| description abstract | This work aims to investigate a multimodal feeder plan for a metro terminal station in the suburbs, where fixed-route transit, flex-route feeder transit (FRFT), shared bike, online car-hailing, and private cars are included. A slack arrival strategy, which relaxes the schedule constraints of a checkpoint but does not affect the bus operating cycle, is proposed to deal with the real-time demand insertion (RDI) problem in FRFT. A dynamic optimization model that is based on slack arrival strategy, which considers penalty time costs, is established to solve rejection decisions and route modification problems in RDI. Then, a method for a multimodal feeder plan is proposed, where FRFT is set for the growing number of commuters and factories, and fixed-route transit is set for mature communities with large passenger demand. A bilevel programming model is built, in which the upper-level multimodal feeder plan model is constructed by comprehensively considering the total travel cost of passengers and the bus profit (ticket income minus operational cost). The lower level is a multimode traffic assignment model. A genetic algorithm (GA) is adopted in the concrete optimization solution. The proposed method is validated through a sample application to Tianjin City, China. Compared with the method without public transit (PT) routes, the method with fixed routes, and the method with conventional flex-route transit in growing communities and factories, the total travel cost is reduced by 9.14%, 5.65%, and 3.86%, respectively. The bus profit increased by 34.67%, 56.89%, and 38.68%, respectively. In addition, the effectiveness of policies for FRFT is verified by evaluating the performance of a multimodal feeder plan under various advanced reservation rates. The feeder problem in a metro terminal station in the suburbs could be solved, and the development of the increasing number of commuters and factories could be ensured with the proposed method. | |
