Open AccessEffective vehicle-to-vehicle positioning method using monocular camera based on VLC
Author(s) -
Jing He,
Kuang Tang,
Jin Shi
Publication year - 2020
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.382482
Subject(s) - computer science , monocular , monocular vision , visible light communication , computer vision , artificial intelligence , position (finance) , kalman filter , positioning system , optics , light emitting diode , acoustics , physics , finance , economics , node (physics)
In this paper, an effective vehicle-to-vehicle (V2V) positioning method using monocular camera based on visible light communication (VLC) is proposed and experimentally demonstrated. As we all know, one of the key impacts of the accuracy of monocular positioning is the baseline which is always unfixed. To improve the accuracy of monocular positioning, the known length of taillights is used as the fixed baseline. Moreover, Kalman filter (KF) is applied to reduce random errors and enhance positioning accuracy for the vehicle position. In addition, to verify the feasibility of the method, a controllable mobile platform is built. By varying the distance between estimating vehicle and target vehicle, and the relative speeds of the two vehicles, the performance of the proposed positioning method based on VLC is investigated. The experimental results show that it can achieve centimeter level of accuracy using the proposed vehicle-to-vehicle VLC based positioning method.