Freeway traffic oscillations: Microscopic analysis of formations and propagations using Wavelet Transform
Freeway traffic oscillations: Microscopic analysis of formations and propagations using Wavelet Transform
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DOI：
10.1016/j.trb.2011.05.012
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发表时间：
2011
影响因子：
6.8
通讯作者：
Zuduo Zheng;Soyoung Ahn;Danjue Chen;Jorge A. Laval
中科院分区：
文献类型：
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作者：
Zuduo Zheng;Soyoung Ahn;Danjue Chen;Jorge A. Laval
在本文中，我们确定的起源停止和去（或缓慢和去）驾驶和测量其传播的微观特征，通过小波变换分析车辆轨迹。基于对53个振荡案例的分析，我们发现振荡可以由换道操纵（LCM）或跟驰行为（CF）引起。LCM主要负责振荡的形成，在相当大的水平或垂直曲线的情况下，而振荡自发地形成附近的路边工作的上坡路段。无论触发，振荡传播的特征是相似的传播速度，振荡持续时间和振幅。所有观察到的情况下，最初表现出一个前驱阶段，在缓慢和去运动的本地化。其中一些最终过渡到一个发展良好的阶段，在该阶段中，振荡在队列中向上游传播。LCM主要负责过渡，尽管有些过渡没有LCM发生。我们的研究结果还表明，振荡对车辆跟随行为具有回归效应：振荡的减速波影响胆小的驾驶员（其特征在于较大的响应时间和/或最小间距），使其变得不那么胆小，而侵略性驾驶员则变得不那么侵略性，尽管这种变化可能是短暂的。纽韦尔的CF模型的扩展框架是能够描述的回归效应与两个额外的参数具有合理的精度，验证使用车辆轨迹数据。
In this paper we identify the origins of stop-and-go (or slow-and-go) driving and measure microscopic features of their propagations by analyzing vehicle trajectories via Wavelet Transform. Based on 53 oscillation cases analyzed, we find that oscillations can be originated by either lane-changing maneuvers (LCMs) or car-following behavior (CF). LCMs were predominantly responsible for oscillation formations in the absence of considerable horizontal or vertical curves, whereas oscillations formed spontaneously near roadside work on an uphill segment. Regardless of the trigger, the features of oscillation propagations were similar in terms of propagation speed, oscillation duration, and amplitude. All observed cases initially exhibited a precursor phase, in which slow-and-go motions were localized. Some of them eventually transitioned into a well-developed phase, in which oscillations propagated upstream in queue. LCMs were primarily responsible for the transition, although some transitions occurred without LCMs. Our findings also suggest that an oscillation has a regressive effect on car-following behavior: a deceleration wave of an oscillation affects a timid driver (characterized by larger response time and/or minimum spacing) to become less timid and an aggressive driver less aggressive, although this change may be short-lived. An extended framework of Newell's CF model is able to describe the regressive effects with two additional parameters with reasonable accuracy, as verified using vehicle trajectory data.