Agent-based modeling and simulation (ABMS) methods have been applied across a spectrum of domains within transportation studies. Different paradigms for ABMS in transportation exist; in general ABMS has strong roots in the individual-based travelers' model in the activity-based travel demand domain. In the distributed system domain, ABMS is commonly seen as a method, known as multiagent systems, for a distributed autonomous system. Recently, transportation-related applications leveraging ABMS have continued to grow. This report attempts to clarify the concept of ABMS and summarize variant paradigms that have been studied in the transportation field. It will do this by distinguishing similarities of differences of the specified problems, model capabilities, strengths and weaknesses of ABMS scoped in different applications, and through a comprehensive review of ABMS approaches that have been seen in transportation studies. The report also seeks to connect the individual-based ABMS with the transportation problems viewed in the social science paradigm. This is achieved by trying to apply ABMS characterized by social science rules to study behavioral decisions of individual travelers. This exploratory study is demonstrated in an example of travelers' route choice decisions, which features a bottom-up, rather than a conventional top-down, approach to formulate the mechanism of an individual traveler's complex route choice behavioral process as a collaborative and reactive result of the traveler's mindset and the network environment integrated in an ABMS.
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