Under the background of COVID-19 epidemic, the traditional ridesplitting scheduling mode is facing the potential risk of cross infection, which brings insecurity to travellers. In order to solve this contradiction, this paper firstly analyzed the matching constraints among travellers under the background of the epidemic, proposed a ridesplitting strategy to separate low-risk and potential risk passengers. Considering the social benefits and service quality of the platform under the COVID-19, this paper developed a dual objective ridesplitting emergency management optimization scheduling model which minimized the waiting time on the basis of rated profit, and proposed a combined simulated annealing algorithm for this model. The effectiveness of the model and algorithm was verified by a specific example. The results show that the model can converge to a stable value, and the calculation results can truly reflect the actual scene, which shows the effectiveness of the model and algorithm. Finally, through a simulation experiment, this paper analyzed the role of the model in virus transmission. The results show that the model can effectively inhibit the virus transmission speed caused by ridesplitting.

[2022-06-20] Accepted Paper /doc/2022.04.0172/v1

[2022-11-05] Printed Article /doc/2022.04.0172/v2