Investigation of a New Approach for Representing Traffic Volumes in Highway Crash Analysis and Forecasting; Final rept. for 1 Sep 04-31 Aug 06

摘要

Accident prediction modeling studies are good for identifying correlations between crash risk and explanatory factors, but cannot give definite safety effects of countermeasures related to the significant covariates. Causality can only be proven using crash reconstruction methods or carefully constructed before-after studies, both of which require special data observation or analysis time, making them impractical to apply on large study data sets representing the variation of characteristics in the road network. This report proposes two advances in crash modeling: (1) a collision type categorization based on factors contributing to the occurrence of collisions to support estimation of prediction models that can better identify crash causality, and (2) definition of crash exposure to consider the traffic flow situation that is necessary for specific collision types to occur.