旅行时间,即使在应用控制操作之后,是相同的或更差。因此,需要协调控制策略,以确保所有可用的控制动作都服务于同一目标。本文提出了一个基于多智能体方法的智能决策支持系统,以辅助道路交通控制中心的人工操作员对当前交通状态进行管理。在该系统中,整个网络被划分为子网络,每个子网络都有自己的评估代理。在提出的系统中,代理将能够通过称为协调器的高级代理与其他(受影响的)代理进行反应,以使用智能交通控制找到最优的全局交通控制动作。提出的基于多主体的决策支持系统的能力在沙特阿拉伯利雅得市部分交通网络的案例研究中进行了测试。结果表明,所提出的基于多智能体的系统具有识别全局最优控制动作的能力。
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