Bus Transit Service Planning and Operations in a Competitive Environment

Transit services are currently facing several challenges in the United States and around the world. For many reasons, among which the fluctuations in gas prices and the state of the economy are the major ones, transit demand has noticed a considerable increase. The challenge that transit agencies are facing is to make these increases permanent by maintaining transit’s competitive edge over the private vehicle with more dense and reliable service. Current methodologies for scheduling new as well as improving existing transit routes should be able to respond to the dynamic nature of urban traffic as it is evolving through ITS and more comprehensive traffic management strategies. In this research paper, we correlate travel time obtained from buses to travel time obtained from floating vehicles in the Twin Cities metropolitan region. This research helps to introduce more reliable estimates of travel time for planning new and competitive transit services. Specifically, this work studied two bus routes over a variety of different roadway types and traffic conditions and produced statistical models that can estimate travel time based on measurements collected from buses and regular vehicle probes. The generated models revealed the characteristics causing bus service to be generally slower. Altering bus route characteristics can reduce overall travel time and minimize the travel time disparity between buses and private vehicles. In particular, the models presented in this paper lend support to Journal of Public Transportation, Vol. 12, No. 3, 2009 40 bus-only shoulder policies, stop consolidation, serving major streets with fewer stop signs, and implementation of smart transit signal priority. Introduction Transit services are facing several challenges around the world, even more in the United States. In recent days transit demand has noticed an increase, which some researcher relate to the increase in gas prices. For such surge in demand to become permanent, transit agencies need to manage their systems strategically and offer a service that can be competitive to private vehicles. A service competitive to private vehicles is possible when a reliable service to passengers is present. A reliable service to a passenger is the service that can be easily accessed at origin and destination, arrives on time, has a short travel time/run time (similar or better than private vehicle travel time), and has low variance in travel time and a short waiting time (Furth and Muller 2006, 2007; Koenig 1980; Murray and Wu 2003; Turnquist 1978; Welding 1957). Achieving such service requires expanding the existing transit operations with routes that follow realistic schedules to which a bus can adhere, in addition to improving the existing service in several aspects. Schedulers rely primarily on using software that is designed based on operations research methods to introduce schedules for new bus services. Such software takes into account the expected operating environment. Unfortunately, a generic solution in transit planning based on optimization is not the best way to go and always requires some kind of fine-tuning. Some transit agencies use floating vehicles driving along corridors where new routes are planned. The vehicles are used to estimate travel time and compare it to schedules generated from optimization software prior to implementation of new service. Doing so without having an accurate understanding of the differences between floating cars and real bus service makes the outputs questionable. Currently, several agencies are looking toward increased implementation of faster services such as limited, express, and Bus Rapid Transit (BRT) services. By implementing these services, transit agencies try to compete with private vehicles to attract more choice riders (Krizek and El-Geneidy 2007). Implementing any of these services requires a full understanding of the operating environment. In this research paper, we correlate travel time obtained from buses to travel time obtained from floating vehicles in the Twin Cities metropolitan region. This research helps to introduce more reliable estimates of travel time for planning new and competitive transit services. Previous research concentrating on relating travel time between buses and floating vehicles along