01697668

Component

Timetable and vehicle schedule are important for transit operation. Electric buses are environmentally friendly compared with conventional buses, developing rapidly and may replace conventional buses in cities. This paper focuses on the timetabling and vehicle scheduling problem for electric buses. A multi-objective optimization model is proposed for a single electric bus line. The model comprehensively considers passenger demand, bus operators’ costs and social benefits. The objectives are to minimize the standard deviation of departure intervals each period, the number of vehicles and the charging costs. As for constraints, the model takes the range of departure intervals, vehicle operation mileage, electricity price of different period, charging time and charging conditions into consideration. This model can be solved by the multi-objective particle swarm optimization (MOPSO) algorithm. Then the paper proposes a strategy to select an actual optimal solution from the Pareto optimal solutions set. In the case, compared to existing schedule and segregated schedule, the integrated model can reduce the number of vehicles and charging costs, as well as relatively increase the smoothness of departure intervals. Moreover, the vehicle charging periods distribute during electricity off-peak hours, which can improve the utilization efficiency of the electricity.

This paper was sponsored by TRB committee AP050 Standing Committee on Bus Transit Systems.

19-04027

English

5p

2019

Transportation Research Board 98th Annual Meeting

Digital/other

Figures; References; Tables

Bus drivers; Bus transit operations; Costs; Departure time; Electric buses; Electric vehicle charging; Optimization; Scheduling; Social benefits; Timetables

Particle swarm optimization

Energy; Highways; Operations and Traffic Management; Planning and Forecasting; Public Transportation

Transportation Research Board Annual Meeting 2019 Paper #19-04027

TRIS, TRB, ATRI

Dec 7 2018 9:34AM