Generalization of the Social Force Model for Mixed Traffic Contexts including Personal Mobility Devices

Abstract

The emergence of Personal Mobility Devices (PMDs), more specifically e-scooters, has transformed the way people move in large cities. These devices can be used in contexts where they interact with low, medium and high pedestrian flows; on cycle paths; but also on roads where they directly interact with motor vehicles. In particular, their coexistence with other soft mobility modes has not been sufficiently explored but is critical for safety and other reasons. In this paper, we propose a novel modeling approach for the description of the movements and interactions among PMDs, cyclists, and pedestrians extending the Social Force Model and introducing specific vehicle dynamics. The novel model is calibrated and validated using a trajectory database obtained through experimentation in a semi-controlled environment. The results show that the proposed model is able to accurately describe all road user interactions and significantly reduces the error in the estimation of the lateral movements.