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.

翻译：在混合交通情况下,一定数目的行人可以在小地区与车辆互动时共存,在这种情况下,每个行人必须同时对周围行人和车辆作出反应。这种集体行人运动的分析模型可以有利于共享空间设计和城市自主驾驶等智能运输做法。这项工作提出了次级目标社会力量模型(SG-SFM),以描述机动车辆影响下的集体行人运动。拟议的模型引入了车辆对行人运动影响的新设计,该设计与周围行人使用次级目标概念的影响顺利地结合起来。该模型旨在描述通用行人运动,即适用于各种车辆行人互动模式。通过定量和定性评价核实了一般化情况。进行了定量评价,以三个不同的数据集(HBS、CITR和DUT)复制行人运动。还比较了调整模型参数的两种不同方式。定性评价审查了一系列基本车辆行人互动假设中对集体行人运动的模拟。上述评价结果显示了拟议模式的有效性。