基于多智能体系统的单车道交通仿真

Fa Zhang, Jinling Li, Qiaoxia Zhao
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引用次数: 26

摘要

基于agent的交通仿真是研究交通现象的一种有效工具。然而,主要的问题是如何在有限的计算资源下,在宏观和微观两个层面上再现真实的交通流模式。本文提出了一种单车道交通仿真的多智能体框架。我们重点研究了该框架中最重要的人车智能体。提出了人车智能体的三层结构,提出了战术纵向运动的决策树,推导了加减速率的简化公式。采用agent状态并行更新的方式,建立了一维交通仿真模型。为了在宏观层面上对其进行验证,我们再现了具有周期性边界条件的交通流的现实流密度和速度密度关系。为了在微观层面上验证它,模拟了一个10辆车的排。给定四种典型的leader速度曲线,每个follower都可以安全稳定的跟随leader。结果表明,该模型能较好地再现单车道交通流的宏观和微观特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Single-lane traffic simulation with multi-agent system
Agent-based traffic simulation has emerged as an efficient tool to investigate traffic phenomenon. However, the main problem is how to reproduce realistic patterns of traffic flow at both macroscopic and microscopic levels with restricted computational resources. In this paper, we present a multi-agent framework of single-lane traffic simulation. We focus on the driver-vehicle agents, which is the most important ones in the framework. The three-layer architecture of driver-vehicle agents is proposed, the decision tree of tactical longitudinal movement is put forward, and the simplified formulas of acceleration and deceleration rate are derived. With parallel update mode of agent states, a one-dimension traffic simulation model is developed. To validate it at the macroscopic level, we reproduced the realistic flow-density and speed-density relation of traffic flow with periodic boundary condition. To validate it at the microscopic level, a platoon of 10 vehicles was simulated. Given four kinds of typical speed profiles of the leader, each follower can follow its leader safely and stably. The result shows that this model can reproduce realistic macroscopic and microscopic characteristics of single-lane traffic flow.
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