NDLI: Video-based lane estimation and tracking for driver assistance: survey, system, and evaluation

Please wait, while we are loading the content...

Video-based lane estimation and tracking for driver assistance: survey, system, and evaluation

Content Provider	IEEE Xplore Digital Library
Author	McCall, J.C. Trivedi, M.M.
Copyright Year	2000
Abstract	Driver-assistance systems that monitor driver intent, warn drivers of lane departures, or assist in vehicle guidance are all being actively considered. It is therefore important to take a critical look at key aspects of these systems, one of which is lane-position tracking. It is for these driver-assistance objectives that motivate the development of the novel "video-based lane estimation and tracking" (VioLET) system. The system is designed using steerable filters for robust and accurate lane-marking detection. Steerable filters provide an efficient method for detecting circular-reflector markings, solid-line markings, and segmented-line markings under varying lighting and road conditions. They help in providing robustness to complex shadowing, lighting changes from overpasses and tunnels, and road-surface variations. They are efficient for lane-marking extraction because by computing only three separable convolutions, we can extract a wide variety of lane markings. Curvature detection is made more robust by incorporating both visual cues (lane markings and lane texture) and vehicle-state information. The experiment design and evaluation of the VioLET system is shown using multiple quantitative metrics over a wide variety of test conditions on a large test path using a unique instrumented vehicle. A justification for the choice of metrics based on a previous study with human-factors applications as well as extensive ground-truth testing from different times of day, road conditions, weather, and driving scenarios is also presented. In order to design the VioLET system, an up-to-date and comprehensive analysis of the current state of the art in lane-detection research was first performed. In doing so, a comparison of a wide variety of methods, pointing out the similarities and differences between methods as well as when and where various methods are most useful, is presented
Sponsorship	IEEE Intelligent Transportation Systems Society
Starting Page	20
Ending Page	37
Page Count	18
File Size	1314481
File Format	PDF
ISSN	15249050
Volume Number	7
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-03-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robustness Filters Roads Data mining System testing Monitoring Vehicle driving Navigation Shadow mapping Vehicle detection performance metrics Active safety systems intelligent vehicles lane detection lane-departure warning machine vision
Content Type	Text
Resource Type	Article
Subject	Automotive Engineering Mechanical Engineering Computer Science Applications

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Video-based lane estimation and tracking for driver assistance: Survey, system, and evaluation

Integrated Lane and Vehicle Detection, Localization, and Tracking: A Synergistic Approach

PSO Algorithm Particle Filters for Improving the Performance of Lane Detection and Tracking Systems in Difficult Roads

Review on Lane Detection and Tracking Algorithms of Advanced Driver Assistance System

An improved pedestrian detection and Lane departure warning system for advanced driver assistance

Integrated Driver–Vehicle–Infrastructure Road Departure Warning Unit

A General Active-Learning Framework for On-Road Vehicle Recognition and Tracking

Lane Change Intent Analysis Using Robust Operators and Sparse Bayesian Learning

A Low-Cost Solution for an Integrated Multisensor Lane Departure Warning System

Video-based lane estimation and tracking for driver assistance: survey, system, and evaluation

Similar Documents

Video-based lane estimation and tracking for driver assistance: Survey, system, and evaluation

Integrated Lane and Vehicle Detection, Localization, and Tracking: A Synergistic Approach

PSO Algorithm Particle Filters for Improving the Performance of Lane Detection and Tracking Systems in Difficult Roads

Review on Lane Detection and Tracking Algorithms of Advanced Driver Assistance System

An improved pedestrian detection and Lane departure warning system for advanced driver assistance

Integrated Driver–Vehicle–Infrastructure Road Departure Warning Unit

A General Active-Learning Framework for On-Road Vehicle Recognition and Tracking

Lane Change Intent Analysis Using Robust Operators and Sparse Bayesian Learning

A Low-Cost Solution for an Integrated Multisensor Lane Departure Warning System

Video-based lane estimation and tracking for driver assistance: survey, system, and evaluation