Route Prediction from GPS Trajectory and Road Data

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dc.contributor.authorChawuthai, Rathachai
dc.contributor.authorKawachakul, Kampanart
dc.contributor.authorBoonrod, Kittikom
dc.contributor.authorThreepak, Thanunchai
dc.date.accessioned2026-08-06T10:40:06Z
dc.date.available2026-08-06T10:40:06Z
dc.date.issued2023-01-01
dc.description.abstractThis paper presents an approach to create a route prediction model for multiple vehicles from GPS trajectory and road data. Since the baseline model is designed for a single car and it provides low performance for our experiment, our approach using the HDBSCAN clustering for route data preprocessing and the prediction model based on Viterbi algorithm, which is an extension of the Hidden Markov Model, provides the better performance in terms of Hit@K where K being 3. The result of our work demonstrates the feasibility to improve the smart city technology under the scope of smart mobility as well. (Abstract)
dc.identifier.citation2023 15th International Conference on Computer and Automation Engineering Iccae 2023, 65-69, 2023
dc.identifier.doi10.1109/ICCAE56788.2023.10111441
dc.identifier.other2-s2.0-85159617209
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/14051
dc.source2023 15th International Conference on Computer and Automation Engineering Iccae 2023
dc.subjectGPS data analytics
dc.subjectmachine learning
dc.subjectroute prediction
dc.titleRoute Prediction from GPS Trajectory and Road Data
dc.typeConference Paper

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