Advances in Vision-Based Lane Detection: Algorithms, Integration, Assessment, and Perspectives on ACP-Based Parallel Vision
TLDR
In this paper, previous vision-based lane detection studies are reviewed in terms of three aspects, which are lane detection algorithms, integration, and evaluation methods, and a Computational experiment-based parallel lane detection framework is proposed.Abstract:
Lane detection is a fundamental aspect of most current advanced driver assistance systems U+0028 ADASs U+0029. A large number of existing results focus on the study of vision-based lane detection methods due to the extensive knowledge background and the low-cost of camera devices. In this paper, previous vision-based lane detection studies are reviewed in terms of three aspects, which are lane detection algorithms, integration, and evaluation methods. Next, considering the inevitable limitations that exist in the camera-based lane detection system, the system integration methodologies for constructing more robust detection systems are reviewed and analyzed. The integration methods are further divided into three levels, namely, algorithm, system, and sensor. Algorithm level combines different lane detection algorithms while system level integrates other object detection systems to comprehensively detect lane positions. Sensor level uses multi-modal sensors to build a robust lane recognition system. In view of the complexity of evaluating the detection system, and the lack of common evaluation procedure and uniform metrics in past studies, the existing evaluation methods and metrics are analyzed and classified to propose a better evaluation of the lane detection system. Next, a comparison of representative studies is performed. Finally, a discussion on the limitations of current lane detection systems and the future developing trends toward an Artificial Society, Computational experiment-based parallel lane detection framework is proposed.read more
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Mastering the game of Go with deep neural networks and tree search
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GOLD: a parallel real-time stereo vision system for generic obstacle and lane detection
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TL;DR: The generic obstacle and lane detection system (GOLD), a stereo vision-based hardware and software architecture to be used on moving vehicles to increment road safety, allows to detect both generic obstacles and the lane position in a structured environment at a rate of 10 Hz.
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Video-based lane estimation and tracking for driver assistance: survey, system, and evaluation
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Journal IssueDOI
Junior: The Stanford entry in the Urban Challenge
Michael Montemerlo,Jan Becker,Suhrid Bhat,Hendrik Dahlkamp,Dmitri A. Dolgov,Scott M. Ettinger,Dirk Haehnel,Tim Hilden,Gabe Hoffmann,Burkhard Huhnke,Doug Johnston,Stefan Klumpp,Dirk Langer,Anthony Levandowski,Jesse Levinson,Julien Marcil,David Orenstein,Johannes Paefgen,Isaac Penny,Anna Petrovskaya,Mike Pflueger,Ganymed Stanek,David Stavens,Antone Vogt,Sebastian Thrun +24 more
TL;DR: The architecture of Junior, a robotic vehicle capable of navigating urban environments autonomously, is presented, which successfully finished and won second place in the DARPA Urban Challenge, a robot competition organized by the U.S. Government.
Junior: The Stanford Entry in the Urban Challenge.
Michael Montemerlo,Jan Becker,Suhrid Bhat,Hendrik Dahlkamp,Dmitri A. Dolgov,Scott M. Ettinger,Dirk Hähnel,Tim Hilden,Gabe Hoffmann,Burkhard Huhnke,Doug Johnston,Stefan Klumpp,Dirk Langer,Anthony Levandowski,Jesse Levinson,Julien Marcil,David Orenstein,Johannes Paefgen,Isaac Penny,Anna Petrovskaya,Mike Pflueger,Ganymed Stanek,David Stavens,Antone Vogt,Sebastian Thrun +24 more
TL;DR: The architecture of Junior, a robotic vehicle capable of navigating urban environments autonomously, successfully finished and won second place in the DARPA Urban Challenge, a robot competition organized by the U.S. Government.