Identifying Promising Highway Segments for Safety Improvement through Speed Management

Abstract

Speed variation is closely related to the occurrence of traffic crashes. Thus, speed management strategies that reduce speed variation are expected to reduce crash frequency and not only improve safety but also prevent congestion due to crash occurrence. This study developed a modeling approach to identify promising road segments for safety improvement through speed management strategies and to illustrate how to select segments on the basis of model results. With the application of four statistical techniques (generalized additive model, negative binomial model, linear model, and empirical Bayes method) in three sequential steps to data collected on a 190-km section of expressway in South Korea, the study developed empirical models for selecting promising segments for safety improvement by the speed management strategies. This paper presents the five most-promising segments for implementing such strategies.