A driving assistance system with vision based vehicle detection techniques

Jyun Min Dai; Lu Ting Wu; Huei Yung Lin; Wen Lung Tai

doi:10.1109/APSIPA.2016.7820739

A driving assistance system with vision based vehicle detection techniques

Jyun Min Dai
, Lu Ting Wu
, Huei Yung Lin
, Wen Lung Tai

Department of Computer Science and Information Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Scopus citations

Abstract

Lane departure and forward collision detection plays an important role in autonomous driving and commercial driver-assistance systems. This paper presents an integrative approach to vision-based lane departure detection which aims to be as simple as possible to enable the real-time computation while being able to adapt to a variety of highway and urban scenarios on different weather conditions. In this work, we also implement a vision-based forward collision warning system and an overtaking vehicle detection system. The forward collision warning system aims to detect other vehicles driving ahead of the host vehicle so as to avoid the potential traffic accidents. On the other hand, the overtaking vehicle detection system is to detect other vehicles behind or on the side of the host vehicle so as to give an alert to the driver when the vehicle begins overtaking. Experimental results are presented with real scene video sequences. The performance evaluation has demonstrated the effectiveness of the proposed techniques.

Original language	English
Title of host publication	2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9789881476821
DOIs	https://doi.org/10.1109/APSIPA.2016.7820739
State	Published - 17 Jan 2017
Event	2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016 - Jeju, Korea, Republic of Duration: 13 Dec 2016 → 16 Dec 2016

Publication series

Name	2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016

Conference

Conference	2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016
Country/Territory	Korea, Republic of
City	Jeju
Period	13/12/16 → 16/12/16

Bibliographical note

Publisher Copyright:
© 2016 Asia Pacific Signal and Information Processing Association.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Access to Document

10.1109/APSIPA.2016.7820739

Cite this

Dai, J. M., Wu, L. T., Lin, H. Y., & Tai, W. L. (2017). A driving assistance system with vision based vehicle detection techniques. In 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016 Article 7820739 (2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/APSIPA.2016.7820739

Dai, Jyun Min ; Wu, Lu Ting ; Lin, Huei Yung et al. / A driving assistance system with vision based vehicle detection techniques. 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016. Institute of Electrical and Electronics Engineers Inc., 2017. (2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016).

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title = "A driving assistance system with vision based vehicle detection techniques",

abstract = "Lane departure and forward collision detection plays an important role in autonomous driving and commercial driver-assistance systems. This paper presents an integrative approach to vision-based lane departure detection which aims to be as simple as possible to enable the real-time computation while being able to adapt to a variety of highway and urban scenarios on different weather conditions. In this work, we also implement a vision-based forward collision warning system and an overtaking vehicle detection system. The forward collision warning system aims to detect other vehicles driving ahead of the host vehicle so as to avoid the potential traffic accidents. On the other hand, the overtaking vehicle detection system is to detect other vehicles behind or on the side of the host vehicle so as to give an alert to the driver when the vehicle begins overtaking. Experimental results are presented with real scene video sequences. The performance evaluation has demonstrated the effectiveness of the proposed techniques.",

author = "Dai, \{Jyun Min\} and Wu, \{Lu Ting\} and Lin, \{Huei Yung\} and Tai, \{Wen Lung\}",

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Dai, JM, Wu, LT, Lin, HY & Tai, WL 2017, A driving assistance system with vision based vehicle detection techniques. in 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016., 7820739, 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016, Institute of Electrical and Electronics Engineers Inc., 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016, Jeju, Korea, Republic of, 13/12/16. https://doi.org/10.1109/APSIPA.2016.7820739

A driving assistance system with vision based vehicle detection techniques. / Dai, Jyun Min; Wu, Lu Ting; Lin, Huei Yung et al.
2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016. Institute of Electrical and Electronics Engineers Inc., 2017. 7820739 (2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Lin, Huei Yung

AU - Tai, Wen Lung

PY - 2017/1/17

Y1 - 2017/1/17

N2 - Lane departure and forward collision detection plays an important role in autonomous driving and commercial driver-assistance systems. This paper presents an integrative approach to vision-based lane departure detection which aims to be as simple as possible to enable the real-time computation while being able to adapt to a variety of highway and urban scenarios on different weather conditions. In this work, we also implement a vision-based forward collision warning system and an overtaking vehicle detection system. The forward collision warning system aims to detect other vehicles driving ahead of the host vehicle so as to avoid the potential traffic accidents. On the other hand, the overtaking vehicle detection system is to detect other vehicles behind or on the side of the host vehicle so as to give an alert to the driver when the vehicle begins overtaking. Experimental results are presented with real scene video sequences. The performance evaluation has demonstrated the effectiveness of the proposed techniques.

AB - Lane departure and forward collision detection plays an important role in autonomous driving and commercial driver-assistance systems. This paper presents an integrative approach to vision-based lane departure detection which aims to be as simple as possible to enable the real-time computation while being able to adapt to a variety of highway and urban scenarios on different weather conditions. In this work, we also implement a vision-based forward collision warning system and an overtaking vehicle detection system. The forward collision warning system aims to detect other vehicles driving ahead of the host vehicle so as to avoid the potential traffic accidents. On the other hand, the overtaking vehicle detection system is to detect other vehicles behind or on the side of the host vehicle so as to give an alert to the driver when the vehicle begins overtaking. Experimental results are presented with real scene video sequences. The performance evaluation has demonstrated the effectiveness of the proposed techniques.

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Dai JM, Wu LT, Lin HY, Tai WL. A driving assistance system with vision based vehicle detection techniques. In 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016. Institute of Electrical and Electronics Engineers Inc. 2017. 7820739. (2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016). doi: 10.1109/APSIPA.2016.7820739

A driving assistance system with vision based vehicle detection techniques

Abstract

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Bibliographical note

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