Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/48718
Type of publication: research article
Type of publication (PDB): Straipsnis konferencijos medžiagoje Clarivate Analytics Web of Science ar/ir Scopus / Article in Clarivate Analytics Web of Science or Scopus DB conference proceedings (P1a)
Field of Science: Informatika / Informatics (N009)
Author(s): Vidugirienė, Aušra;Demčenko, Andriejus;Tamošiūnaitė, Minija
Title: Vehicle acceleration prediction using specific road curvature points
Is part of: ICINCO 2009 : 6th international conference on informatics in control, automation and robotics, Milan, Italy, July 2-5, 2009: proceedings. Vol. 2 : Robotics and automation. Setubal: INSTICC Press, 2009
Extent: p. 147-152
Date: 2009
Keywords: Human-like driving;Intelligent driver’s assistance;Longitudinal control;Curve-based parameters
ISBN: 9789896740009
Abstract: In the work vehicle acceleration prediction issue is discussed. Three types of parameters are used for prediction system input: CAN-bus parameters – speed and curvature, derived speed parameters and newly offered specific curve point parameters, denoting changes in a curve. The real road data was used for predictions. Road curvature segments were divided into single and S-type curves. Acceleration was predicted using artificial neural networks and look-up table. The look-up table method showed the best results with newly offered specific curve parameters
Internet: https://hdl.handle.net/20.500.12259/48718
Affiliation(s): Informatikos fakultetas
Taikomosios informatikos katedra
Vytauto Didžiojo universitetas
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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