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Cooperative Driving Based on Negotiation with Persuasion and Concession

机译:基于谈判的说服与让步的协同驾驶

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Recently, along with emergence of autonomous driving vehicles, it is predicted that in the near future, human drivers need to share road and interact with self-driving cars in all the possible traffic scenarios. In this paper, an algorithm based on negotiation with both persuasion and concession is proposed to tackle the challenging task of cooperative driving involving both human and robot drivers. The decision making process is formulated as an optimization based negotiation problem. The persuasion of autonomous vehicle is achieved by making commitment to tipping towards cooperation in the form of convex constraint. The concession is accomplished by gradually tuning weights in the objective function. We propose an approach suitable for most common driving scenarios including ramp merging, lane keeping/changing and intersection crossing. The effectiveness of the proposed algorithm is demonstrated by simulation for several different driving scenarios.
机译:最近,随着自动驾驶汽车的出现,预计在不久的将来,人类驾驶员需要在所有可能的交通场景中共享道路并与自动驾驶汽车互动。在本文中,提出了一种基于说服与让​​步的协商算法,以解决涉及人和机器人驾驶员的协同驾驶的挑战性任务。决策过程被表述为基于优化的谈判问题。无人驾驶汽车的说服力是通过承诺以凸约束的形式向合作小费来实现的。通过逐步调整目标函数中的权重可以实现特许经营。我们提出一种适用于大多数常见驾驶场景的方法,包括坡道合并,车道保持/更改和交叉路口。通过针对几种不同的驾驶场景进行仿真,证明了所提出算法的有效性。

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