Application of social force model to pedestrian behavior analysis at signalized crosswalk

• Formulate pedestrians’ decision-making behavior at signalized crosswalk.
• Represent pedestrian evasion behavior and collision avoidance with vehicles.
• Calibrate model parameters by separating into measurable and non-measurable groups.
• Visually reproduce pedestrian crossing behavior in microscopic simulation.

Limited pedestrian behavior models shed light on the case at signalized crosswalk, where pedestrian behavior is characterized by group or individual evasion with surrounding pedestrians, collision avoidance with conflicting vehicles, and response to signal control and crosswalk boundary. This study fills this gap by developing a microscopic simulation model for pedestrian behavior analysis at signalized intersection. The social force theory has been employed and adjusted for this purpose. The parameters, including measurable and non-measurable ones, are either directly estimated based on observed dataset or indirectly derived by maximum likelihood estimation. Last, the model performance was confirmed in light of individual trajectory comparison between estimation and observation, passing position distribution at several cross-sections, collision avoidance behavior with conflicting vehicles, and lane-formation phenomenon. The simulation results also concluded that the model enables to visually represent pedestrian crossing behavior as in the real world.