Pattern Recognition in Complex Activity Travel Patterns: Comparison of Euclidean Distance, Signal-Processing Theoretical, and Multidimensional Sequence Alignment Methods

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Pattern Recognition in Complex Activity Travel Patterns: Comparison of Euclidean Distance, Signal-Processing Theoretical, and Multidimensional Sequence Alignment Methods

Joh, Chang-Hyeon / Arentze, Theo / Timmermans, Harry

The application of a multidimensional sequence alignment method for classifying activity travel patterns is reported. The method was developed as an alternative to the existing classification methods suggested in the transportation literature. The relevance of the multidimensional sequence alignment method is derived from the fact that structural information (both interdependency and sequential relationships) embedded in activity travel patterns is taken into account—a property not shared with existing classification methods. The performance of the multidimensional sequence alignment method is compared with several other methods (Euclidean distance and signal processing) that have been used in activity analysis in the past.

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Title :

Pattern Recognition in Complex Activity Travel Patterns: Comparison of Euclidean Distance, Signal-Processing Theoretical, and Multidimensional Sequence Alignment Methods

Additional title:

Transportation Research Record

Contributors:

Joh, Chang-Hyeon (author) / Arentze, Theo (author) / Timmermans, Harry (author)

Published in:

Transportation Research Record: Journal of the Transportation Research Board ; 1752 , 1 ; 16-22

Publication date :

2001-01-01

ISSN :

2169-4052 , 0361-1981

DOI :

https://doi.org/10.3141/1752-03