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Situation-aware decision making for autonomous driving on urban road using online POMDP

机译:使用在线POMDP进行城市道路自动驾驶的情境感知决策

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As autonomous vehicles begin venturing on the urban road, rational decision making is essential for driving safety and efficiency. This paper presents a situation-aware decision making algorithm for autonomous driving on urban road. Specifically, an urban road situation model is proposed first for proper environment representation, thereafter the situation-aware decision making problem is modeled as a Partially Observable Markov Decision Process (POMDP) and solved in an online manner. The proposed algorithm has been extensively evaluated, which is general enough for autonomous driving in various urban road scenarios, including leader following, collision avoidance and traffic negotiation at both T-junction and roundabout.
机译:随着自动驾驶汽车开始在城市道路上行驶,合理的决策对于驾驶安全性和效率至关重要。本文提出了一种在城市道路上自动驾驶的情境感知决策算法。具体来说,首先提出了一种城市道路状况模型,用于适当的环境表示,然后将情景感知决策问题建模为部分可观察的马尔可夫决策过程(POMDP),并以在线方式进行求解。所提出的算法已经得到了广泛的评估,对于在各种城市道路场景中的自动驾驶已经足够通用,包括在T形交叉口和回旋处的领导者跟随,避撞和交通协商。

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