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Decision - making of Lane Change Behavior Based on RCS for Automated Vehicles in the Real Environment

机译:真实环境下基于RCS的自动驾驶车道变更行为决策

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This paper proposes the decision-making framework of lane change behavior based on Hierarchical State Machine (HSM) and we build distributed control system architecture based on RCS (Real-Time Control System) to test the model. Environment perception module, decision planning module and execution control module are put into the distributed system architecture based on RCS to improve real-time and ensure that several modules run simultaneously. Besides, the decision-making framework of lane change behavior consists of two parts: miniature scene information model and decision-making model of lane change behavior based on multi-attribute decision-making. The decision-making model of lane change behavior is based on HSM and it sets two top-level state machines: free lane change model and mandatory lane change model. Free lane change model changes the state by using lane reward model to judge and assess driving condition of each lane, while mandatory lane change model uses strategy of multi-source information fusion tojudge whether to lane change. In the end, the unmanned platform BYD Tang using vehicle embedded platform is used to verify the reliability and effectiveness of the lane change decision-making algorithm proposed in this paper in the real road environment.
机译:本文提出了一种基于分层状态机(HSM)的车道变更行为决策框架,并建立了基于RCS(实时控制系统)的分布式控制系统体系结构,对该模型进行了测试。将环境感知模块,决策计划模块和执行控制模块放入基于RCS的分布式系统体系结构中,以提高实时性并确保多个模块同时运行。此外,车道变更行为的决策框架由两部分组成:微型场景信息模型和基于多属性决策的车道变更行为的决策模型。车道变更行为的决策模型基于HSM,它设置了两个顶级状态机:自由车道变更模型和强制车道变更模型。自由车道改变模型通过使用车道奖励模型来判断和评估每个车道的行驶状态来改变状态,而强制车道改变模型则使用多源信息融合策略来判断是否要改变车道。最后,采用车载嵌入式平台的无人驾驶平台比亚迪唐,验证了本文提出的变道决策算法在真实道路环境下的可靠性和有效性。

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