Identifying promising segments for safety improvement through Speed management

Abstract

Speed variation is closely related to traffic crash occurrence. Thus, speed management strategies reducing speed variation is expected to reduce crash frequency, not only improving safety but also preventing congestion due to crash occurrence. This study was to develop a modeling approach of identifying promising road segments for safety improvement through such speed management strategies and to illustrate how to select segments based on the model results. By applying four statistical techniques (generalized additive model, negative binomial model, linear model, and empirical Bayes method) in three sequential steps to data collected on 190-kilometer expressway section in Korea, the study was able to develop empirical models for selecting promising segments for safety improvement by the speed management strategies and present top 5 promising segments for implementing such strategies.