research-article

An incremental learning technique for detecting driving behaviors using collected EV big data

Authors:

Chung-Hong Lee,

Chih-Hung WuAuthors Info & Claims

ASE BD&SI '15: Proceedings of the ASE BigData & SocialInformatics 2015

Article No.: 10, Pages 1 - 5

https://doi.org/10.1145/2818869.2818935

Published: 07 October 2015 Publication History

Abstract

This paper presents an expansible machine learning approach applying the EV big data as the human sensor to extract driving behaviors and driving modes. A pattern recognition approach is proposed to model the driving pattern according to the energy consumption of an EV. The growing hierarchical self-organizing maps (GHSOM) is applied to learn driver's behaviors gradually in the offline process, and the clustered neurons are used as the training sets for implementing online classifiers based on support vector machine (SVM). This proposed framework would facilitate the understanding of driver's behaviors and help drivers overcome range anxiety.

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Cited By

Lee CWu C(2016)A data driven approach to create an extensible EV driving data modelProceedings of the The 3rd Multidisciplinary International Social Networks Conference on SocialInformatics 2016, Data Science 201610.1145/2955129.2955164(1-6)Online publication date: 15-Aug-2016
https://dl.acm.org/doi/10.1145/2955129.2955164
Salah KKama N(2016)Reducing Range Anxiety by Unifying Networks of Charging StationsMATEC Web of Conferences10.1051/matecconf/2016700400370(04003)Online publication date: 11-Aug-2016
https://doi.org/10.1051/matecconf/20167004003

Index Terms

An incremental learning technique for detecting driving behaviors using collected EV big data
1. Computing methodologies
  1. Machine learning
2. Information systems
  1. Information retrieval
    1. Document representation
  2. Information systems applications
    1. Data mining

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cover image ACM Other conferences

ASE BD&SI '15: Proceedings of the ASE BigData & SocialInformatics 2015

October 2015

381 pages

ISBN:9781450337359

DOI:10.1145/2818869

Copyright © 2015 ACM.

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Publication History

Published: 07 October 2015

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ASE BD&SI '15

ASE BD&SI '15: ASE BigData & SocialInformatics 2015

October 7 - 9, 2015

Kaohsiung, Taiwan

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Cited By

Lee CWu C(2016)A data driven approach to create an extensible EV driving data modelProceedings of the The 3rd Multidisciplinary International Social Networks Conference on SocialInformatics 2016, Data Science 201610.1145/2955129.2955164(1-6)Online publication date: 15-Aug-2016
https://dl.acm.org/doi/10.1145/2955129.2955164
Salah KKama N(2016)Reducing Range Anxiety by Unifying Networks of Charging StationsMATEC Web of Conferences10.1051/matecconf/2016700400370(04003)Online publication date: 11-Aug-2016
https://doi.org/10.1051/matecconf/20167004003

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