Theoretically speaking, the data of a stated preference survey could be suggested for the calibration of a stochastic route choice model. However, it is unrealistic to implement the questionnaire survey for such a large number of alternative routes. Engineers generally determine the parameter empirically. This experienced choice of perception parameter may cause higher errors in the route flows. In our calibration model of the perception parameter, the data of the cellular network is set as the input. This model consists of two levels. The upper level is to minimize the gap squares of the route choice ratio between the C-logit model and the cellular network data. The stochastic user equilibrium (SUE) in terms of the C-logit model is used as the lower level. The simulated annealing (SA) algorithm is used to solve the model, where the route-based gradient projection (GP) algorithm is used to solve the inner SUE. A case study is used to validate the convergence of the model calibration. A real-world road network is used to demonstrate the objective advantage of an equilibrium constraint over a nonequilibrium constraint and explain the feasibility of the candidate routes assumption.