State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, 100044, China.
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, 100044, China.
Accid Anal Prev. 2021 Jul;157:106163. doi: 10.1016/j.aap.2021.106163. Epub 2021 May 11.
This paper designs a systemic framework to quantify speed reduction induced by traffic incidents using a causal inference framework. The results can provide a reference to traffic managers for evaluating incident severities, thus take proper control measures after the incident in order not to underestimate or overestimate the negative impact. A two-phase scheme is proposed, including impacted region determination and speed reduction quantification. We first propose a Frame Region (FR) method, based on the shockwave propagation, to determine the spatiotemporal impacted region (SIR) using speed map. It is worth-noting that we design a statistical experiment to prove the rationality of congestion threshold selection. Secondly, we introduce a causal inference method for identifying the matched freeway segments. The traffic condition of finally matched freeway segments can be served as non-incident traffic condition of the incident occurred location, which contributes to quantifying the incident impact on speed reduction. We further demonstrate the proposed method in a case study by taking advantage of an incident record and related real freeway speed data in China. An interesting observation is that, along with the freeway segments away from the incident location, the congestion duration time of different freeway segments firstly rises and then decreases. The case study also illustrates the impact of incident on speed lasts almost 3 h and the congestion caused by the incident spreads 11 km, while the average causal effect of incident on all the impacted freeway segments is 42.3 km/h.
本文设计了一个系统框架，使用因果推理框架来量化交通事件引起的速度降低。研究结果可以为交通管理人员评估事件严重程度提供参考，以便在事件发生后采取适当的控制措施，从而避免低估或高估负面影响。该研究提出了一个两阶段方案，包括受影响区域的确定和速度降低的量化。首先，我们提出了一种基于冲击波传播的帧区域（Frame Region，FR）方法，使用速度图来确定时空受影响区域（Spatio-Temporal Impacted Region，SIR）。值得注意的是，我们设计了一个统计实验来证明拥堵阈值选择的合理性。其次，我们引入了一种因果推理方法来识别匹配的高速公路路段。最终匹配的高速公路路段的交通状况可以作为事故发生位置的非事故交通状况，有助于量化事故对速度降低的影响。我们进一步通过利用中国的事故记录和相关的真实高速公路速度数据在案例研究中展示了所提出的方法。一个有趣的观察是，随着与事故位置的高速公路路段的远离，不同高速公路路段的拥堵持续时间先增加后减少。案例研究还说明了事故对速度的影响持续近 3 小时，事故造成的拥堵蔓延 11 公里，而事故对所有受影响的高速公路路段的平均因果效应为 42.3 公里/小时。
