Optimization of electric bus dispatching interval considering stochastic traffic conditions

Due to their efficient and environmentally friendly features, electric buses have become the key to solving urban transportation and environmental problems. However, existing studies primarily concentrate on optimizing schedules under fixed operational scenarios. This paper proposes a scheduling optimization approach to investigate the impact of stochastic traffic conditions on electric bus operations. First, a static dispatching interval optimization model is established, balancing the interests of the service and operation sides by measuring the passenger and company costs. Then, stochastic model formulas are designed considering three stochastic traffic conditions. Finally, a probabilistic evolution model is developed to improve the genetic algorithm. Based on the bus operation data in Harbin, we validate the model's performance in enhancing operational benefits. Results reveal that the impact of stochasticity is nonlinear and more significant on passenger travel quality. Furthermore, retrofitting buses and upgrading routes are beneficial to reducing costs and improving travel experience.