Travel Time Reliability Using the Hasofer–Lind–Rackwitz–Fiessler Algorithm and Kernel Density Estimation

Abstract

Travel time reliability has emerged as an indicator of roadway performance. Estimation of travel time distribution is an important starting input for measuring travel time reliability. This study used kernel density estimation to estimate travel time distribution. The Hasofer–Lind–Rackwitz–Fiessler algorithm, widely used in the field of reliability engineering, was used in this work to compute the reliability index of a system based on its previous performance. The computing procedure for travel time reliability of corridors on a freeway was introduced, then network travel time reliability was developed. Given probability distributions estimated by the kernel density estimation technique and an anticipated travel time from travelers, the two equations of corridor and network travel time reliability can be used to address the question, “How reliable is my perceived travel time?” The definition of travel time reliability was in the sense of on-time performance, and this study was conducted from the perspective of travelers. The major advantages of the proposed method are as follows: ( a) it demonstrates an alternative way to estimate travel time distributions when the choice of probability distribution family is still uncertain and ( b) it shows its flexibility for application to levels of roadways (e.g., individual roadway segment or network). A user-defined anticipated travel time can be input, and travelers can use the computed travel time reliability information to plan their trips so that they can better manage trip time, reduce costs, and avoid frustration.