Cited By
View all- Cheng XRen LCui JZhang Z(2017)Traffic Flow Prediction with Improved SOPIO-SVR AlgorithmChallenges and Opportunity with Big Data10.1007/978-3-319-61994-1_17(184-197)Online publication date: 4-Aug-2017
Improving route prediction through user journey detection
Pages 476 - 479
Abstract
The positioning datasets that underpin route prediction models arrive as time series or point process logs. However, their use for prediction requires them to be split into meaningful segments, conceptualised as travelling periods or 'journeys', to form a set of training inputs. Despite significant research into route prediction, this important pre-processing step has traditionally occurred in an ad-hoc fashion, using arbitrary connectivity or movement thresholds. There has been little consideration to date of the impact of this on prediction, a fact rectified in this work.
Three methods for detection of journeys are evaluated using a dataset of labelled movement histories collected specifically for this investigation. We perform an exhaustive series of parameterisations of detection methods, optimising with respect to actual journeys specified by users. We find that using existing methods, GPS multipath artefacts introduce journey extraction error that raises concern for prediction applications. A new approach is presented that explicitly uses these effects to improve journey detection results.
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Index Terms
- Improving route prediction through user journey detection
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Published In
November 2013
598 pages
ISBN:9781450325219
DOI:10.1145/2525314
- General Chairs:
- Craig Knoblock,
- Markus Schneider,
- Program Chairs:
- Peer Kröger,
- John Krumm,
- Peter Widmayer
Copyright © 2013 Owner/Author.
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Published: 05 November 2013
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SIGSPATIAL'13
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SIGSPATIAL'13: 21st SIGSPATIAL International Conference on Advances in Geographic Information Systems
November 5 - 8, 2013
Florida, Orlando
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View all- Cheng XRen LCui JZhang Z(2017)Traffic Flow Prediction with Improved SOPIO-SVR AlgorithmChallenges and Opportunity with Big Data10.1007/978-3-319-61994-1_17(184-197)Online publication date: 4-Aug-2017
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