Using Travel Time Reliability Measures With Individual Vehicle Data

Abstract

The assessment of travel time reliability for segments and routes is a rapidly advancing frontier. The increasing availability of probe data is making it possible to monitor reliability in real-time based on individual vehicle data as opposed to ex-post-facto based on averages. This paper examines metrics that can be used to monitor reliability based on probe data. The merits of traditional metrics like the planning time index, buffer index, and travel time index are compared with newer ideas like complete cumulative distribution functions and mean/variance combinations. The question is: what is the quality of information about real-time reliability provided by these various options? This paper compares these metrics in the context of probe-based observations of travel times and rates. Also, a new idea for a pairwise metric, the root mean square travel rate rms in conjunction with the standard deviation  . These two measures in combination seem to provide a picture of reliability that is nearly as complete as the underlying Cumulative Density Function (CDF) and better than the simpler metrics. These ideas are examined in the context of probe data from I-5 in Sacramento, CA.