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首页> 外文期刊>Transportation Research Part B: Methodological >A behavioral car-following model that captures traffic oscillations
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A behavioral car-following model that captures traffic oscillations

机译：捕获交通波动的行为跟车模型

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摘要

This paper presents a behavioral car-following model based on empirical trajectory data that is able to reproduce the spontaneous formation and ensuing propagation of stop-and-go waves in congested traffic. By analyzing individual drivers' car-following behavior throughout oscillation cycles it is found that this behavior is consistent across drivers and can be captured by a simple model. The statistical analysis of the model's parameters reveals that there is a strong correlation between driver behavior before and during the oscillation, and that this correlation should not be ignored if one is interested in microscopic output. If macroscopic outputs are of interest, simulation results indicate that an existing model with fewer parameters can be used instead. This is shown for traffic oscillations caused by rubbernecking as observed in the US 101 NGSIM dataset. The same experiment is used to establish the relationship between rubbernecking behavior and the period of oscillations.
机译：本文提出了一种基于经验轨迹数据的行为跟随模型，该模型能够重现自发形成并在拥挤的交通中确保走走停停波的传播。通过分析整个驾驶员在整个振荡周期中的跟车行为，发现该行为在各个驾驶员之间是一致的，并且可以通过简单的模型来捕获。对模型参数的统计分析表明，振动前后驾驶员行为之间存在很强的相关性，如果对微观输出感兴趣，则不应忽略这种相关性。如果对宏观输出感兴趣，仿真结果表明可以使用参数较少的现有模型代替。如US 101 NGSIM数据集中观察到的那样，这是由橡胶瓶颈引起的流量振荡所显示的。使用相同的实验来建立胶颈行为与振荡周期之间的关系。

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