This paper presents a motivation-based model in order to explore crowd behavior. The case study is about what motivates the decision processes of passengers about choice of location on the station platform for ingressing and egressing trains. The goal of the research is twofold: to establish a cognitive generic crowd behavior modeling method and to respond to a major challenge of public transportation: to reduce dwell time to ensure a high level of service. We first introduce motivation-based modeling for the simulation of the dynamics of numerous cognitive agents and report the collection of passengers’ dynamics that was done through an extensive survey observation. Most significant variables were then extracted from factor analysis to compose and distinguish six main motivation based strategies that are to be used for the simulation of crowd behavior in the train station. Discussion is about the advantages of motivation-based simulation in terms of robustness and adaptability and conclusion about how Artificial Intelligence, Cognitive Psychology and Data Science operate together to model such complex systems.