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2018 | OriginalPaper | Chapter

Hidden Markov Model for Floating Car Trajectory Map Matching

Authors : Chengbo Song, Xuefeng Yan

Published in: Advances in Computer Science and Ubiquitous Computing

Publisher: Springer Singapore

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Abstract

Map matching is the key technology in the data processing of floating car trajectory data. In order to improve the matching accuracy, this paper adopted widely followed Hidden Markov Model (HMM) approach and proposed new probabilistic models for the transition probability. The new model considers distance difference feature and average speed difference feature, which was proved to be more reasonable and accurate to describe the context relationship between adjacent candidate points by experiments. The experiments showed that our proposed algorithm can achieve a better matching accuracy compared with a comparable HMM-based method from the literature.

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Metadata
Title
Hidden Markov Model for Floating Car Trajectory Map Matching
Authors
Chengbo Song
Xuefeng Yan
Copyright Year
2018
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-7605-3_91