  In mixed traffic scenarios, a certain number of pedestrians might coexist in
a small area while interacting with vehicles. In this situation, every
pedestrian must simultaneously react to the surrounding pedestrians and
vehicles. Analytical modeling of such collective pedestrian motion can benefit
intelligent transportation practices like shared space design and urban
autonomous driving. This work proposed the sub-goal social force model (SG-SFM)
to describe the collective pedestrian motion under vehicle influence. The
proposed model introduced a new design of vehicle influence on pedestrian
motion, which was smoothly combined with the influence of surrounding
pedestrians using the sub-goal concept. This model aims to describe generalized
pedestrian motion, i.e., it is applicable to various vehicle-pedestrian
interaction patterns. The generalization was verified by both quantitative and
qualitative evaluation. The quantitative evaluation was conducted to reproduce
pedestrian motion in three different datasets, HBS, CITR, and DUT. It also
compared two different ways of calibrating the model parameters. The
qualitative evaluation examined the simulation of collective pedestrian motion
in a series of fundamental vehicle-pedestrian interaction scenarios. The above
evaluation results demonstrated the effectiveness of the proposed model.
