Methods to Detect Road Features for Video-Based In-Vehicle Navigation Systems
- 12 February 2010
- journal article
- research article
- Published by Informa UK Limited in Journal of Intelligent Transportation Systems
- Vol. 14 (1), 13-26
- https://doi.org/10.1080/15472450903386005
Abstract
Understanding road features such as position and color of lane markings in a live video captured from a moving vehicle is essential in building video-based car navigation systems. In this article, the authors present a framework to detect road features in 2 difficult situations: (a) ambiguous road surface conditions (i.e., damaged roads and occluded lane markings caused by the presence of other vehicles on the road) and (b) poor illumination conditions (e.g., backlight, during sunset). Furthermore, to understand the lane number that a driver is driving on, the authors present a Bayesian network (BN) model, which is necessary to support more sophisticated navigation services for drivers such as recommending lane change at an appropriate time before turning left or right at the next intersection. In the proposed BN approach, evidence from (1) a computer vision engine (e.g., lane-color detection) and (2) a navigation database (e.g., the total number of lanes) was fused to more accurately decide the lane number. Extensive simulation results indicated that the proposed methods are both robust and effective in detecting road features for a video-based car navigation system.Keywords
This publication has 17 references indexed in Scilit:
- A New Measure of Travel Time Reliability for In-Vehicle Navigation SystemsJournal of Intelligent Transportation Systems, 2008
- Locating Intersections for Autonomous Vehicles: A Bayesian Network ApproachETRI Journal, 2007
- A High Accuracy Fuzzy Logic Based Map Matching Algorithm for Road TransportJournal of Intelligent Transportation Systems, 2006
- Video-Based Lane Estimation and Tracking for Driver Assistance: Survey, System, and EvaluationIEEE Transactions on Intelligent Transportation Systems, 2006
- Building Detection in Augmented Reality Based Navigation SystemLecture Notes in Computer Science, 2006
- Color-based road detection in urban traffic scenesIEEE Transactions on Intelligent Transportation Systems, 2004
- Road profile recognition for autonomous car navigation and navstar GPS supportIEEE Transactions on Aerospace and Electronic Systems, 2003
- Support vector machines for 3D object recognitionIeee Transactions On Pattern Analysis and Machine Intelligence, 1998
- SCARF: a color vision system that tracks roads and intersectionsIEEE Transactions on Robotics and Automation, 1993
- Recursive 3-D road and relative ego-state recognitionIeee Transactions On Pattern Analysis and Machine Intelligence, 1992