The Research On Ride-sharing Strategy Of The Business-to-Consumer Online Car-hailing Platform

Traffic congestion is a major traffic problem in the current city.It has attracted the attention of all sectors of society.To solve this problem,the government has adopted various methods including increasing the traffic load on urban roads,accelerating the construction of public transportation methods,and controlling the number of urban vehicles and road traffic flow.,But the results are limited.With the birth and popularization of the sharing economy and gradually derived into the transportation field,various forms of shared transportation travel modes such as shared bicycles,shared cars,online car-hailing,and ride-hailing have been formed.Among them,carpooling is one of the travel modes of online car-hailing.,Can meet the needs of more passengers without increasing the number of vehicles,which is an effective way to alleviate urban traffic and environmental problems.This article affirms the positive role of carpooling in alleviating traffic congestion,and combines the rise of new energy vehicles and the development of autonomous driving technology to further study carpooling services.Faced with the current increasing requirements for travel quality by passengers,and the low success rate of existing carpooling,uncertain travel time and other factors that limit the further development of carpooling,a carpool strategy based on vehicle scheduling on the online car-hailing platform has been constructed,in which the platform promises to provide passengers on time For travel services,the optimization goal is to minimize platform and passenger travel costs,and to formulate the best passenger matching and vehicle route planning schemes through passenger matching and vehicle allocation.According to the different forms of passenger carpooling,two schemes have been constructed,namely,no-transfer carpooling and transferable carpooling.The difference is that in the non-transfer carpooling scheme,passengers always complete the service by one car,and the passengers are based on the order time and location information.Matching,matching occurs between different passengers;while the interchangeable carpooling scheme matches between passenger travel sections,splitting the set of passenger travel sections,looking for the best way to merge the sections,and planning the vehicle dispatching route on this basis.A solution algorithm is designed according to the characteristics of the model.The non-transfer carpooling model is solved by genetic algorithm.The transferable carpooling model first solves the passenger link merging problem through integer programming algorithm,and then uses genetic algorithm to solve the optimal link allocation.By generating several random calculation examples for analysis,it is proved that the two schemes constructed in this paper can effectively reduce the distance traveled by passengers and the number of vehicles,and by changing the three parameters of order quantity,order time span,and assembly point number,Simulate different traffic situations.According to the results of calculation examples,the effect of carpooling is affected by the number of orders,order time,and spatial density.The more the number and the density,the better the effect of carpooling.The greater the cost reduction effect of the platform to complete travel services through carpooling.The gap in the effect of platform cost reduction between carpooling strategies is also increasing.Compared with the two strategies,considering the cost of platform travel alone,ride-free carpooling is better than interchangeable carpooling.Passenger travel time,as one of the key indicators of passenger travel experience,is a key factor that cannot be ignored in the long-term development of the platform.The time cost of interchangeable carpooling because passengers do not have to bear the time delay caused by detours is lower than that of non-transferring carpooling,but it generates more platform operating costs than non-transferring carpooling.In areas with sparse regional demand,the platform cost between the two is close but the passenger time cost gap is large.At this time,transfer carpooling is better than no transfer carpooling,and in demand-intensive areas,the passenger time cost between the two is close but the platform cost gap Larger,no-ride carpooling is better than interchangeable carpooling at this time.The platform can also choose a more suitable carpool strategy based on the density of regional demand or the sensitivity of passengers to time,as well as the importance of operating costs and passenger experience,so as to achieve a win-win situation for both the platform and the passengers.