Electric taxis have been adopted as a new energy public transportation tool as opposed to traditional taxis in modern city. Designing an efficient swapping station deployment scheme has become an important issue to improve the endurance capability of electric taxis. In this study, based on real operation trajectory data from 3997 taxis in Suzhou city, the battery swapping demand of taxis based on urban traffic flow is obtained to construct a network coverage deployment model under rule constraints, where the main optimization goal is to minimize the number of swapping stations and load balancing. According to this model, a traffic drive planning algorithm based on computational geometry is presented. The experimental results illustrate that the deployment scheme obtained by the proposed algorithm is significantly optimized in terms of the deployment cost and service load and has a lower algorithm time complexity than the typical unified deployment scheme. Therefore, the proposed method can be applied to improve the operating efficiency of the urban electric taxi system.