A Combined Travel Planning Model of Shared Car and Public Transportation Based on Improved Ant Colony Algorithm

In the transportation system, each travel mode is independent, so travel planning for each person is not integrated. To solve this problem, MaaS provides a new idea. This paper focuses on the new transportation mode of car sharing. The combination of multiple travel planning modes under MaaS is also carried out. Based on the Amap data, a combined travel planning model of shared cars and public transportation was established, and the improved ant colony algorithm was selected to solve the problem. Finally, in a case study in Xi’an, the travel planning model combined with Amap JS API service is applied, and a travel plan was generated as the outputs of the model. Compared with the travel plan output from other platforms, the model performs well in the two core indexes of travel time and travel cost. The results show that the model is practicable and feasible.