论文标题
在不受控制的人行横情景下，用于车辆互动的多国家社会力量框架
A Multi-State Social Force Based Framework for Vehicle-Pedestrian Interaction in Uncontrolled Pedestrian Crossing Scenarios
论文作者
论文摘要
车辆互动（VPI）是自动驾驶系统最具挑战性的任务之一。此类系统的驾驶策略的设计通常始于在模拟中验证VPI。这项工作提出了一个改进的框架，以研究不受控制的人行横情景中VPI的研究。该框架承认行人与车辆之间的相互效果。基于多国家的行人运动模型旨在描述行人交叉行为的微观运动。行人模型考虑了主要的相互作用因素，例如行人决定何时开始越过的决定的差距，行人的所需速度以及车辆对行人的影响，而行人则在越过道路上。车辆驾驶策略的重点是纵向运动控制，在该控制中，对反馈障碍物控制和模型预测控制进行了测试并在框架中进行了比较。仿真结果证实了所提出的框架可以生成各种VPI场景，包括行人屈服于车辆的行人或行人屈服的车辆。可以轻松地扩展该框架以将不同的方法应用于VPI问题。
Vehicle-pedestrian interaction (VPI) is one of the most challenging tasks for automated driving systems. The design of driving strategies for such systems usually starts with verifying VPI in simulation. This work proposed an improved framework for the study of VPI in uncontrolled pedestrian crossing scenarios. The framework admits the mutual effect between the pedestrian and the vehicle. A multi-state social force based pedestrian motion model was designed to describe the microscopic motion of the pedestrian crossing behavior. The pedestrian model considers major interaction factors such as the accepted gap of the pedestrian's decision on when to start crossing, the desired speed of the pedestrian, and the effect of the vehicle on the pedestrian while the pedestrian is crossing the road. Vehicle driving strategies focus on the longitudinal motion control, for which the feedback obstacle avoidance control and the model predictive control were tested and compared in the framework. The simulation results verified that the proposed framework can generate a variety of VPI scenarios, consisting of either the pedestrian yielding to the vehicle or the vehicle yielding to the pedestrian. The framework can be easily extended to apply different approaches to the VPI problems.
