title: Sample-size guidelines for recalibrating crash prediction models: Recommendations for the highway safety manual.
abstract: The Highway Safety Manual (HSM) prediction models are fitted and validated based on crash data collected from a selected number of states in the United States. Therefore, for a jurisdiction to be able to fully benefit from applying these models, it is necessary to calibrate or recalibrate them to local conditions. The first edition of the HSM recommends calibrating the models using a one-size-fits-all sample-size of 30-50 locations with total of at least 100 crashes per year. However, the HSM recommendation is not fully supported by documented studies. The objectives of this paper are consequently: (1) to examine the required sample size based on the characteristics of the data that will be used for the calibration or recalibration process; and, (2) propose revised guidelines. The objectives were accomplished using simulation runs for different scenarios that characterized the sample mean and variance of the data. The simulation results indicate that as the ratio of the standard deviation to the mean (i.e., coefficient of variation) of the crash data increases, a larger sample-size is warranted to fulfill certain levels of accuracy. Taking this observation into account, sample-size guidelines were prepared based on the coefficient of variation of the crash data that are needed for the calibration process. The guidelines were then successfully applied to the two observed datasets. The proposed guidelines can be used for all facility types and both for segment and intersection prediction models.
authors.affiliation: Zachry Department of Civil Engineering, Texas A&M University, College Station TX 77843, United States. Electronic address: alishirazi@tamu.edu.
authors.forename: Mohammadali
authors.initials: M
authors.lastname: Shirazi
authors.affiliation: Zachry Department of Civil Engineering, Texas A&M University, College Station TX 77843, United States. Electronic address: d-lord@tamu.edu.
authors.forename: Dominique
authors.initials: D
authors.lastname: Lord
authors.affiliation: Texas A&M Transportation Institute, College Station, TX 77843-3135, United States. Electronic address: srinivas-g@tti.tamu.edu.
authors.forename: Srinivas Reddy
authors.initials: SR
authors.lastname: Geedipally
mesh_terms: D000063:Accidents, Traffic / Q000517:prevention & control*; D001334:Automobile Driving / Q000706:statistics & numerical data*; D004779:Environment Design; D017408:Guidelines as Topic; D006801:Humans; D015233:Models, Statistical; D018570:Risk Assessment; D013223:Statistics as Topic
keywords: Calibration factor; Crash prediction models; Monte-Carlo simulation; Sample size