An application of Bayesian Hidden Markov Models to explore traffic flow conditions in an urban area

An application of Bayesian Hidden Markov Models to explore traffic flow conditions in an urban area

This study employs Bayesian Hidden Markov Models as method to explore vehicle traffic flow conditions in an urban area in Stockholm, based on sensor data from separate road positions. Inter-arrival times are used as the observed sequences. These sequences of inter-arrival times are assumed to be gen...

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Bibliographic Details
Main Author: Andersson, Lovisa
Format: Others
Language:English
Published: Uppsala universitet, Statistiska institutionen 2019
Subjects:
Bayesian statistics
hidden states
Markov chain
traffic flow modeling
filtering
smoothing
most probable state sequence
MCMC
Hamiltonian Monte Carlo
No-U-Turn sampler
Probability Theory and Statistics
Sannolikhetsteori och statistik
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385187

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385187

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