A procedure to determine when safety performance functions should be recalibrated Academic Article uri icon

abstract

  • © 2017 Taylor & Francis Group, LLC and The University of Tennessee. Crash prediction models or safety performance functions can be used for estimating the number of crashes and evaluating roadway safety. Developing a new model can be a difficult task and requires a significant amount of time and energy. To simplify the process, the Highway Safety Manual provides safety performance functions for conducting different types of safety analyses for several facilities. However, because data collected from a few selected states for a specific period of time were considered for fitting and validating these models, they are required to be calibrated to the conditions of the new jurisdiction, and as well need to be revisited for recalibration over time. Therefore, the analyst may need to know when or how often the models are recommended to be recalibrated. This article addresses this question and documents recommendations that are based on the general characteristics of data. The proposed procedure only requires (1) the total number of crashes, (2) the average traffic flow, and (3) the total segment length (or number of intersections) in the network. The method was validated with different empirical datasets collected in Texas and Michigan. The results show that the proposed procedure provides useful information about when recalibration is recommended.

author list (cited authors)

  • Shirazi, M., Geedipally, S. R., & Lord, D.

citation count

  • 8

publication date

  • September 2016