Implementing Travel Time Reliability for Evaluation of Congestion Relief Schemes on Expressways

Abstract

Preevaluation of the impacts of congestion relief schemes on travel time reliability is significant for road authorities. However, most existing approaches to estimating travel time reliability rely mainly on empirical data and are therefore not of help for evaluating improvement schemes before implementation. A methodology is presented to estimate travel time reliability on the basis of modeling travel time variations as a function of demand, capacity, weather conditions, and road accidents. For a subject expressway segment, patterns of demand and capacity were generated for each 5-min interval during a year by using the Monte Carlo simulation technique, and accidents were generated randomly according to traffic conditions. A whole year analysis was performed by comparing demand and available capacity for each scenario; shock wave analysis was used to estimate the queue length at each time interval. Travel times were estimated from refined speed–flow relationships. The buffer time index was estimated as a measure of travel time reliability and compared with observed values from empirical data. After validation, the methodology was applied to assess the impact on travel time reliability of opening the hard shoulder to traffic. Opening the hard shoulder to traffic during the peak periods was found to ameliorate travel time reliability significantly and mitigate congestion levels, which could result in up to a 26% cut in the number of accidents occurring.