Transactions of Society of Automotive Engineers of Japan
Online ISSN : 1883-0811
Print ISSN : 0287-8321
ISSN-L : 0287-8321
Research Paper
High-precision traffic congestion detection using lane-by-lane polygons
Naoko ShigematsuIchibe NaitoNobuhiro OkiIsoo UenoAtsushi IsomuraYasuhiro IidaTakao Nakamura
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2022 Volume 53 Issue 3 Pages 705-710

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Abstract
Traffic congestion near shopping centers or traffic accidents may be avoided by keeping away from specific lanes. Therefore, this study proposes a large-scale distributed data processing technique and a polygonal-shape based data search technique to detect traffic congestion at a higher accuracy than VICS. The implementation and experiments suggest establishment of a semi-real-time lane-by-lane traffic congestion detection method possibly be used for nationwide vehicle data.
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© 2022 Society of Automotive Engineers of Japan, Inc.
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