Presentation 2011-01-20
A driving diagnosis and instruction system based on past driving data
Kenji KURUMIDA, Yuichi KUROYANAGI, Chiyomi MIYAJIMA, Norihide KITAOKA, Kazuya TAKEDA,
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Abstract(in English) We propose a driving diagnosis and feedback system which detects hazardous situations of risky driving behavior from driver's own driving data and efficiently provides feedback to drivers using a GIS-based system. Driving data was recorded using various sensors such as cameras, an accelerometer, laser scanners and GPS. Our drive recorder detects nine types of hazardous situations including insufficient following distance, excessive speed, and risky behavior when passing obstacles or at poor visibility intersections, as well as three situations which can also be detected by conventional drive recorders. Our system efficiently provides feedback to drivers by showing examples of their own risky driving behavior, with maps, videos, related driving signals, and advices. After providing feedback, the number of hazardous scenes was decreased by about 55.6%.
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Keyword(in English) ITS / GIS / Driving diagnosis / Driver model
Paper # PRMU2010-163,MVE2010-88
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Conference Information
Committee PRMU
Conference Date 2011/1/13(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A driving diagnosis and instruction system based on past driving data
Sub Title (in English)
Keyword(1) ITS
Keyword(2) GIS
Keyword(3) Driving diagnosis
Keyword(4) Driver model
1st Author's Name Kenji KURUMIDA
1st Author's Affiliation Graduate School of Information Science, Nagoya University()
2nd Author's Name Yuichi KUROYANAGI
2nd Author's Affiliation Graduate School of Information Science, Nagoya University
3rd Author's Name Chiyomi MIYAJIMA
3rd Author's Affiliation Graduate School of Information Science, Nagoya University
4th Author's Name Norihide KITAOKA
4th Author's Affiliation Graduate School of Information Science, Nagoya University
5th Author's Name Kazuya TAKEDA
5th Author's Affiliation Graduate School of Information Science, Nagoya University
Date 2011-01-20
Paper # PRMU2010-163,MVE2010-88
Volume (vol) vol.110
Number (no) 381
Page pp.pp.-
#Pages 6
Date of Issue