School of Computer Science, Xianyang Normal University, Xianyang, Shaanxi 712000, China.
Comput Intell Neurosci. 2022 Oct 28;2022:3154532. doi: 10.1155/2022/3154532. eCollection 2022.
The interactive motion planning between unmanned vehicles and pedestrians in urban road environments is the key to realizing the autonomous motion of unmanned vehicles in hybrid traffic scenarios. The problem of human-vehicle interaction motion planning modeling at complex intersections is studied for an unmanned vehicle in this article. First, the motion planning of pedestrians and the unmanned vehicles is established according to the social force model and the behavioral dynamics model. Then, the autonomous vehicle is added to the crowd, and the human-vehicle interaction force is established. The virtual force is added to the social force model and the behavioral dynamics model, respectively, and the improved social force model and the behavioral dynamics model are used for the motion planning of pedestrians and unmanned vehicles. In this way, the established model solves the problems of simple pedestrian interaction motion planning in the social force model and single-body motion planning in the behavioral dynamics and thus provides a strong support for multibody motion planning. Finally, through the interactive motion planning trajectory of pedestrians and unmanned vehicles in different scenes, the vehicle and pedestrian motion planning trajectory can effectively avoid overlapping or crossing, so as to avoid the collision, which verifies the effectiveness and feasibility of the proposed model.
无人车与行人在城市道路环境中的交互运动规划是实现无人车在混合交通场景下自主运动的关键。本文研究了复杂交叉口无人车的人车交互运动规划建模问题。首先，根据社会力模型和行为动力学模型建立行人与无人车的运动规划。然后，将自主车加入到人群中，建立人车交互力。分别在社会力模型和行为动力学模型中添加虚拟力，利用改进后的社会力模型和行为动力学模型进行行人及无人车的运动规划。这样建立的模型解决了社会力模型中行人交互运动规划简单和行为动力学中单体运动规划单一的问题，为多体运动规划提供了有力支持。最后，通过不同场景下行人与无人车的交互运动规划轨迹，验证了车辆和行人运动规划轨迹能够有效避免重叠或交叉，从而避免碰撞，验证了所提模型的有效性和可行性。
