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Can Priors Be Trusted? Learning to Anticipate Roadworks

Abstract:

This paper addresses the question of how much a previously obtained map of a road environment should be trusted for vehicle localisation during autonomous driving by assessing the probability that roadworks are being traversed. We compare two formulations of a roadwork prior: one based on Gaussian Process (GP) classification and the other on a more conventional Hidden Markov Model (HMM) in order to model correlations between nearby parts of a vehicle trajectory. Importantly, our formulation a...

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Publication status:
Published

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Publisher copy:
10.1109/ITSC.2012.6338696

Authors


Mathibela, B More by this author
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Institution:
University of Oxford
Department:
Oxford, MPLS, Engineering Science
Journal:
2012 15TH INTERNATIONAL IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC)
Pages:
927-932
Publication date:
2012
DOI:
ISSN:
2153-0009
URN:
uuid:1bb31003-6e6c-457b-ac9f-70559251bdd9
Source identifiers:
371423
Local pid:
pubs:371423
Language:
English

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