The Crash Prediction Module (CPM)—which is an implementation of the crash prediction methods documented in part C of the American Association of State Highway and Transportation Officials’ (AASHTO) First Edition Highway Safety Manual (HSM)—includes capabilities to evaluate rural two-lane highways, rural multilane highways, urban/suburban arterials, freeway segments, and freeway ramps/interchanges (including ramps, collector-distributor (C-D) roads, and ramp terminals). Crash prediction methods for 6+ lanes and 1-way urban/suburban arterials were added to IHSDM in 2016, based on materials developed under National Cooperative Highway Research Program (NCHRP) Project 17-58, for inclusion in the future Second Edition HSM.
The CPM estimates the frequency of crashes expected on a roadway based on its geometric design and traffic characteristics. The crash prediction algorithms consider the effect of a number of roadway segment and intersection variables.
The algorithms for estimating crash frequency combine statistical Safety Performance Functions (SPFs)—i.e., base models—and crash modification factors (CMFs). SPFs are available for roadway segments, many types of intersections, freeway ramps, C-D roads, and ramp terminals.
The CMFs adjust the SPF (base model) estimates for individual geometric design element dimensions and for traffic control features. The factors are the consensus on the best available estimates of quantitative safety effects of each design and traffic control feature. The algorithms can be calibrated by State or local agencies to reflect roadway, topographic, environmental, and crash-reporting conditions. IHSDM includes a CPM Calibration Utility to assist agencies in implementing the calibration procedures described in the appendix to part C of the HSM. The algorithm also provides an Empirical Bayes procedure for weighted averaging of the algorithm estimate with project-specific crash history data.
The CPM can provide input for scoping improvement projects on existing roadways, comparing the relative safety performance of design alternatives, and assessing the safety cost-effectiveness of design decisions.