Identifying the Local Impacts of Speed-Related Factors on Tunnel Entrance Crash Severity

Abstract

According to crash statistics, freeway tunnel entrance zones have higher injury severity rates than other freeway sections. The concentration of traffic injuries is a combination of high speed and low driver alertness. The government of South Korea has deployed the variable speed limit (VSL) as a safety countermeasure to mitigate the consequences of tunnel entrance crashes. This measure has not been quantitatively reviewed, therefore, the effectiveness of implementing VSL at tunnel entrance zones is unknown. The aim of this was to predict the injury severity of crashes occurring at the tunnel entrance zone given the nature of the crash, the size of the tunnel, the roadway geometric characteristics, and environmental factors. It was anticipated that a statistical model calibrated with historical crash data and tunnel features would be able to justify the current locations of VSL implementation and prioritize new VSL implementations. A geographically weighted logistic regression was employed and benchmarked by the conventional logistic regression model, considering the varying geographic locations of freeway tunnel entrances. The geographically weighted logistic regression model presented consistent findings and a slightly better statistical goodness-of-fit than the conventional logistic model. Moreover, the geographically weighted regression captured the local impact of low-level traffic speed on crash injury severities. The findings in this study could help researchers and practitioners evaluate site-specific traffic safety improvement strategies.