A dynamic optimization model for bus schedule design to mitigate the passenger waiting time by dispatching the bus platoon

We present a platoon-based bus dispatching strategy and passenger boarding strategy which utilizes a platoon of vehicles to improve capacity flexibility in response to dynamically changing demands, and controls passenger boarding flows to minimize the networkwise passengers' perceived delay time. The released buses in the same platoon are allowed to separate when approaching the stop station, which makes our strategy more flexible and data-driven. A Mixed Integer Linear Programming (MILP) model is firstly developed to formulate the problem with the linear cost, in which both the passengers' actual delay time and the operating bus vacancy are minimized subject to the volume dynamic constraints on both buses and stops. With the computational complexity as a concern, the Genetic Algorithm (GA) is adopted to solve the problem in real time. Comparison between MILP and GA on the computational time and result quality is conducted to show the efficiency of our method. Also, the optimization model with the nonlinear cost considering the passengers' perceived delay time and the operating bus vacancy is directly solved by the GA. Finally, the performance of our method and the traditional bus schedule strategies under two different objectives is discussed in the case study, which indicates the potential of the platoon dispatching in mitigating the passenger's perceived delay.