Academic Journal

A comparative analysis of trajectory similarity measures

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: A comparative analysis of trajectory similarity measures
Συγγραφείς: Yaguang Tao, Alan Both, Rodrigo I. Silveira, Kevin Buchin, Stef Sijben, Ross S. Purves, Patrick Laube, Dongliang Peng, Kevin Toohey, Matt Duckham
Συνεισφορές: University of Zurich, Duckham, Matt, Universitat Politècnica de Catalunya. Departament de Matemàtiques, Universitat Politècnica de Catalunya. CGA - Computational Geometry and Applications
Πηγή: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
GIScience & Remote Sensing, Vol 58, Iss 5, Pp 643-669 (2021)
Στοιχεία εκδότη: Informa UK Limited, 2021.
Έτος έκδοσης: 2021
Θεματικοί όροι: Classificació AMS::94 Information And Communication, Matemàtiques i estadística::Matemàtica aplicada a les ciències [Àrees temàtiques de la UPC], Mathematical geography. Cartography, Codificació, Teoria de la, 02 engineering and technology, GA1-1776, Movement analytics, Similarity measure, 500: Naturwissenschaften, 0202 electrical engineering, electronic engineering, information engineering, GE1-350, Network-constrained movement, 910 Geography & travel, network-constrained movement, Teoria de la, 510: Mathematik, Circuits::94C Circuits, 1900 General Earth and Planetary Sciences, Classificació AMS::94 Information And Communication, Circuits::94C Circuits, networks, similarity measures, Trajectory similarity, trajectory similarity, 94 Information And Communication, Circuits::94C Circuits, networks [Classificació AMS], Environmental sciences, 10122 Institute of Geography, Àrees temàtiques de la UPC::Matemàtiques i estadística::Matemàtica aplicada a les ciències, networks, General Earth and Planetary Sciences, movement analytics, Coding theory, Codificació, Similarity measures
Περιγραφή: Computing trajectory similarity is a fundamental operation in movement analytics, required in search, clustering, and classification of trajectories, for example. Yet the range of different but interrelated trajectory similarity measures can be bewildering for researchers and practitioners alike. This paper describes a systematic comparison and methodical exploration of trajectory similarity measures. Specifically, this paper compares five of the most important and commonly used similarity measures: dynamic time warping (DTW), edit distance (EDR), longest common subsequence (LCSS), discrete Fréchet distance (DFD), and Fréchet distance (FD). The paper begins with a thorough conceptual and theoretical comparison. This comparison highlights the similarities and differences between measures in connection with six different characteristics, including their handling of a relative versus absolute time and space, tolerance to outliers, and computational efficiency. The paper further reports on an empirical evaluation of similarity in trajectories with contrasting properties: data about constrained bus movements in a transportation network, and the unconstrained movements of wading birds in a coastal environment. A set of four experiments: a. creates a measurement baseline by comparing similarity measures to a single trajectory subjected to various transformations; b. explores the behavior of similarity measures on network-constrained bus trajectories, grouped based on spatial and on temporal similarity; c. assesses similarity with respect to known behavioral annotations (flight and foraging of oystercatchers); and d. compares bird and bus activity to examine whether they are distinguishable based solely on their movement patterns. The results show that in all instances both the absolute value and the ordering of similarity may be sensitive to the choice of measure. In general, all measures were more able to distinguish spatial differences in trajectories than temporal differences. The paper concludes with a high-level summary of advice and recommendations for selecting and using trajectory similarity measures in practice, with conclusions spanning our three complementary perspectives: conceptual, theoretical, and empirical.
Τύπος εγγράφου: Article
Other literature type
Περιγραφή αρχείου: application/pdf; 2021_Purves_A_comparative_analysis_of_trajectory_similarity_measures.pdf - application/pdf
Γλώσσα: English
ISSN: 1943-7226
1548-1603
DOI: 10.1080/15481603.2021.1908927
DOI: 10.21256/zhaw-24596
DOI: 10.5167/uzh-210337
DOI: 10.13039/501100003329
Σύνδεσμος πρόσβασης: https://doaj.org/article/2e52be8dbbae45318276d782f469aadf
https://research.tudelft.nl/en/publications/a-comparative-analysis-of-trajectory-similarity-measures
https://upcommons.upc.edu/handle/2117/352861
https://www.tandfonline.com/doi/full/10.1080/15481603.2021.1908927
https://hdl.handle.net/2117/352861
https://doi.org/10.1080/15481603.2021.1908927
http://resolver.tudelft.nl/uuid:0157a47f-8beb-43b4-93d3-85b4d7f444ac
https://www.zora.uzh.ch/id/eprint/210337/
https://doi.org/10.5167/uzh-210337
Rights: CC BY
Αριθμός Καταχώρησης: edsair.doi.dedup.....c6d2e2b7bec9ce521c242f444565a9dc
Βάση Δεδομένων: OpenAIRE
Περιγραφή
ISSN:19437226
15481603
DOI:10.1080/15481603.2021.1908927