Calibrating safety-based design charts for horizontal curves using system reliability analysis and multivariate models

Abstract

The majority of previous studies on reliability-based highway design focussed on assessing the risk associated with only one mode of non-compliance (i.e. insufficient sight distance on horizontal curves using 2 D sight distance calculations). Only a handful number of studies established a link between risk levels and collisions. This paper calibrates safety-based design charts for horizontal curves considering a system reliability analysis (i.e., multi-mode) where the non-compliance could result from limited sight distance and vehicle skidding. The paper first utilised LiDAR data to collect curve attributes and assess the Available Sight Distance in a 3 D environment on 244 horizontal curves in Alberta, Canada. Monte Carlo Simulation was then used to calculate the associated risk levels, and full-Bayes multivariate Poisson lognormal regression was utilised to develop statistically significant safety performance functions that relate risk levels to collisions. Safety-based design charts were calibrated to relate curve attributes to risk levels and collisions. The calibrated charts showed the importance of using multi-mode reliability analysis. An example of using the calibrated charts in estimating the expected safety benefits of geometric improvements was introduced. The developed charts can offer designers a tool to estimate the safety consequences of design alternatives and aid the decision-making process of rehabilitation projects.