Daily O-D Matrix Estimation using Cellular Probe Data

Abstract

With the fast-growing wireless-communication market, the cellular positioning technologies are becoming one of the important means to monitoring real-time traffic status, providing traveler information, measuring system operations performance, and estimating travel demand. An innovative methodology is presented in this paper to estimate the daily O-D demand using cellular trajectory information. Taking advantages of the emerging cell phone tracking technologies, the cellular trajectories are obtained by recording all the signal-transition events and period location update events of cellular probes to determine the trip origins and destinations. To apply the O-D estimation to a broader spectrum, the probability of cell-phone ownership was treated as a conditional probability depending on user's socio-economic factors available in the census data such as age, rage, household income, etc.. A mathematic model was designed to convert the cellular counts into equivalent vehicle counts, using the posterior information obtained from the characteristics of cellular trajectories. Next, the traveling population daily O-D demand was estimated via a robust Horvitz-Thompson estimator. Finally, the methodology was tested via a VISSIM simulation and results were compared with a conventional simple random sampling (SRS) method. The comparison outcome shows great potential of using cellular trajectory information as a means to estimating daily O-D travel demand.