WEKO3
アイテム
Adaptive Approaches in Mobile Phone Based Traffic State Estimation with Low Penetration Rate
https://ipsj.ixsq.nii.ac.jp/records/79965
https://ipsj.ixsq.nii.ac.jp/records/7996535325255-ffe3-4a92-833b-9e7236e046b8
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
IPSJ-JNL5301028 (1.1 MB)
|
Copyright (c) 2012 by the Information Processing Society of Japan
|
|
| オープンアクセス | ||
| Item type | Journal(1) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 公開日 | 2012-01-15 | |||||||||
| タイトル | ||||||||||
| タイトル | Adaptive Approaches in Mobile Phone Based Traffic State Estimation with Low Penetration Rate | |||||||||
| タイトル | ||||||||||
| 言語 | en | |||||||||
| タイトル | Adaptive Approaches in Mobile Phone Based Traffic State Estimation with Low Penetration Rate | |||||||||
| 言語 | ||||||||||
| 言語 | eng | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | 特集：新たな展開を迎えるITS、モバイル通信とユビキタスコンピューティング | |||||||||
| 資源タイプ | ||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||
| 資源タイプ | journal article | |||||||||
| 著者所属 | ||||||||||
| Shibaura Institute of Technology, Department of Communications Engineering, College of Engineering | ||||||||||
| 著者所属 | ||||||||||
| Shibaura Institute of Technology, Department of Communications Engineering, College of Engineering | ||||||||||
| 著者所属(英) | ||||||||||
| en | ||||||||||
| Shibaura Institute of Technology, Department of Communications Engineering, College of Engineering | ||||||||||
| 著者所属(英) | ||||||||||
| en | ||||||||||
| Shibaura Institute of Technology, Department of Communications Engineering, College of Engineering | ||||||||||
| 著者名 |
QuangTranMinh
× QuangTranMinh
× Eiji, Kamioka
|
|||||||||
| 著者名(英) |
Quang, TranMinh
× Quang, TranMinh
× Eiji, Kamioka
|
|||||||||
| 論文抄録 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | The penetration rate is one of the most important factors that affects the effectiveness of the mobile phone-based traffic state estimation. This article thoroughly investigates the influence of the penetration rate on the traffic state estimation using mobile phones as traffic probes and proposes reasonable solutions to minimize such influence. In this research, the so-called “acceptable” penetration rate, at which the estimation accuracy is kept as an “acceptable” level, is identified. This recognition is important to bring the mobile phone-based traffic state estimation systems into realization. In addition, two novel “velocity-density inference” models, namely the “adaptive” and the “adaptive feedback” velocity-density inference circuits, are proposed to improve the effectiveness of the traffic state estimation. Furthermore, an artificial neural network-based prediction approach is introduced to a the effectiveness of the velocity and the density estimation when the penetration rate degrades to 0%. These improvements are practically meaningful since they help to guarantee a high accurate traffic state estimation, even in cases of very low penetration rate. The experimental evaluations reveal the effectiveness as well as the robustness of the proposed solutions. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.20(2012) No.1 (online) DOI http://dx.doi.org/10.2197/ipsjjip.20.297 ------------------------------ |
|||||||||
| 論文抄録(英) | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | The penetration rate is one of the most important factors that affects the effectiveness of the mobile phone-based traffic state estimation. This article thoroughly investigates the influence of the penetration rate on the traffic state estimation using mobile phones as traffic probes and proposes reasonable solutions to minimize such influence. In this research, the so-called “acceptable” penetration rate, at which the estimation accuracy is kept as an “acceptable” level, is identified. This recognition is important to bring the mobile phone-based traffic state estimation systems into realization. In addition, two novel “velocity-density inference” models, namely the “adaptive” and the “adaptive feedback” velocity-density inference circuits, are proposed to improve the effectiveness of the traffic state estimation. Furthermore, an artificial neural network-based prediction approach is introduced to a the effectiveness of the velocity and the density estimation when the penetration rate degrades to 0%. These improvements are practically meaningful since they help to guarantee a high accurate traffic state estimation, even in cases of very low penetration rate. The experimental evaluations reveal the effectiveness as well as the robustness of the proposed solutions. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.20(2012) No.1 (online) DOI http://dx.doi.org/10.2197/ipsjjip.20.297 ------------------------------ |
|||||||||
| 書誌レコードID | ||||||||||
| 収録物識別子タイプ | NCID | |||||||||
| 収録物識別子 | AN00116647 | |||||||||
| 書誌情報 |
情報処理学会論文誌 巻 53, 号 1, 発行日 2012-01-15 |
|||||||||
| ISSN | ||||||||||
| 収録物識別子タイプ | ISSN | |||||||||
| 収録物識別子 | 1882-7764 | |||||||||
