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A two-level urban traffic control for autonomous vehicles to improve network-wide performance

机译:自动驾驶汽车的两级城市交通控制,以提高全网性能

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In the near future, autonomous vehicles will face with new challenges in several fields. One of the most exciting changes will be represented by the network-wide optimal traffic control. When driverless vehicles take over the road, classical road signalization schemes will become superfluous. Accordingly, the paper’s aim is to propose a control design methodology for autonomous vehicles in urban traffic network by considering the network-wide performance. The proposed two-level control strategy solves a tractable optimization problem for a network wide traffic control. On the one hand, a local intersection controller is designed which ensures safe crossings of vehicles and aims to reduce traffic emission in the junction area. On the other hand, the local controllers also optimize the network performance by minimizing the queues in all road links. The traffic is therefore modeled in a two-level fashion. A microscopic dynamics is considered in junctions and macroscopic model is applied for the whole traffic network. The control strategy is tested and evaluated based on microscopic traffic simulation.
机译:在不久的将来,自动驾驶汽车将在几个领域面临新的挑战。网络范围内的最佳流量控制将代表最激动人心的变化之一。当无人驾驶车辆接管道路时,经典的道路信号方案将变得多余。因此,本文的目的是通过考虑全网性能,为城市交通网络中的自动驾驶汽车提出一种控制设计方法。所提出的两级控制策略解决了针对网络范围的流量控制的易处理的优化问题。一方面,设计了一种局部路口控制器,以确保车辆的安全穿越,并旨在减少路口区域的交通排放。另一方面,本地控制器还通过最小化所有道路链接中的队列来优化网络性能。因此,以两级方式对流量进行建模。在路口考虑微观动力学,并将宏观模型应用于整个交通网络。基于微观交通仿真对控制策略进行测试和评估。

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