Bus Scheduling Optimization Based On Epidemic Normalized Prevention And Control

A major epidemic has had a serious impact on social order and posed a major threat to people’s lives,health and safety.Urban public transport system is closely related to the daily life of urban residents,and its operation under the epidemic situation has new conditions and characteristics.Therefore,the study on bus scheduling optimization under the normal epidemic prevention and control has theoretical and practical significance and practical application value.Firstly,this paper uses the bus IC card swiping data combined with manual investigation to obtain the data of bus passenger flow.After processing the data,the characteristics of bus passenger flow under the epidemic situation are obtained.After the analysis,the change of passenger flow and the delay of service time of bus stops under the implementation of epidemic prevention and control measures are predicted.After that,The minimum travel time cost of passengers,the minimum operating cost of public transport enterprises and the minimum probability of passengers infected with new crowns are taken as the objectives,and the maximum acceptable departure interval of passengers,the prescribed minimum departure interval and the maximum full load constraint of public transport vehicles under the epidemic formulated by the government are taken as constraints.Then take the departure interval as the decision variable.Combined with the travel needs of passengers during the epidemic.The bus operation time is divided into 16 time periods from 6:00 to22:00.Build the bus scheduling optimization model under the epidemic situation.Through the analysis of the current bus operation policies of major cities under the impact of the epidemic,the necessity of Bus scheduling in Luoyang as a tourist city is demonstrated,with the case of Luoyang No.103 bus route.The model is solved and verified by using particle swarm optimization algorithm.And use smooth transition to determine the departure time interval of different time periods.It provides a theoretical basis for the preparation of bus departure schedule when residents’ travel needs are guaranteed under the normal situation of the epidemic.The results show that the service time of bus stops is related to the number of passengers on board,and is related to the "health code" check and payment method of passengers on board under the influence of the epidemic.The time for a passenger to pay in cash is 6.708 s,compared to 4.898 s for IC card payment and 3.855 s for mobile payment,which has the greatest impact on the length of bus stopping time.Particle swarm optimization algorithm is used to solve the optimization function of bus scheduling.The optimal objective function F(min)is 0.3111,and the optimal objective iteration is achieved in the 52 th generation.And the upward departure interval is between 4min and 16.5min,with a total of 122 times.The downlink departure interval was between 3.2min and 20 min,with a total of 132 times,And meet the full load rate of prevention and control requirements,so as to achieve the effect of reducing the cost of bus companies and the probability of passengers infected with epidemic.By analysing the experimental example,the outbreak of bus IC card data is combined with artificial survey is a good way to get passengers travel characteristics,epidemic under the normalization of bus scheduling model is established to solve is good to improve the public transportation scheduling problem.Which minimizes the chances of passengers contracting the coronavirus,thegovernment in the new crown normalized epidemic prevention and control during the build bus provide decisionmaking basis for prevention and control system.