Dynamic control strategy based on passenger choice behavior with real-time information

Real-time control strategies are important methods for high-frequency transit to counteract the effects of bus bunching in passenger waiting time. This paper extends previous literature with the development of an optimization model for multiple lines in a corridor capable of executing a dynamic control strategy based on passenger choice behavior with real-time information. The bi-level model integrates “passenger perceptions,”“service selection,” and “control strategy” effectively. The upper level model is a control model with the objective of minimizing the total waiting time of passengers in the system composed of common lines to decide whether a bus arriving at the hub should be held and its holding time. The lower level model is an allocation model with the utilization of a Nested Logit model to study passenger choice behavior. In addition, a heuristic algorithm is introduced to solve the problem. The effectiveness of the model is evaluated with the data of two lines in Dalian city of China. The results show that the control strategy proposed in this paper outperforms the simple control strategy without passenger choice behavior, where the waiting time of passengers, the number of buses that need to hold, and bus holding time are all reduced.