Abstract
Dangerous driving behaviors can lead to traffic accidents. However, there is a lack of systematic real-Time driving monitoring and alerting mechanism. In this paper, nine major dangerous driving behaviors are identified and defined based on past researches and experiences. An on-board safety driving assistance system, which utilizes in-vehicle dynamics and real-Time traffic information, is proposed to instantly detect dangerous driving behaviors and alert the driver during driving periods. The in-vehicle dynamics are collected from On-Board Diagnostics (OBD-II), an accelerometer and a gyroscope. The real-Time traffic information is collected from a camera with image processing. The proposed system is implemented on a CPU board with a user interface (UI), which shows alerting icons when dangerous behaviors occur.
Original language | English |
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Title of host publication | Proceedings - 2017 IEEE 8th International Conference on Awareness Science and Technology, iCAST 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 416-421 |
Number of pages | 6 |
ISBN (Electronic) | 9781538629659 |
DOIs | |
Publication status | Published - 2017 Jul 1 |
Event | 8th IEEE International Conference on Awareness Science and Technology, iCAST 2017 - Taichung, Taiwan Duration: 2017 Nov 8 → 2017 Nov 10 |
Publication series
Name | Proceedings - 2017 IEEE 8th International Conference on Awareness Science and Technology, iCAST 2017 |
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Volume | 2018-January |
Other
Other | 8th IEEE International Conference on Awareness Science and Technology, iCAST 2017 |
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Country | Taiwan |
City | Taichung |
Period | 17-11-08 → 17-11-10 |
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All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications
- Computer Vision and Pattern Recognition
- Control and Optimization
- Health Informatics
Cite this
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A safety driving assistance system by integrating in-vehicle dynamics and real-Time traffic information. / Tsai, Yi Cheng; Lee, Wei-Hsun; Chou, Chien Ming.
Proceedings - 2017 IEEE 8th International Conference on Awareness Science and Technology, iCAST 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 416-421 (Proceedings - 2017 IEEE 8th International Conference on Awareness Science and Technology, iCAST 2017; Vol. 2018-January).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - A safety driving assistance system by integrating in-vehicle dynamics and real-Time traffic information
AU - Tsai, Yi Cheng
AU - Lee, Wei-Hsun
AU - Chou, Chien Ming
PY - 2017/7/1
Y1 - 2017/7/1
N2 - Dangerous driving behaviors can lead to traffic accidents. However, there is a lack of systematic real-Time driving monitoring and alerting mechanism. In this paper, nine major dangerous driving behaviors are identified and defined based on past researches and experiences. An on-board safety driving assistance system, which utilizes in-vehicle dynamics and real-Time traffic information, is proposed to instantly detect dangerous driving behaviors and alert the driver during driving periods. The in-vehicle dynamics are collected from On-Board Diagnostics (OBD-II), an accelerometer and a gyroscope. The real-Time traffic information is collected from a camera with image processing. The proposed system is implemented on a CPU board with a user interface (UI), which shows alerting icons when dangerous behaviors occur.
AB - Dangerous driving behaviors can lead to traffic accidents. However, there is a lack of systematic real-Time driving monitoring and alerting mechanism. In this paper, nine major dangerous driving behaviors are identified and defined based on past researches and experiences. An on-board safety driving assistance system, which utilizes in-vehicle dynamics and real-Time traffic information, is proposed to instantly detect dangerous driving behaviors and alert the driver during driving periods. The in-vehicle dynamics are collected from On-Board Diagnostics (OBD-II), an accelerometer and a gyroscope. The real-Time traffic information is collected from a camera with image processing. The proposed system is implemented on a CPU board with a user interface (UI), which shows alerting icons when dangerous behaviors occur.
UR - http://www.scopus.com/inward/record.url?scp=85050700232&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85050700232&partnerID=8YFLogxK
U2 - 10.1109/ICAwST.2017.8256491
DO - 10.1109/ICAwST.2017.8256491
M3 - Conference contribution
AN - SCOPUS:85050700232
T3 - Proceedings - 2017 IEEE 8th International Conference on Awareness Science and Technology, iCAST 2017
SP - 416
EP - 421
BT - Proceedings - 2017 IEEE 8th International Conference on Awareness Science and Technology, iCAST 2017
PB - Institute of Electrical and Electronics Engineers Inc.
ER -