Caron, Monsieur Marceau (2022) The applications of Hidden Markov Model for Map and Context Matching PRE - Research Project, ENSTA.



Like most fields, mobility collects and accumulates data that must be processed and analyzed to extract its full potential. Mobility data science is one of the builders of the city of tomorrow. The problem of matching noisy trajectory points with a path on a Map — known as Map Matching problem — is one of the most fundamental in mobility data science. This report relates a thorough study of how to solve it with the hidden Markov model. Subsequently, it attempts to adapt and expand the method in order to address a broader issue by matching trajectory points with the context of the travel. A genetic algorithm then appears as an efficient way to proceed.

Item Type:Thesis (PRE - Research Project)
Uncontrolled Keywords:Mobility Data Science, Hidden Markov Model, Map Matching, Genetic Algorithm, C++
Subjects:Mathematics and Applications
ID Code:9146
Deposited By:Marceau Caron
Deposited On:07 juin 2023 10:56
Dernière modification:07 juin 2023 10:56

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