Modelling pedestrian behavior is crucial in the development and testing of autonomous vehicles. In this work, we present a hierarchical pedestrian behavior model that generates high-level decisions through the use of behavior trees, in order to produce maneuvers executed by a low-level motion planner using an adapted Social Force model. A full implementation of our work is integrated into GeoScenario Server, a scenario definition and execution engine, extending its vehicle simulation capabilities with pedestrian simulation. The extended environment allows simulating test scenarios involving both vehicles and pedestrians to assist in the scenario-based testing process of autonomous vehicles. The presented hierarchical model is evaluated on two real-world data sets collected at separate locations with different road structures. Our model is shown to replicate the real-world pedestrians' trajectories with a high degree of fidelity and a decision-making accuracy of 98% or better, given only high-level routing information for each pedestrian.
翻译:模拟行人行为在自主车辆的开发和测试中至关重要。 在这项工作中,我们展示了一个等级行人行为模型,该模型通过使用行为树来产生高层决定,目的是利用经调整的社会力量模型产生由低级别运动规划者执行的动作。我们的工作被充分纳入GeoScenario服务器,这是一个情景定义和执行引擎,通过行人模拟扩大其车辆模拟能力。扩展的环境允许模拟车辆和行人之间的测试情景,以协助基于情景的自主车辆测试过程。展示的等级模型是在不同道路结构的不同地点收集的两个真实世界数据集上进行评估的。我们的模型展示了真实世界行人轨迹的复制率,高度忠诚,决策精确度达到98%或更高,只给每个行人提供高层次的路线信息。