DocumentCode
181871
Title
Vision-based forward collision warning system design supported by a field-test verification platform
Author
Bei Ren ; Weiwen Deng ; Tomm, Christian ; Fei Han ; Ying Wang
Author_Institution
State Key Lab. of Automotive Simulation & Control, Jilin Univ. of China, Changchun, China
fYear
2014
fDate
8-11 June 2014
Firstpage
492
Lastpage
497
Abstract
This paper proposes a novel approach of developing a vision-based forward collision warning system (V-FCW) under an integrated platform with both V-FCW algorithm development and field-test data driven system verification. The developed verification platform provides huge amount of video data collected from field testing under various real driving conditions with labeled ground truth and fast search capability. Under this integrated platform, the V-FCW system can be effectively developed, tested and verified under various real driving conditions and scenarios in a lab environment, and in a repeatable, cost effective and even automatic way to achieve robust, reliable and high performance.
Keywords
alarm systems; computer vision; driver information systems; object detection; video signal processing; V-FCW algorithm development; V-FCW system; driving conditions; field-test data driven system verification platform; integrated platform; laboratory environment; video data; vision-based forward collision warning system design; Accuracy; Estimation; IP networks; Memory; Object detection; Testing; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Vehicles Symposium Proceedings, 2014 IEEE
Conference_Location
Dearborn, MI
Type
conf
DOI
10.1109/IVS.2014.6856566
Filename
6856566
Link To Document