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Precise travel route identification is the guiding basis of feasible urban traffic planning and modeling. A range of map matching (MM) algorithms have been studied in previous research to integrate coordinate-based GPS data with digital road network information to identify personal travel route. However, these methods significantly depend on the high-density positioning data, which are usually unavailable or costly for transportation planning projects. Fortunately, mobile phones under 3 G, 4 G and 5 G networks can generate massive cell-based travel trajectory data with almost no additional cost. This data is potentially valuable for travel route identification if proper MM algorithms can be developed. This paper proposes an MM method to detect travel route by using handoff trajectory data from the cellular phone network. First, a wireless communication simulation model for dynamic cellular handoff-based traffic monitoring is developed for handoff data collection. Second, the Earth Mover's Distance (EMD) algorithm is used to identify travel route by finding the time-space relationship among the cellular handoff patterns of the road network. Finally, by comparing the performance of the proposed method with classical sequence similarity algorithms, results indicate that the EMD-based MM algorithm is much more efficient for travel route identification, and it can detect small spacing parallel roads with a high accuracy. [ABSTRACT FROM AUTHOR]