Optimizing On-Demand Bus Services for Remote Areas

Abstract

This study proposes on-demand bus services for remote areas with low transit demand, incorporating travelers’ willingness to pay and values of time. To jointly optimize the on-demand service of overlapping bus routes, we construct a bi-level model. The upper-level model (UM) optimizes bus departure frequency in different time windows and ticket prices of on-demand services to minimize the total generalized cost, subject to travelers’ willingness to pay for on-demand services. The lower-level model (LM) calculates the probability of travelers choosing on-demand stops. A numerical analysis based on Meishan Island data in Ningbo indicates that with on-demand bus services, the total generalized cost incurred by buses and travelers can be reduced by 30.36% and 15.35% during rush and off-rush hours, respectively. Additionally, the waiting time at an on-demand bus stop is only 4.3 min during rush hours and 6.8 min during off-rush hours.