Tool with Road-Level Crash Prediction for Transportation Safety Planning

Abstract

The growing use of packages based on geographic information systems (GISs) in transportation planning is assisting in the development and implementation of methods that facilitate consideration of safety. This paper presents a method of predicting safety for planning alternatives. Although applicable to large road networks, the method predicts crashes at the road facility level (intersections and segments). Thus it is suitable for joint evaluation of modifications of the road network, changes in network traffic flows, and improvements in road geometry considered by planners. A complete set of crash prediction models was developed by the authors for seven types of road segments and four types of road nodes on the basis of crashes reported on Indiana highways from 2003 to 2005. A mainstream research method has been used: negative binomial regression with a stepwise method for variable selection and the Akaike information criterion. The obtained equations are transparent to transportation planners and allow efficient computations for large road networks. The crash prediction equations have been implemented in the GIS-based planning package TransCAD as an add-on tool. The calibration procedure included in the tool allows a planner to search for optimal values of calibration factors if calibration of crash prediction models is needed.

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