An Adaptive Rear-End Collision Warning System for Drivers That Estimates Driving Phase and Selects Training Data
-
- Ikeda Kazushi
- Graduate School of Information Science, Nara Institute of Science and Technology
-
- Mima Hiroki
- Graduate School of Information Science, Nara Institute of Science and Technology
-
- Inoue Yuta
- Graduate School of Information Science, Nara Institute of Science and Technology
-
- Shibata Tomohiro
- Graduate School of Information Science, Nara Institute of Science and Technology
-
- Fukaya Naoki
- DENSO CORPORATION
-
- Hitomi Kentaro
- DENSO CORPORATION
-
- Bando Takashi
- DENSO CORPORATION
Bibliographic Information
- Other Title
-
- 運転状況を推定し学習データを選択する適応的ブレーキ警報システム
- ウンテン ジョウキョウ オ スイテイ シ ガクシュウ データ オ センタク スル テキオウテキ ブレーキ ケイホウ システム
Search this article
Abstract
The paper proposes a rear-end collision warning system for drivers, where the collision risk is adaptively set from driving signals. The system employs the inverse of the time-to-collision with a constant relative acceleration as the risk and the one-class support vector machine as the anomaly detector. The system also utilizes brake sequences for outliers detection. When a brake sequence has a low likelihood with respect to trained hidden Markov models, the driving data during the sequence are removed from the training dataset. This data selection is confirmed to increase the robustness of the system by computer simulations. <br>
Journal
-
- Transactions of the Institute of Systems, Control and Information Engineers
-
Transactions of the Institute of Systems, Control and Information Engineers 24 (8), 193-199, 2011
THE INSTITUTE OF SYSTEMS, CONTROL AND INFORMATION ENGINEERS (ISCIE)
- Tweet
Keywords
Details 詳細情報について
-
- CRID
- 1390001205166706048
-
- NII Article ID
- 10030146265
-
- NII Book ID
- AN1013280X
-
- ISSN
- 2185811X
- 13425668
-
- NDL BIB ID
- 11191349
-
- Text Lang
- ja
-
- Data Source
-
- JaLC
- NDL
- Crossref
- CiNii Articles
-
- Abstract License Flag
- Disallowed
