Improving Public School Bus Operations Boston and Baltimore County Public Schools
Studies show that congestion in big cities has a tremendous impact on the time travelers spend on the road. This is translated into a loss of productivity and also impacts students relying on school buses to commute to their schools. In fact, a common problem facing schools is students arriving late for breakfast and/or classes. The objective of this research is to develop a system that allows the Boston Public Schools (BPS) and Baltimore County Public Schools (BCPS) to transport students to and from schools in a safe, reliable, and optimum manner. Due to BPS and BCPS's system of school choice and geography, some students need to travel long distances to attend school. This problem is complex and has many dimensions, and we built a system that uses historical and real-time traffic data to predict the traffic state evolution over a short time horizon. This is then coupled to an advanced routing algorithm to route buses in an optimal fashion to improve the quality of service.
Impacts and Outcomes
This research makes two main contributions. The first one is to consider three levels of schools in three separate time windows in a single framework to optimize the entire routing. Second, the algorithm considers the maximum DOC for all individual students, which enforces all student trips to be within a certain travel circuity. Because lengthy travel for certain students is one of the major complaints about school bus routing, it is believed that including the maximum DOC as a constraint of the algorithm can improve the level of service for some students.
Universities and Sponsoring Organizations Involved
Virginia Tech Transportation Institute
Morgan State University
Boston Public Schools
Baltimore County Public Schools
U.S. Department of Transportation Office of the Secretary-Research
Jianhe Dou (VT), email; firstname.lastname@example.org
William Eger (MSU) Email: email@example.com
Funding Sources and Amounts
USDOT: $140,000 (Federal), Virginia Tech: $35,001 (Match), Morgan State University: $42,373 (Match)
Transit/paratransit/ride-sharing, freight planning, urban mobility, optimum bus routing, cost efficiency, and equity