Applicability of an agent-based modeling concept to modeling of transportation phenomena

Today's transportation problems are found in the complex interactions of social, financial, economic, political, and engineering issues. The traditional approach to analyzing transportation problems has been the top-down approach, in which a set of overall objectives is defined and specific parts are fitted in the overall scheme. The effectiveness of this analysis process has been challenged when many issues need to be addressed at once and the individual parts [participants to decisions] have greater autonomy. A factor contributing to this phenomenon is the greater opportunity and power for individual parts to communicate and to interact with one another. As a result, it has become increasingly difficult to predict or control the overall performance of a large system, or to diagnose particular phenomena. In the past decade, the concept of agent-based modeling has been developed and applied to problems that exhibit a complex behavioral pattern. This modeling approach considers that each part acts on the basis of its local knowledge and cooperates and/or competes with other parts. Through the aggregation of the individual interactions, the overall image of the system emerges. This approach is called the bottom-up approach. This paper examines the link between today's transportation problems and agent-based modeling, presents the framework of agent based modeling, notes recently used examples applied to transportation, and discusses limitations. The intent of this paper is to explore a new avenue for the direction of modeling and analysis of increasingly complex transportation systems.