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Maneuver delegation and planning for automated vehicles at multi-lane road intersections

机译:多车道路口的自动驾驶机动授权和计划

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Multi-lane intersections set high demands for maneuver planning modules of automated vehicles due to the complex environment as well as the high traffic and maneuver density. Complex interdependencies arise in case the driver is integrated into the automation concept by shared vehicle control on maneuver level. Therefore, we introduce and evaluate different maneuver delegation strategies for multi-lane intersections and describe and quantify their consequences for the vehicle trajectory in a reference intersection scenario. Also, a novel trajectory back propagation approach is presented that allows the determination of fundamental reference points within the intersection that are needed for a comprehensive maneuver- and behavior planning approach that can also be used for fully automated vehicle concepts.
机译:由于复杂的环境以及高交通量和机动密度,多车道交叉口对自动化车辆的机动计划模块提出了很高的要求。如果驾驶员通过机动级别上的共享车辆控制将驾驶员集成到自动化概念中,则会产生复杂的相互依赖性。因此,我们介绍和评估了多车道交叉口的不同机动授权策略,并描述和量化了它们在参考交叉口场景中对车辆轨迹的影响。此外,提出了一种新颖的轨迹向后传播方法,该方法可以确定交叉点内的基本参考点,而这些参考点是综合机动和行为计划方法所必需的,该方法也可用于全自动车辆概念。

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