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首页> 外文期刊>Transportation Research Record >Agent-Based Approach to Travel Demand Modeling: Exploratory Analysis
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Agent-Based Approach to Travel Demand Modeling: Exploratory Analysis

机译：基于Agent的旅行需求建模方法：探索性分析

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An agent-based travel demand model is developed in which travel demand emerges from the interactions of three types of agents in the transportation system: node, arc, and traveler. Simple local rules of agent behaviors are shown to be capable of efficiently solving complicated transportation problems such as trip distribution and traffic assignment. A unique feature of the agent-based model is that it explicitly models the goal, knowledge, searching behavior, and learning ability of related agents. The proposed model distributes trips from origins to destinations in a disaggregate manner and does not require path enumeration or any standard shortest-path algorithm to assign traffic to the links. A sample 10-by-10 grid network is used to facilitate the presentation. The model is also applied to the Chicago, Illinois, sketch transportation network with nearly 1,000 trip generators and sinks, and possible calibration procedures are discussed. Agent-based modeling techniques provide a flexible travel forecasting framework that facilitates the prediction of important macroscopic travel patterns from microscopic agent behaviors and hence encourages studies on individual travel behaviors. Future research directions are identified, as is the relationship between the agent-based and activity-based approaches for travel forecasting.
机译：建立了基于代理的旅行需求模型，其中旅行需求是由运输系统中三种类型的代理（节点，弧和旅行者）的交互作用产生的。代理行为的简单本地规则显示出能够有效解决复杂的运输问题，例如行程分配和交通分配。基于代理的模型的一个独特功能是它显式地对相关代理的目标，知识，搜索行为和学习能力进行建模。所提出的模型以散列的方式分配从起点到目的地的行程，并且不需要路径枚举或任何标准的最短路径算法来将流量分配给链接。示例10 x 10网格网络用于简化演示。该模型还适用于伊利诺伊州芝加哥市的草图运输网络，其中包含近1,000个行程发生器和汇，并讨论了可能的校准程序。基于代理的建模技​​术提供了一种灵活的旅行预测框架，该框架便于根据微观代理行为来预测重要的宏观旅行模式，从而鼓励对个人旅行行为进行研究。确定了未来的研究方向，以及基于代理和基于活动的旅行预测方法之间的关系。

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