Optimizing feeder bus timetables to boost advanced passenger transfers: a case study of Beijing

In multimodal transportation systems, passengers typically prefer paths with a high portion of metro travel and lean towards transferring to feeder buses at downstream transfer stations. This results in severe passenger congestion at downstream transfer stations, putting increased pressure on feeder buses. This paper introduces a novel perspective to tackle this issue: optimizing feeder bus timetables to boost advanced passenger transfers. These advanced passenger transfers help distribute congestion and pressure to upstream transfer stations, thereby improving system performance. To achieve this, we incorporate the heterogeneity of metro-bus transfer patterns into feeder bus timetable optimization and introduce a coordination degree for each pattern. These coordination degrees are quantified based on network topology and associated passenger demand. With these coordination degrees, a mixed-integer linear programming model is built to minimize the total weighted passenger transfer waiting time. Subsequently, a logit model is developed to formulate passenger transfer choices and evaluate the performance of the obtained timetables in terms of advanced passenger transfers. According to experimental results from a real-world case in Beijing, our methods prove effective in significantly promoting advanced passenger transfer by 35.94%. Compared to methods ignoring coordination degrees, our methods enhance the cumulative number of advanced passenger transfers by 33.48%.