An HMM-based map matching method with cumulative proximity-weight formulation
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Jaillet_an HMM-based.pdf
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949.35 KB
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Author(s)
Oran, Ali
Jaillet, Patrick
Date Issued
December 2013
Journal
Proceedings of the 2013 International Conference on Connected Vehicles and Expo (ICCVE)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Oran, Ali, and Patrick Jaillet. “An HMM-Based Map Matching Method with Cumulative Proximity-Weight Formulation.” 2013 International Conference on Connected Vehicles and Expo (ICCVE) (December 2013).
Version
Author's final manuscript
Abstract
In this study, we introduce a hidden Markov model map matching method that is based on a cumulative proximity-weight formulation. This new formula is based on the line integral of a point-wise segment weight rather than the almost standard shortest distance based weight. The proposed method was tested using vehicle and map data from Seattle area. Several simulations were conducted so as to have a clear comparison of the new weight to the traditional one; and particular emphasis were given to matching of GPS data with long sampling periods and high level noise. Overall, possible improvements to MM accuracies by the new weight were identified. It was seen that the new weight could be a better option than the shortest distance based weight in the presence of low-frequency sampled and/or noisy GPS data.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/ICCVE.2013.6799840
