Factors associated with consecutive and non-consecutive crashes on freeways: A two-level logistic modeling approach

Abstract

A consecutive crash consists of a primary crash and one or more secondary crashes that occur subsequently in a short period of time within a certain distance. It often affects a relatively large area of road space and the traffic disruption created can be difficult for traffic managers to control and resolve. This study identifies the factors delineating a primary crash that results in secondary crashes within a minute from a regular crash that does not result in any secondary crashes. Random-effects, random-parameter and two-level binary logistic regression models are applied to data collected on 8779 crashes on the freeway network of the Guizhou Province, China in 2018, of which 299 are consecutive crashes. According to the AIC values, the two-level logistic model outperforms the other two models. Rear-end primary crashes have a significant random effect varying across road segments on the occurrence of consecutive crashes. Various crash types (rear-end, roll-over and side-swipe), tunnel crash and foggy weather are positively associated with the possibility to cause subsequent consecutive crashes, whereas single-vehicle crash, truck involvement and the time periods with poorer natural lighting are less likely to incur consecutive crashes. Recommendations are provided to minimize the possibility of the occurrence of consecutive crashes on a freeway.

Keywords: Consecutive crash; Multi-level model; Road safety; Traffic hazard; Unobserved heterogeneity.