In this paper, mobile phone signaling data are first processed to extract information such as the trip volume and spatial distribution from the starting point to the termination point. This information is then used to identify the residential and employment locations of users. Next, multiple Thiessen polygons based on cell towers are aggregated into Traffic Analysis Zones (TAZs) to minimize differences between the actual cell tower coverage and the theoretical coverage. Then, based on TAZ cluster analysis involving transport accessibility and commuting population density, multiple stepwise regression is applied to obtain the commuting trip production rates and attraction rates for overall residential land and each subdivided housing type during the peak morning hours. The obtained commuting trip generation rates can be directly applied to local transport analysis models. This paper suggests that as information and data sharing continue, mobile phone signaling data will become increasingly important for use in future trip rate research.