Estimating Path Travel-Time Reliability

Abstract

The estimation of path or trip travel-time reliability is critical to any Advanced Traveler Information System. The state-of-practice procedures for estimating path travel-time reliability assumes that travel times follow a normal distribution and requires a measure of trip travel-time variance. The study analyzes AVI data from San Antonio and demonstrates through goodness-of-fit tests that the assumption of normality is, from a theoretical standpoint, inconsistent with field travel-time observations and that a lognormal distribution is more representative of roadway travel times. However, visual inspection of the data demonstrates that the normality assumption may be sufficient from a practical standpoint given its computational simplicity. The paper then proposes five methods for the estimation of path travel-time variance from its component segment travel-time variances. The analysis demonstrates that computing the trip travel-time coefficient of variation as the conditional expectation over all realizations of roadway segments provides estimates within 13% of field observations for both uncongested and congested conditions.

On the estimation of arterial route travel time distribution with Markov chains

“…The evaluation is done using dataset from a taxis fleet in San Francisco, CA, as a part of The Mobile Millennium Project. To model the correlation and dependency in transport networks, Rakha et al (2006) have tried to estimate the variance of freeway route travel time by modeling correlation between segment travel time variances. Geroliminis and Skabardonis (2006) also estimated the variance of urban route travel time by assuming linear correlations between successive links travel times.…”

A Simplified Network Model for Travel Time Reliability Analysis in a Road Network

“…This assumption was supported by Rakha et al [36], which demonstrated that the normality assumption may be sufficient from a practical standpoint given its computational simplicity. Equation (19) can be calculated as follows:…”

“…Rakha et al [36] presented extensive evidence of a significant correlation between travel times of two adjacent links in the network. Although they analyzed travel time variability over vehicles, this evidence may support travel time variability over days.…”

Design of vehicle cruise control using road inclinations

“…From the aspect of microscopic approach, models of vehicle dynamics are preferred in the paper. Alternative truck lane management strategies are evaluated in [19]. The efficiency of this method is presented by different scenarios, which show that using these methods travel time, energy and the emission of the vehicle can be reduced.…”

“…The efficiency of this method is presented by different scenarios, which show that using these methods travel time, energy and the emission of the vehicle can be reduced. [19,20] present modeling methods for the design of route guidance strategies and the reliable estimation of travel time. The preliminary results of the research are also published in [14,15].…”