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On-road Directional Trajectory Prediction by Junction-based Pattern Mining from GPS Data
Suash Deb1; Congmao Jia2; Simon Fong2
2014-10-08
Conference Name2013 International Conference on Machine Intelligence Research and Advancement
Source PublicationProceedings - 2013 International Conference on Machine Intelligence Research and Advancement, ICMIRA 2013
Pages253-257
Conference Date21-23 Dec. 2013
Conference PlaceKatra, India
PublisherIEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Abstract

On-road trajectory prediction has its important applications such as road traffic security and urban road planning. In the past, mathematical models have been formulated for predicting the trajectory of a particular moving object by tracking its latest GPS records. The methods are capable in pinpointing the predicted location in terms of GPS coordinates in the near future. However, in reality, cars and pedestrians do neither move in line-of-sight nor perfect projectile in urban roads. Rather they navigate from junction-to-junction and around building blocks on the roads. In this paper, the authors propose a new computational framework that predicts the next moving direction of on-road trajectory at a junction, based on the probabilities of junction-turns from the aggregated historical traffic patterns. The prediction is constrained by the road formation, the trajectory is tracked by the route that a moving object has travelled, in some abstract format of node pattern. Simple pattern mining is used to match the travelled route with the most frequent routes recorded in the database, for inferring what the next most probable turn will be from the current junction. A simulation experiment is conducted by using Microsoft Trajectory Dataset, that validates the model is efficient and effective.

KeywordPattern Mining Trajectory Prediction
DOIhttps://doi.org/10.1109/ICMIRA.2013.54
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000353945100042
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Cited Times [WOS]:2   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.Department of Computer Science and Engineering, Cambridge Institute of Technology, Ranchi, India
2.Department of Computer and Information Science, University of Macau, Taipa, Macau SAR
Recommended Citation
GB/T 7714
Suash Deb,Congmao Jia,Simon Fong. On-road Directional Trajectory Prediction by Junction-based Pattern Mining from GPS Data[C]:IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA,2014:253-257.
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