面向群体交通协调的多智能体系统体系结构与方法

Jana Görmer, J. Müller
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引用次数: 8

摘要

下一代交通管理系统将利用车辆和交通基础设施的车载智能和通信能力。在本文中,我们研究了一种多智能体方法,允许车辆智能体组成群体,以协调它们的速度和车道选择。我们的假设是,基于合作驾驶方法的分散方法可以促进更高、更顺畅的交通流量,从而实现更高的速度和更少的延误。我们的重点是自动车辆决策模型。我们开发了一种面向群体的驾驶方法,车辆代理感知其环境并交换信息。提出了分散的动态车辆分组算法、冲突检测和全局协调方法,并定义了车辆的个体驾驶策略。为了验证,我们将该方法与商用交通仿真平台AIMSUN中实现的驾驶方法进行了比较。实验结果表明,群体形成和群体协调方法可以提高交通网络的吞吐量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiagent system architecture and method for group-oriented traffic coordination
Next-generation traffic management systems will make use of on-board intelligence and communication capabilities of vehicles and traffic infrastructure. In this paper, we investigate a multiagent approach allowing vehicle agents to form groups in order to co-ordinate their speed and lane choices. Our hypothesis is that a decentralized approach based on a co-operative driving method can contribute to higher and smoother traffic flow, leading to higher speeds and less delays. Our focus is on automated vehicle decision models. We develop a group-oriented driving method with vehicle agents that perceive their environment and exchange information. The paper proposes decentralized dynamic vehicle grouping algorithm, a conflict detection and global coordination method, and defines individual driving strategies for vehicles. For validation, we compare our method with a driving method implemented in the commercial traffic simulation platform AIMSUN. Experimental results indicate that group formation and group coordination methods can improveme traffic network throughput.
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