Taxi scheduling based on data mining and sharing network

Considering the development of intelligent networked vehicle technology, in order to solve the problem of real-time scheduling under large-scale urban taxis, this paper considers the method of clustering first and dispatching later to construct a new taxi dispatch mode. Based on the GPS data of taxi in Chengdu, the model constructed in this paper is applied. The results show that the empty distance of the taxi is reduced by 11.4% after optimization. Then based on the comparative experiment, the results show that the optimization effect of the model is better with the expansion of the data scale; In the continuous real-time optimization experiment, the model optimization effect is relatively stable and has good applicability. The research results of this paper can solve the problem of real-time taxi dispatching under large-scale vehicles, and the operation efficiency is high, which can provide ideas and references for the dispatching management and operation of taxis in reality.