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Microscopic Traffic Behaviour near Incidents

机译:事故附近的显微流量行为

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摘要

Much of the delays on road networks are caused by incidents. This is partially caused by blockage or closure of lanes, but also by the change of driving behaviour in the remaining lanes. This contribution analyses traffic flow conditions near an incident both microscopically and macroscopically. A theory is proposed to describe drivers' behaviour, which is tested using traffic data of individual vehicles, collected using a helicopter. A bimodal headway distribution is observed, centred around two mean values, 2 seconds and 4 seconds. To understand the underlying mechanisms a car-following model is fitted to the drivers' behaviour. The model parameters show that the reaction time is much higher than usual. Using this model-based analysis, we conclude that the incident distracts the drivers and less attention is paid to the driving process. The consequence is that the queue discharge rate for the unblocked lanes is 30% lower than the usual queue discharge rate per lane.
机译:道路网络的大部分延迟是由事件引起的。这部分是由堵塞或封闭车道的堵塞,而且是通过剩余车道中的驾驶行为的变化来引起。该贡献分析了微观和宏观的事件附近的交通流量条件。提出了一个理论来描述使用直升机收集的各个车辆的交通数据测试的驱动器行为。观察到双峰分布,以两个平均值为中心,2秒和4秒为中心。要了解潜在的机制,汽车之后的模型适用于司机的行为。模型参数表明反应时间远高于平常。使用基于模型的分析,我们得出结论,事件分散了司机的注意力,并且对驾驶过程支付了不太关注。结果是未阻止的车道的队列排放率比平时的队列放电率低30%。

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