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Autonomous vehicle with communicative driving for pedestrian crossing: Trajectory optimization

机译:自动车辆与交际驾驶为行人交叉路:轨迹优化

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Connected and autonomous vehicles (CAV) is a key technology for this century. One of the main challenges is to define a smart interaction behavior of CAV with the other road users. The challenge is mainly raised at conflicting points where path of CAV intersects with the other users. Recent studies show interaction with humans is a big challenge. It not only requires a collision avoidance system but also more communicative behaviors of the CAV. More precisely, pedestrian needs to understand the intention of the incoming CAV whether it will cross first or not according to its speed profile. One way to overcome this issue is to design optimal trajectory control of the CAV that matches with the pedestrian expectation. However, such a design faces the non-linearity of the space sharing constraint. This paper uses sequence modeling based on Petri Net in order to overcome the problem. It also uses Hamiltonian analysis to derive the optimal control. Numerical examples of the communicative behavior of CAV at pedestrian crossing show that the proposed approach provides CAV with a kind of automatic courtesy.
机译:连接和自主车辆(CAV)是本世纪的关键技术。主要挑战之一是用其他道路使用者定义CAV的智能相互作用行为。挑战主要在矛盾的矛盾点,其中Cav的路径与其他用户相交。最近的研究表明与人类的互动是一个很大的挑战。它不仅需要碰撞避免系统,而且需要更多的距离CAV的交际行为。更确切地说,行人需要了解进入的CAV的意图,无论是根据其速度剖面首先还是交叉。克服这个问题的一种方法是设计与行人期望相匹配的CAV的最佳轨迹控制。然而,这种设计面向空间共享约束的非线性。本文使用基于Petri网的序列建模,以克服问题。它还使用Hamiltonian分析来导出最佳控制。行人交叉路Cav的交际行为的数值例子表明,该方法提供了一种自动礼貌的CAV。

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