Analytical models for comparing operational costs of regular bus and semi-flexible transit services

The provision of public transit services is essential to provide citizens with an improved quality of life. The most popular fixed route bus service (FRBS) is intended to serve a large population along with fixed stops, routes, and schedules. However, in low demand conditions, bus transit operators pay a high cost per passenger to maintain the desired level of service. A demand-responsive transit (DRT) is a commonly discussed transportation solution for serving low passenger demand. Although the conventional DRT system offers a shared-ride door-to-door service to passengers, its implementation is challenging and expensive during peak hours. The present study suggests a form of transit system that combines the rigidity of FRBS and flexibility of DRT to operate in low demand routes. This defined category of transit service is referred to as semi-flexible transit (SFT) system. The proposed SFT service is delivered along the fixed bus route and a limited number of fixed stops based on a flexible schedule to meet passenger requests. The defined SFT system offers reduced operating time and higher vehicle utilization. The study considers an operation of the proposed SFT service for two types of service delivery systems: Contract-Out Taxi Service (COTS), and In-House Paratransit Service (IHPS). A methodology is proposed to develop analytical models describing operational costs of regular FRBS, COTS, and IHPS as a function of demand or annual ridership. Operating cost models are proposed as a decision support tool to enable transit planners to determine the passenger demands along the route at which it is justifiable to “switch” from FRBS to the SFT system to minimize the total cost of operation. Further, the analysis results for FRBS indicate that operating costs are strongly related to vehicle-service hours and for SFT services to average vehicle occupancy rate and deadheading time. Applications of the proposed models and analysis method are demonstrated for a low demand route in the City of Regina