Bus Scheduling Model Based on Peak Hour Volume Clustering

Abstract

Temporal variations of bus passenger flow are essential for transit scheduling in routine management and operations. Smart card, with its detailed and accurate information, is used a lot in research on passenger flow. Aiming at laying the foundation for passenger flow theory as well as providing bus scheduling suggestions, a mathematical model based on passenger peak hour volume clustering is established. To ensure the rationality of this model, stability of passenger flow in each hour during a typical day is validated using time series analyses. Then, a multi-objective program is proposed considering both operational efficiencies and levels of service. Besides, clustering analysis is conducted in the grouping of passenger peak hours. To illustrate the practicability of this model, a case study in Shanghai is conducted. The schedule strategy proposed by this model includes the group number and the optimal value for each group, which helps to improve the reliability and efficiency of bus dispatching and staff scheduling, as well as to improve bus services for passengers.