Travel time reliability reflects the degree to which the amount of time needed for a trip is predictable. Metrics that quantify travel time reliability are emerging as a fundamental part of assessing the performance of transportation networks. Many states and municipalities are starting to incorporate travel time reliability into their transportation assessments and planning processes. Probe vehicle data is a prevalent data source which can be utilized to compute many of these travel time reliability metrics. This study used probe vehicle data from INRIX to compute, compare, and apply travel time reliability metrics on interstate segments in Iowa. It also looked at the concept of utilizing composite travel time reliability metrics to more concisely but still comprehensively convey travel time reliability.

Different travel time reliability metrics were gathered from past literature and current FHWA rulemaking. These reliability metrics were computed and outcomes from each were compared. From ten different metrics, three groups of similar metrics were identified: the standard deviation of segment travel time index (TTI), the 15th-85th percentile range of TTI, and the buffer time index. These metrics, along with the level of travel time reliability and peak hour travel time reliability metrics from the FHWA, were applied at a segment level to the interstate network in the Des Moines area as well as across Iowa. Choropleth maps and identification of the most unreliable segments in the network emerged as useful ways to assess travel time reliability. It was observed that each metric would identify different segments as being unreliable because the metrics were sensitive to different characteristics of the TTI distribution.

To concisely and comprehensively convey multiple aspects of travel time reliability, a method was developed for creating composite travel time reliability metrics using different combinations of the three key metrics identified earlier. Composite metrics were compared with each other as well as with the original travel time reliability metrics using choropleth maps and route progression plots. A composite metric combining the standard deviation of TTI and the 15th-85th percentile range of TTI emerged as a feasible composite metric to apply to assess travel time reliability at scale.