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To improve transportation safety, this study applies Highway Safety Manual(HSM) procedures to roadways while accounting for unobserved heterogeneity andexploring alternative functional forms for Safety Performance Functions (SPFs).Specifically, several functional forms are considered in Poisson andPoisson-gamma modeling frameworks. Using five years (2011-2015) of crash,traffic, and road inventory data for two-way, two-lane roads in Tennessee,fixed- and random-parameter count data models are calibrated. The modelsaccount for important methodological concerns of unobserved heterogeneity andomitted variable bias. With a validation dataset, the calibrated anduncalibrated HSM SPFs and eight new Tennessee-specific SPFs are compared forprediction accuracy. The results show that the statewide calibration factor is2.48, suggesting rural two-lane, two-way road segment crashes are at least 1.48times greater than what HSM SPF predicts. Significant variation in fourdifferent regions in Tennessee is observed with calibration factors rangingbetween 2.02 and 2.77. Among all the SPFs considered, fully specifiedTennessee-specific random parameter Poisson SPF outperformed all competing SPFsin predicting out-of-sample crashes on these road segments. The best-fit randomparameter SPF specification for crash frequency includes the followingvariables: annual average daily traffic, segment length, shoulder width, lanewidth, speed limit, and the presence of passing lanes. Significantheterogeneity is observed in the effects of traffic exposure-related variableson crash frequency. The study shows how heterogeneity-based models can bespecified and used by practitioners for obtaining accurate crash predictions.

Development of Safety Performance Functions: Incorporating Unobserved Heterogeneity and Functional Form Analysis