Optimization of Bus Routes at Urban Rail Transit Stations Based on Link Growth Probability

Efficient integration of urban rail lines and buses can improve public transportation. However, current methods for connecting them are not effective or fast. This paper analyzes passenger travel data, including taxi tracks and road network information, to identify potential bus connection stations based on demand. The link growth probability model is then applied to determine the bus lines’ most connected directions based on demand. Finally, a constraint-based exhaustive tree view technique is proposed to speed up the convergence of results. The WEI QU NAN Station in Shaanxi Province is used as an example to evaluate the model’s efficacy. The study reveals 153 prospective stations and lays out the feeder bus network for the entire line, along with a route optimization strategy. Keywords include Feeder Bus, Route Optimization, Link Growth Probability, and Graph Theory.