Estimating intersections’ near-crash conflicts with the drone-based image-recording data - Huang, Yen-Lin; Chen, Yen-Hsiang (Traffic Safety Research, 2025)
Recognizing the fact that the information from historical crash data cannot sufficiently reflect the risk level of target intersections under the current driving populations, some traffic safety researchers proposed to use various surrogate measures of safety (SMoS) from either roadside video records or simulation results for estimating near-crash conflicts and performing proactive safety assessment. Along the same line of research but taking advantage of the high-quality drone-based image-recording data (DIRD), this study presents a new effective surrogate variable, named ‘Extra Brake Required to Avoid a Crash’ (EBRAC), which offers a convenient, reliable, and direct tool for traffic professionals to perform the same analyses and risk rankings for resource allocation. The proposed new surrogate variable, featuring its direct relevance to road users’ maneuvers, e.g. braking from high-precision time-varying braking rate information uniquely available from the DIRD, has reflected crash-prone contributors attributed to driving behaviors and intersections’ overall environments. Hence, after proper field calibration, the proposed method based on EBRAC is directly applicable for estimating near-crash conflicts at other intersections in the same region without further adjustment or employing other advanced statistical techniques to integrate the information from multiple safety surrogates. The effectiveness of the proposed method with the new safety surrogate has been evaluated with field data from five intersections and 20 approaches; the results confirm that its performances, evaluated with two popular statistical tests, are either comparable to or better than the two state-of-the-art methods.