Research On The Pricing Of Online Ride-sharing Considering Supply And Demand Equilibrium

Online ride-sharing is an emerging mode of travel that has emerged in recent years.Relying on the sharing economy and advances in technology,online ride-sharing has also made significant development.Ride-sharing plays a complementary role in urban public transportation.On the one hand,it reduces the number of unloaded vehicles on urban roads,promotes efficient use of road resources,improves transportation capacity,and relieves road congestion.It is obvious to alleviate the problem that it is hard to take a taxi;On the other hand,through ride-sharing,the cost of travel is shared and the cost of personal travel is reduced.However,the pricing of ride-sharing is in the hands of the platform.The opacity of ride-sharing prices and the unreasonable distribution of charges restrict the development of online ridesharing.Therefore,the research on the pricing of online ride-sharing is very important,which is conducive to the wider promotion and longer-term development of ride-sharing.Based on the queuing theory and equilibrium theory,this paper combines the interests of passengers,drivers and platforms,considers the different ways of income distribution between platforms and drivers,and explores the pricing problem of online ride-sharing in the market where a single platform exists.Firstly,this article classified the ride-sharing behavior,clarifies the research object of this article.Secondly,it analyzes the method of apportioning passenger expenses and the calculation method of driver’s income in ride-sharing.Thirdly,the acceptable price of passengers and the expected income of drivers are taken into consideration in the model,a dynamic single-threshold pricing strategy is applied.An online car-sharing pricing model established based on queuing theory and equilibrium theory,according to different drivers income calculation,from the perspective of platform and the government,with the platform optimization and the social welfare optimization as the objective function.Then,according to the characteristics of the ride-sharing pricing model of online ride-sharing,a genetic algorithm process conducive to solving the model was designed and solved according to the calculation examples to verify the effectiveness of the genetic algorithm in solving the model.Moreover,the calculation results of the model were compared and analyzed to explore the situation of order size and objective function value under different pricing methods.Finally,the rationality of the model is verified through the impact analysis of related parameters.The results show that single threshold dynamic pricing is beneficial to improve the utilization rate of the driver,the average order running time,the number of carpooling,passengers can accept the price,the driver can accept a greater influence on the price of the model,aimed at the optimal to social welfare is beneficial to social public transport channel,according to passenger total pay calculation for distribution of income is advantageous to the order quantity increase.