Suburban transit agencies can face challenges in improving transit operation efficiency cost-effectiveness due to a wide geographic service area, often resulting in long headways between vehicles and long waiting times which discourage users. An Integrated Dynamic Transit Operation (IDTO) system in Contra Costa County, California, was developed to enable enhanced connectivity, reduce travel time and improve operations for suburban transit agencies. A prototype system, including the IDTO server, a dispatch interface and a traveler mobile app, was developed and field tested with several Tri-Delta Transit (TDT) bus routes and San Francisco Bay Area Rapid Transit (BART) routes connecting at identified points. The IDTO system prototype included the transit connection protection (T-CONNECT) application which aims to improve transfers by extending the wait time of outbound buses to meet connecting riders at transfer stops.
- Improve dynamic transit applications by using a combination of innovative real-time data capture and data management methodologies. Innovative technologies, such as stand-alone mobile applications and in-vehicle driver information terminals, should be introduced to enable improved dynamic transit applications.
- Upgrade the transit management system with driver information terminals. The lack of an onboard driver information terminal presented a constraint for IDTO, as the transit dispatch center experienced increased workload in responding to the dynamic IDTO operational recommendations. Driver information terminals could help as the level of dynamic operation increases.
- Utilize advanced approaches to predict estimated time of arrival (ETA). The effectiveness of transit operations is significantly affected by the accuracy of ETA predictions. IDTO’s ETA values were provided by the automatic vehicle location (AVL) system. During the demonstration, a large portion of invalid T-CONNECT requests were caused by occasional inaccurate ETA predictions. This could be alleviated by utilizing more advanced approaches for ETA predictions.
- Adjust and optimize scheduled departure times and running time. For example, the waiting time for transfer passengers can be significantly reduced by adjusting the scheduled time of the connecting bus routes to meet the main bus route. This will lead to a higher success rate for connection protection and the overall efficiency and effectiveness of transit operation. The study showed that a large number of schedules can be adjusted, resulting in a considerable benefit for all passengers.
- Develop a mechanism for determining amount of dynamic holding time. Dynamic holding time should incorporate both operational conditions and passengers’ dynamic needs. The fixed amount of holding time in the prototype limited the improvement of passengers’ transit experience.
- Take potential changes to trip schedules and route maps into account. If the current transit system has a plan for expansion, the IDTO system should take potential changes to trip schedules and route maps into account to reflect changes in travel patterns.