Abstract
Traffic control and safety hardware such as traffic signs, lighting, signals, pavement markings, guardrails, barriers, and crash cushions form an important and inseparable part of highway infrastructure affecting safety performance. Significant progress has been made in recent decades to develop safety performance functions and crash modification factors for site-specific crash predictions. However, the existing models and methods lack rigorous treatments of safety impacts of time-deteriorating conditions of traffic control and safety hardware. This study introduces a refined method for computing the Safety Index (SI) as a means of crash predictions for a highway segment that incorporates traffic control and safety hardware performance functions into the analysis. The proposed method is applied in a computation experiment using five-year data on nearly two hundred rural and urban highway segments. The root-mean square error (RMSE), Chi-square, Spearman’s rank correlation, and Mann-Whitney U tests are employed for validation.
Highlights
Highway analysis and management have evolved over the years to become an all-encompassing effort with safety of the users included as an over-arching goal
The following formulation considered in Equations 9-11 for the purpose of computing the Crash Severity Factors quantifies the relative increase in crash severity factor ΔCSrsij, by utilizing safety performance functions for predicting fatal, injury, and property damage only (PDO) crashes adjusted to account for traffic control and safety hardware conditions that deteriorate over time as follows: DCSrsij f^CSrsij,0h - f^CSrsij,th f^CSrsij,0h - f^CSrsij,T h where: ΔCSrsij –percentage change in the Crash Severity Factor for all types of crashes, CSrsij,0 –initial value of the CS contributing factor when the hardware is first installed, CSrsij,T –terminal value of the CS contributing factor when the hardware needs to be replaced, CSrsij,t –value of the CS contributing factor at time t
This study has proposed refining of the exiting methods for highway safety analysis and management, as utilizing the time-varying safety hardware performance functions to compute the Safety Index (SI) which correlates the traffic control and safety hardware condition
Summary
Highway analysis and management have evolved over the years to become an all-encompassing effort with safety of the users included as an over-arching goal. Madanu et al [6] developed a methodology incorporating the life-cycle cost analysis for refined estimation of impacts of the traffic control and safety hardware on crash predictions, to address the limitations of the existing traditional methods for safety impacts assessment of highway safety hardware improvements. The available methods have a limitation with regard to estimating the changes in the crash frequency and the severity level after implementing traffic control and safety hardware improvement projects during the course of highway facility service life-cycle. In order to address this limitation, it is necessary to use the performance functions corresponding to different categories of traffic control and safety hardware, which are a function of time for the analysis In this context, research was conducted to develop performance functions for traffic signs, traffic signals, and pavement markings. Step 1: Categorize the highway segment by land area and functional class and crashes by type and severity
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