Uncertain low penetration rate - A practical issue in mobile intelligent transportation systems

Quang Tran Minh, Muhammad Ariff Baharudin, Eiji Kamioka

研究成果: Conference contribution

抄録

Low penetration rate is one of the essential issues in the mobile phone based traffic state estimation model. This paper proposes an appropriate genetic algorithm (GA) mechanism to optimize the traffic state estimation model even in cases of low penetration rate. This mechanism also reduces the critical penetration rate, thus improves the error-tolerance as well as the scalability of the traffic state estimation system. The paper also investigates the ANN-based prediction model to overcome the weakness of the GA-based traffic state estimation approach when the penetration rate becomes unacceptably low. In addition, the effect of different level related road segments on the prediction effectiveness is thoroughly discussed. Consequently, this study provides practically useful instructions in verifying the data missing rate at different level related road segments to ensure the prediction accuracy. The experimental evaluations reveal the effectiveness and the robustness of the proposed solutions.

本文言語English
ホスト出版物のタイトルProceedings - 26th IEEE International Conference on Advanced Information Networking and Applications, AINA 2012
ページ237-244
ページ数8
DOI
出版ステータスPublished - 2012
イベント26th IEEE International Conference on Advanced Information Networking and Applications, AINA 2012 - Fukuoka, Japan
継続期間: 2012 3 262012 3 29

出版物シリーズ

名前Proceedings - International Conference on Advanced Information Networking and Applications, AINA
ISSN(印刷版)1550-445X

Conference

Conference26th IEEE International Conference on Advanced Information Networking and Applications, AINA 2012
CountryJapan
CityFukuoka
Period12/3/2612/3/29

ASJC Scopus subject areas

  • Engineering(all)

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