Impact analysis of MBTA 2009 Key Bus Route Initiative program

Abstract

The Massachusetts Bay Transit Agency (MBTA) has the stated service objectives of customer service excellence, accessibility, reliability, and state-of-the-art technology. Over the last few years, the MBTA has been concerned about a possible decline in bus service quality. In response, the MBTA launched the Key Bus Route Initiative (KBRI) program in 2009. Funded entirely by the American Recovery and Reinvestment Act, the program is intended to improve bus service reliability on six key bus routes in the Boston area. The program uses an array of new initiatives to achieve this goal. In September 2009, our team of four students in the Master of Engineering Program was asked to provide an independent impact analysis of the KBRI program. In response, we worked to analyze KBRI as well as expand the scope of the study to answer the two-part question of how to best improve bus service performance with limited resources and how to best use existing technology to strategically plan for future performance improvements. To this end, performance metrics were developed, which focus on customer's perception of both bus service efficiency and reliability. These metrics and the methodology provide a short term tool to analyze KBRI, but also a strategic framework for continuous improvement in overall MBTA bus service. This report demonstrates that additional resources deployed on KBRI selected routes had considerable positive impacts on bus service performance. As a result of the KBRI initiatives, MBTA customers riding these routes saved a total wait time of 56 hours per day in the AM and PM peak travel periods. In addition to demonstrating how these results were achieved, this report provides further in-depth analysis of MBTA bus service performance. Several cases are shown where performance was improved without adding additional resources. For that reason, we provide general schedule related findings, which are summarized as recommendations for future efficient schedule adjustments on other MBTA routes. Additionally, our analysis has shown that tremendous potential exists for expanded use of automated data collection systems at the MBTA. By linking several systems, which to this point have not interfaced with one another, we provide to the MBTA a framework for how to use these existing technologies to strategically plan for future performance improvements.