Travel Characteristics Extracting Method Based on Cellular Network Recording Data

摘要

Compared to other types of cellular signaling data, cellular network recording data has several unique advantages on extracting travel characteristics, including comprehensive samples, high location accuracy, elaborate trajectory, and high data stability. With such advantageous attributes, a series of methods are proposed in order to extract valuable information. First, in order to build candidate default trajectory point set, Bowyer-Watson algorithm is applied to delimit Voronoi diagram of base station coverage. Second, a user's trajectory is segmented based on motion state discriminant algorithms. This is done in which sample filtering and noise reduction are helpful for parameter extraction. Third, the MBR of trajectory point subset is introduced to improve conventional piecewise map-matching algorithms. Lastly, the proposed algorithm will be evaluated by verifying the accuracy of the parameters. Preliminary results show that the extracted parameters are acceptable for further traffic modeling application at both macro and micro levels and are expected to replace the traditional individual trip survey.