This paper aims to evaluate travel time variability as well as reliability indexes using global positioning systems (GPS)-based trajectory data of bus trips collected along a selected bus route of the city of Chennai in the southern part of India. Travel time reliability indexes, such as planning time index (PTI), buffer time index (BTI), and buffer time (BT), along with other statistical measures over different time periods are estimated. Generalized extreme value (GEV) distribution is found to be the best-fitted distribution for explaining bus travel time variability reasonably well, using the Kolmogorov-Smirnov (KS) test. Buffer time and 95th percentile travel time are the reliability measures with the most potential, the variation of which reasonably matches the variation in k-value (shape parameter of GEV distribution) over time. The findings from the statistical distribution analysis indicate that travel times during peak hours can be better described using normal distributions. The generic model is developed for predicting volumes based on bus journey speeds. Further, the developed model is validated with the help of travel time data of the same route during a different time period. The study also attempts to demonstrate a methodology for establishing level-of-service (LoS) criteria using reliability indicators. The classification of reliability indicators, considering segment-level travel time data, coefficient of variation (COV) of travel time, and volume-to-capacity ratio (V/C), is finally presented using the cluster technique. Finally, the study concludes that the most effective performance indicators for examining travel time variability on a given bus route are 95th percentile travel time and BT. (C) 2018 American Society of Civil Engineers.
