Adaptation and calibration of a social force based model to study interactions between electric scooters and pedestrians

Abstract

The Personal Mobility Vehicles (PMV) and in particular the electric scooters enjoy increasing popularity and their use has become widespread in the urban environment. The use of existing infrastructure, such as the sidewalks, by escooter drivers, poses a new challenge to policy makers trying to regulate the use of this new mode of transport so that it will be smoothly integrated in the urban networks. So far, there is limited research on the movement of electric scooters and their interaction with pedestrians, depriving the authorities of tools to draw and enforce effective policies. In this paper, we explore the applicability of the social force model for pedestrian dynamics to simulate the movement of e-scooters and the interaction between e-scooters and pedestrians. To conduct this study, we extract electric scooter and pedestrian trajectories through image analysis of videos containing pedestrian and e-scooter movement. Based on the extracted trajectories, scenarios and the respective initial conditions are generated. The social force model is used for the scenarios, and simulated trajectories of escooter and pedestrian movement are produced. The simulated trajectories are compared to the experimental trajectories with the Root Mean Squared Error (RMSE). Finally, the parameters of the social force model and the free speed of the vehicle are estimated with the Cross Entropy Method (CEM).