Headway management can potentially reduce passenger waiting time and on-board crowding on high-frequency services. In this study, a headway control experiment was conducted and evaluated for Washington Metropolitan Area Transit Agency routes 70 and 79 in Washington, D.C. The field experiment is evaluated by performing a before–after empirical evaluation. The organizational process and challenges involved with the implementation are discussed. Overall, a reduction of 26% in passenger excess waiting time was attained, which implies annual time savings that translate into US$1 million. Even though the field experiment implementation was far from ideal, the benefits obtained so far might pave the road to a long-term commitment to shift into a fully controlled headway-based management.

Transit agencies traditionally have used vehicle movement to assess service quality. However, new technologies such as automatic fare collection systems, automatic passenger counters, and automatic vehicle location devices are giving agencies a wealth of data from which critical insights can be gained about customer experience. Trip-level travel time distributions are used to explore the potential for a new customer-focused measure of service quality. The proposed method builds on recent transit research and ties in to lessons learned over the past 20 years of highway reliability research. An example of delay incidents illustrates the disconnect between the vehicle-focused tools that currently are available to transit agencies for the evaluation of service quality (e.g., minutes of train delay, headway adherence) and what a customer cares about (i.e., travel time to the destination). This disconnect is addressed with the use of actual trip times to outline a new measure: percentage of customers with a travel time of less than x min. Historical travel time distributions create the opportunity to understand better the duration and magnitude of an incident. Possible applications of information about travel time reliability are identified; these include improved understanding of the causes of delay, incident management, and communication of service status to customers.