In the absence of accurate transit demand information, this paper proposes a DRT route planning method based on taxi trajectory data to predict the "potential demand" of demand responsive transit and provide a feasible plan for route planning before transit operation. Firstly, taxi trajectory data in the study area was obtained through data mining, representing the "potential demand" for passenger travel in the area, and candidate station were determined using the k-means clustering algorithm. Secondly, a benchmark station network is established using these candidate station, with edge benchmark stations designated as the starting and ending points of routes. Utilizing the KSP algorithm constrained by route length, benchmark chains are generated. Finally, after determining the sub-chain set of the benchmark chains, demand response stations within each sub-chain are searched based on circumferential critical value constraints. Using this algorithm, alternative routes are generated repeatedly within specific time periods, and an initial optimal route is selected based on comprehensive evaluation indices for each alternative route.