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Agent-based modeling and simulation (ABMS) methods have been applied in a spectrum of research domains. This primer focuses on ABMS in the transportation interdisciplinary domain, describes the basic concepts of ABMS and the recent progress of ABMS in transportation areas, and elaborates on the scope and key characteristics of past agent-based transportation models, based on research results that have been reported in the literature. Specifically, the objectives of this primer are to explain the basic concept of ABMS and various ABMS methodologies scoped in the literature, review ABMS applications emerging in transportation studies in the last few decades, describe the general ABMS modeling frameworks and commonly shared procedures exhibited in a variety of transportation applications, outline the strength and limitation of ABMS in various transportation applications, and demonstrate that ABMS exhibits certain comparable modeling outcomes compared to classical approaches through a traveler’s route choice decision-making process example. The target audiences of this primer are researchers and practitioners in the interdisciplinary fields of transportation, who are specialized or interested in social science models, behavioral models, activity-based travel demand models, lane use models, route choice models, human factors, and artificial intelligence with applications in transportation.