Optimization of Bus Scheduling Model Considering Unstable Passenger Flow

Taking a single bus line, this paper proposed a method to evaluate the volatility levels of passenger flows. Using this method, the time periods and stations with high volatility level were determined. To improve the performance of the bus scheduling model when the passenger flows were unstable and unpredictable, the passenger flows were described as two parts: stable passenger flow and unstable passenger flow. Based on set pair analysis, this paper constructed a bus scheduling model of passenger flow using binary connection number. The results show that the bus scheduling model considering unstable passenger flow proposed in this paper could significantly save passenger waiting time and operation cost compared with normal scheduling models, especially when the fluctuation of passenger flows was more obvious. By changing the coefficient value, the model could adapt to passenger flow at different volatility levels, and provide decision makers with scheduling options to meet different objectives.