Optimization of Bus Departure Headway Based on Fuzzy Clustering of Operation Period Considering Congestion and Passenger Flow

Determining the bus departure headway is an important part of bus operation. In order to meet different demands of passenger flow in different time periods, the bus departure headway is required to be differentiated; and to cope with the impact of road congestion on the punctuality of the bus and the passenger ride experience, the bus departure headway is also required to have flexibility. The existing methods for determining the bus departure headway are mostly limited to the satisfaction of passenger flow demand, and the influence of road congestion is often ignored. Both types of factors have strong time-course characteristics, but their time-based divisions are often ambiguous, and there is a certain period of time between the two factors. To this end, a bus operation time division method considering the two types of factors is proposed. By extracting the statistical characteristics of passenger flow and road congestion during the whole bus operation period, the comprehensive similarity coefficient is designed, and the fuzzy clustering is performed for the whole operation period. By recognizing the characteristic boundaries of the fuzzy categories, the whole operation period is divided into different fuzzy time categories, and different bus departure headways are set in different time categories to improve the adaptability of the time and the service quality of the public transportation. Finally, the method is analyzed and verified by a simulation of the operation data of a line in Leshan, Sichuan, which proves great effects on the service level of the bus system.