Identifying Secondary Crashes on Freeways by Leveraging the Spatiotemporal Evolution of Shockwaves in the Speed Contour Plot
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 146, Issue 2
Abstract
The congestion caused by primary traffic crashes often exposes subsequent vehicles to the risk of secondary crashes. There has been a proliferation of studies attempting to identify secondary crashes. These studies can be broadly classified into four types: static spatiotemporal threshold–based approaches, queuing model–based approaches, speed contour plot–based approaches, and shockwave-based approaches. However, their respective limitations would lead to the misidentification of secondary crashes. This paper proposes an approach to identifying secondary crashes on freeways by leveraging the spatiotemporal evolution of shockwaves in speed contour plots. In this approach, a spatiotemporal speed matrix is first constructed according to which the speed contour can be plotted. Then, an integer programming model is developed to determine the spatiotemporal region in which a primary crash occurred. The model can ensure that the crash region is consistent with the spatiotemporal evolution of shockwaves. Then, a new way to identify secondary crashes in a speed contour plot is proposed. The model is also extended to handle scenarios in which there are multiple primary crashes in a speed contour plot. Using real data in Beijing, case studies are conducted to validate the proposed approach. The results show that this approach is capable of reducing the misidentification of secondary crashes compared to an approach using static spatiotemporal thresholds and a current identification method based on speed contour plots.
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Data Availability Statement
The models used in this study can be found in the manuscript. The code of the models and some of the data are available from the authors by request.
Acknowledgments
This research was supported by the Natural Science Foundation of China (Grant Nos. 71622006 and 71761137003) and the Center for Data-Centric Management in the Department of Industrial Engineering at Tsinghua University.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 146 • Issue 2 • February 2020
Copyright
©2019 American Society of Civil Engineers.
History
Received: Aug 29, 2018
Accepted: May 31, 2019
Published online: Dec 9, 2019
Published in print: Feb 1, 2020
Discussion open until: May 9, 2020
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