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PERMIT - A SUMO Simulator for Platooning Maneuvers in Mixed Traffic Scenarios

机译:PERMIT-用于混合交通场景中的机动演习的SUMO模拟器

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Automated driving will have a major impact on traffic. The impact can be particularly relevant under mixed traffic scenarios where automated vehicles will coexist with conventional and connected vehicles. In these scenarios, nonautomated vehicles can obstruct automated driving maneuvers, and the maneuvers can influence the mobility of nonautomated vehicles. Studies are hence necessary to understand the impact on traffic of a gradual introduction of automation. This paper contributes towards this objective by presenting PERMIT, an open-source platooning simulator based on SUMO and its platooning extension Plexe. PERMIT extends the current state of the art by simulating platooning maneuvers in mixed traffic scenarios where automated and non-automated vehicles coexist. PERMIT currently implements (as finite state machines) the join, merge, leave, split and leader leave maneuvers. This paper publicly releases PERMIT to the community.
机译:自动驾驶将对交通产生重大影响。在自动交通车辆将与常规车辆和互联车辆共存的混合交通场景下,影响尤其重要。在这些情况下,非自动车辆会阻碍自动驾驶操作,并且该操作会影响非自动车辆的机动性。因此,有必要进行研究以了解逐步引入自动化对流量的影响。本文通过介绍PERMIT(基于SUMO及其排扩展Plexe的开源排模拟器),为实现这一目标做出了贡献。 PERMIT通过模拟自动和非自动车辆共存的混合交通场景中的排班演习来扩展当前的技术水平。 PERMIT当前(作为有限状态机)实现联接,合并,离开,拆分和领导者离开操作。本文向社区公开发布了PERMIT。

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