Computing Headway Bounds Under Worst-Case Bunching in Fixed-Line Transit Systems

August 2026·
Michael Yuhas
George Gunter
George Gunter
,
Jose Paolo Talusan
Aron Laszka
Aron Laszka
,
Dan Freudberg
,
Abhishek Dubey
Abstract
Vehicle bunching is a major problem for transit operators. When vehicles bunch together, the lead vehicle will service the majority of passenger demand, leaving the following vehicles to operate below capacity, wasting fuel and money. Furthermore, after the last vehicle in the bunch passes, the time before the next vehicle’s arrival (headway) will be large. Transit operators can combat bunching by holding buses at stops along a route, trading riding time for even headway times. While prior work has focused on developing holding policies to minimize average case bunching, no work has focused on analyzing the longest and shortest possible headway times under a broad group of such policies. We assume that dwell times at stops and travel times between stops are bounded and develop a dynamic program that computes the maximum and minimum headway times for a single bus route with an arbitrary number of control points, vehicles, and holding policies. These bounds are tight in the sense that it is always possible to identify the specific sequence of events that lead to their occurrence. We use these bounds to investigate the effects of different holding policies, stop placement, and number of vehicles on route headways and worstcase bunching. Finally, we apply these analysis techniques to a real-world transit system in Nashville, TN and show their utility for transit planning.
Type
Venue
32nd IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA 2026), 52–62
publications

Authors

George Gunter
Postdoctoral Researcher
George is a postdoctoral researcher studying formal methods (FM) approaches for real-time control of transit systems. He is interested in using FM approaches to study how we can assure properties of transit operation while also balancing the performance of surrounding traffic flows. George previously received his Ph.D. from the Vanderbilt University Civil Engineering department, and his bachelor’s degree from the University of Illinois at Urbana-Champaign Civil Engineering department.
Aron Laszka
Associate Professor

Aron Laszka is an Associate Professor in the College of Information Sciences and Technology at the Pennsylvania State University. Previously, he was an Assistant Professor at the University of Houston, a Research Assistant Professor at Vanderbilt University, and a Postdoctoral Scholar at the University of California, Berkeley.

His research interests revolve around artificial intelligence and cyber-physical systems, focusing on machine learning for decision making and optimization, with applications in smart and connected communities, critical infrastructure, and cybersecurity.

His research is funded by the National Science Foundation, the Department of Energy, the Department of Transportation, and other agencies.