Abstract
A challenge in the postprocessing of data for a passive Global Positioning System–based travel survey, which constitutes the essence of this paper, is the development of a series of methods for automatically restoring continuous sequences, both in space and in time. Thus trips and activities occurring during the survey period should be identified in chronological order and should respect conventional definitions. On the basis of previous research results and a combination of the experience from the French National Travel Survey 2007–2008 and the Personal Mobility Survey in Lille, France, a series of methods has been developed and applied: (a) filtering invalid data, (b) cutting the data chains into “moving” and “stopping” segments, (c) estimating missing data, (d) assuming mode choice, (e) grouping stop points into visited locations, (f) identifying the type of visited points, (g) map-matching, and (h) connecting segments to trips. To use the maximum available information and guarantee the quality of the results, some feedback between the methods is implemented within the algorithm. The resulting processing system is ready for use in other applications.
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