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Research on the Behavioral Dynamics Motion Planning Method of the Human-Vehicle Social Force Model

机译:人车社会力模型的行为动力学运动规划方法研究

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摘要

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.
机译:城市道路环境下无人车与行人的交互运动规划是实现混合交通场景下无人车自主运动的关键。本文研究了复杂交叉口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和无人车的运动规划;然后,将自动驾驶汽车加入人群中,建立人车交互力。将虚拟力分别添加到社会力模型和行为动力学模型中,将改进的社会力模型和行为力模型用于行人和无人车的运动规划。通过这种方式,所建立的模型解决了社会力模型中简单的行人交互运动规划和行为动力学中单体运动规划的问题,从而为多体运动规划提供了有力的支持。最后,通过行人和无人车在不同场景下的交互式运动规划轨迹,使车辆与行人的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。

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