Optimization Model of Battery Electric Bus Scheduling Combined with the Whole Bus and Shuttle Bus during Heavy Congestion

The existing battery electric bus scheduling usually ignored the impact of real-time road network state, and the bus arrival time in congestion is far from the planned schedule. Therefore, this paper comprehensively considers the real-time road network state and bus passenger flow demand and establishes an optimization model of battery electric bus scheduling combined with the whole bus and shuttle bus. Aiming at improving the bus service level, the improved particle swarm optimization (PSO) algorithm is used to obtain the optimized departure interval when the road network is seriously congested. The model is verified based on the operation data of bus line 361 in Beijing city, China. The results show that the model can significantly reduce the waiting time and travel time of passengers, and the average waiting time of passengers is reduced by 182.2 s, which greatly improves the bus service level.