A companion of moving objects is an object group that move together in a period of time. Platoon companions are a generalised companion pattern, which describes a group of objects that move together for time segments, each with some minimum consecutive duration of time. This study proposes a method that can instantly discover platoon companions from a special kind of streaming traffic data, called automatic number plate recognition data. Compared to related approaches, the authors transform the companion discovery into a frequent sequence mining problem. The authors propose a data structure, platoon tree (PTree), to record discovered platoon companions. To reduce the cost of tree traversal during mining platoon companions, they utilise the last two together-moving objects of a group to update PTree. Finally, a lot of experiments have been carried out to show the efficiency and effectiveness of the proposed approach.
Approach to discovering companion patterns based on traffic data stream
IET Intelligent Transport Systems ; 12 , 10 ; 1351-1359
2018-10-09
9 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
called automatic number plate recognition data , data structures , frequent sequence mining problem , trees (mathematics) , related approaches , companion patterns , platoon tree , object group , discovered platoon companions , data mining , generalised companion pattern , traffic engineering computing , mining platoon companions , time segments , data structure , tree data structures , traffic data stream , companion discovery
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