Identifying Secondary Crashes on Freeways by Leveraging the Spatiotemporal Evolution of Shockwaves in the Speed Contour Plot

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.