Vision-based driving environment identification for autonomous highway vehicles

Yao Jan Wu; Chun Po Huang; Feng Li Lian; Tang Hsien Chang

Vision-based driving environment identification for autonomous highway vehicles

Yao Jan Wu, Chun Po Huang, Feng Li Lian, Tang Hsien Chang

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

Abstract

In this paper, we propose an approach to identify the driving environment for autonomous highway vehicles by means of image processing and computer vision techniques. The proposed approach is mainly composed of two consecutive computational steps. The first step is the lane markings detection, used to identify the location of host vehicle and road geometry. The second one is the vehicle detection that can provide relative position and speed between host vehicle and each preceding vehicle. The proposed approach has been validated in several real-world scenes. Herein, the experimental results indicate low false alarm and low false dismissal and have demonstrated the robustness of the proposed detection approach.

Original language	English (US)
Title of host publication	Conference Proceeding - 2004 IEEE International Conference on Networking, Sensing and Control
Pages	1323-1328
Number of pages	6
State	Published - 2004
Externally published	Yes
Event	Conference Proceeding - 2004 IEEE International Conference on Networking, Sensing and Control - Taipei, Taiwan, Province of China Duration: Mar 21 2004 → Mar 23 2004

Publication series

Name	Conference Proceeding - IEEE International Conference on Networking, Sensing and Control
Volume	2

Other

Other	Conference Proceeding - 2004 IEEE International Conference on Networking, Sensing and Control
Country/Territory	Taiwan, Province of China
City	Taipei
Period	3/21/04 → 3/23/04

Keywords

Computer vision
Driving environment identification
Image processing
Lane markings detection
Vehicle detection

ASJC Scopus subject areas

General Engineering

Cite this

Vision-based driving environment identification for autonomous highway vehicles. / Wu, Yao Jan; Huang, Chun Po; Lian, Feng Li et al.
Conference Proceeding - 2004 IEEE International Conference on Networking, Sensing and Control. 2004. p. 1323-1328 (Conference Proceeding - IEEE International Conference on Networking, Sensing and Control; Vol. 2).

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

Wu, YJ, Huang, CP, Lian, FL & Chang, TH 2004, Vision-based driving environment identification for autonomous highway vehicles. in Conference Proceeding - 2004 IEEE International Conference on Networking, Sensing and Control. Conference Proceeding - IEEE International Conference on Networking, Sensing and Control, vol. 2, pp. 1323-1328, Conference Proceeding - 2004 IEEE International Conference on Networking, Sensing and Control, Taipei, Taiwan, Province of China, 3/21/04.

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title = "Vision-based driving environment identification for autonomous highway vehicles",

abstract = "In this paper, we propose an approach to identify the driving environment for autonomous highway vehicles by means of image processing and computer vision techniques. The proposed approach is mainly composed of two consecutive computational steps. The first step is the lane markings detection, used to identify the location of host vehicle and road geometry. The second one is the vehicle detection that can provide relative position and speed between host vehicle and each preceding vehicle. The proposed approach has been validated in several real-world scenes. Herein, the experimental results indicate low false alarm and low false dismissal and have demonstrated the robustness of the proposed detection approach.",

keywords = "Computer vision, Driving environment identification, Image processing, Lane markings detection, Vehicle detection",

author = "Wu, {Yao Jan} and Huang, {Chun Po} and Lian, {Feng Li} and Chang, {Tang Hsien}",

year = "2004",

language = "English (US)",

isbn = "0780381939",

series = "Conference Proceeding - IEEE International Conference on Networking, Sensing and Control",

pages = "1323--1328",

booktitle = "Conference Proceeding - 2004 IEEE International Conference on Networking, Sensing and Control",

note = "Conference Proceeding - 2004 IEEE International Conference on Networking, Sensing and Control ; Conference date: 21-03-2004 Through 23-03-2004",

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TY - GEN

T1 - Vision-based driving environment identification for autonomous highway vehicles

AU - Wu, Yao Jan

AU - Huang, Chun Po

AU - Lian, Feng Li

AU - Chang, Tang Hsien

PY - 2004

Y1 - 2004

N2 - In this paper, we propose an approach to identify the driving environment for autonomous highway vehicles by means of image processing and computer vision techniques. The proposed approach is mainly composed of two consecutive computational steps. The first step is the lane markings detection, used to identify the location of host vehicle and road geometry. The second one is the vehicle detection that can provide relative position and speed between host vehicle and each preceding vehicle. The proposed approach has been validated in several real-world scenes. Herein, the experimental results indicate low false alarm and low false dismissal and have demonstrated the robustness of the proposed detection approach.

AB - In this paper, we propose an approach to identify the driving environment for autonomous highway vehicles by means of image processing and computer vision techniques. The proposed approach is mainly composed of two consecutive computational steps. The first step is the lane markings detection, used to identify the location of host vehicle and road geometry. The second one is the vehicle detection that can provide relative position and speed between host vehicle and each preceding vehicle. The proposed approach has been validated in several real-world scenes. Herein, the experimental results indicate low false alarm and low false dismissal and have demonstrated the robustness of the proposed detection approach.

KW - Computer vision

KW - Driving environment identification

KW - Image processing

KW - Lane markings detection

KW - Vehicle detection

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M3 - Conference contribution

AN - SCOPUS:2942648212

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T3 - Conference Proceeding - IEEE International Conference on Networking, Sensing and Control

SP - 1323

EP - 1328

BT - Conference Proceeding - 2004 IEEE International Conference on Networking, Sensing and Control

T2 - Conference Proceeding - 2004 IEEE International Conference on Networking, Sensing and Control

Y2 - 21 March 2004 through 23 March 2004

ER -

Vision-based driving environment identification for autonomous highway vehicles

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

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