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What Makes an Automated Vehicle a Good Driver?: Exploring Lane Change Announcements in Dense Traffic Situations

机译:是什么让自动化的车辆成为一个好司机?:探索Lane更改密集的交通情况

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An automated vehicle needs to learn how human road users experience the intentions of other drivers and understand how they communicate with each other in order to avoid misunderstandings and prevent giving a negative external image during interactions. The aim of the present study is to identify a cooperative lane change indication which other drivers understand unambiguously and prefer when it comes to lane change announcements in a dense traffic situation on the highway. A fixed-base driving simulator study is conducted with N = 66 participants in Germany in a car-following scenario. Participants rated, from the lag driver's perspective, different lane change announcements of another driver which varied in lateral movements (i.e., duration, lateral offset). Main findings indicate that a medium offset and moderate duration of lateral movement is experienced as most cooperative. The results are crucial for the development of lane change strategies for automated vehicles.
机译:自动化车辆需要了解人类道路用户如何体验其他驱动因素的意图,并了解它们如何互相通信,以避免误解并防止在相互作用期间给出负面的外部图像。 本研究的目的是识别合作车道改变指示,其他司机明确地理解,当谈到道路改变公路在高速公路上的浓密交通情况时。 在汽车之后的场景中,在德国的N = 66名参与者进行了固定的基础驾驶模拟器研究。 从延迟驾驶员的角度来看,参与者评分为横向运动中变化的另一个驱动器的不同车道改变通告(即持续时间,横向偏移)。 主要发现表明,横向运动的中等偏移和中等持续时间经历了最合作的。 结果对自动车辆的车道变更策略的开发至关重要。

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