An Agent-Based Approach to Travel Demand Modeling: An Exploratory Analysis |
Zhang, Lei and David Levinson. (2004) An Agent-Based Approach to Travel Demand Modeling: An Exploratory Analysis Transportation Research Record: Journal of the Transportation Research Board #1898 pp. 28-38
|
Abstract: The paper develops an agent-based travel
demand model. In this model, travel demands emerge 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 sketch transportation network
with nearly 1000 trip generators and sinks, followed by a discussion of
possible calibration procedures. The 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 the studies on individual travel behaviors. Future
research directions are identified, as are the relationship between the
agent-based and activity-based approaches for travel forecasting. Keywords: Travel forecasting, Agent-based model, Travel behavior, Trip distribution, Traffic assignment, Shortest path algorithm, Activity-based model |
|