Research On Dispatching And Bus Scheduling Of Mixed Bus System Considering Autonomous Bus

With the rapid development of self-driving technology,autonomous bus has become a hot research topic at home and abroad.The advantages of self-driving buses over traditional buses are: unmanned driving and bus units can be platooned.Unmanned driving can reduce driver costs,thereby reducing the operating costs of bus companies.Bus platooning can adjust the bus capacity,increase departure frequency,and reduce passenger cost.At present,there are relatively few research on the application of selfdriving buses in bus systems.Generally,only a single pure self-driving bus system is considered,and there is a lack of relevant research on the driving plan of the self-driving bus system.Considering it is a long-term process that transiting from traditional bus to self-driving,this paper conducts optimization research on the mixed bus system composed of traditional bus and self-driving bus from the bus dispatching and scheduling of the mixed bus system.The main research contents are as follows:Utilizing the grouping characteristics of self-driving bus unites and considering the passengers’ preference for traditional bus and self-driving bus,this paper constructs a mixed bus system dispatching model.The model aims to minimize the cost of enterprises and passengers,and considers the constraints such as bus departure frequency,departure time,and stop time.The Genetic Algorithm is used to solve the model.The results show that the mixed bus system considering self-driving can reduce the total cost of bus dispatch by about 19.81% compared with traditional bus.The characteristics of the bus platooning can improve the departure frequency and rate of load and reduce the waiting time of passengers in the peak period.Through the sensitivity analysis of the passenger proportion,it can be found that when the proportion of self-driving buses increases,the total cost of dispatching shows a significant downward trend.Secondly,based on the bus dispatching results,this paper builds a driving planning model of a mixed bus system in a single line,aiming to minimize the cost of enterprise,operation and charging.Due to the mileage limits of traditional electric buses and selfdriving buses,the impact of charging on the scheduling plan is considered in the model.Also,the self-driving bus distinguishes the difference between the self-driving guidance and the platooning unit,which is reflected in the different power consumption and operating cost.The model uses a directed network graph to describe related problems and combines the enumeration of the initial solution and the Column Generation Algorithm to solve the model.The results show that the introduction of self-driving guidance and platooning unit can significantly reduce the operation cost of the bus schedule by 21%.At the same time,it can reduce the average charging times of the vehicle in the driving plan,reduce the loss of the bus battery caused by charging,and improve the average service life of the battery.Finally,this paper analyzes the passenger flow data of multiple bus lines in a single depot which includes specific differences in the passenger flow of different lines in the depot at different times.Therefore,based on the single-line scheduling model the multiline scheduling model in the mixed bus system is constructed allowing bus to operate across different bus lines.The model aims to minimize the purchase cost,operation cost and charging cost of public transport enterprises and uses enumeration and column generation algorithms to solve the model.The results show that compared with the operation mode of the single-line scheduling model,the multi-line scheduling model in the mixed bus system can significantly reduce the vehicle configuration of the bus system in the depot and improve the vehicle utilization rate by about 20%.