Vehicle Detection in the Autonomous Vehicle Environment for Potential Collision Warning (CROSBI ID 698732)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Gluhaković, Mario ; Herceg, Marijan ; Popović, Miroslav ; Kovačević, Jelena
engleski
Vehicle Detection in the Autonomous Vehicle Environment for Potential Collision Warning
In this paper, a method for the vehicles detection in the surroundings of an autonomous vehicle and warnings of potential collision with them is presented. The method, which consists of two parts, is implemented in robot operating system (ROS). The first part is used to detect vehicles in an autonomous vehicle environment, in which, YOLO v2 algorithm, trained on a newly created set of images, is used. The YOLO v2 algorithm is configured to detect four classes of objects: a car, a van, a truck, and a bus. The second part of the proposed method is the ROS node for distance assessment. In particular, two ROS nodes for distance assessment are created ; one ROS node used for distance assessment in the Carla simulator, while the other ROS node is used for real-world distance assessment. The testing results of the proposed method show promising results.
object detection ; ROS ; YOLO v2 ; distance assessment ; Carla simulator ; collision ; autonomous vehicle
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Podaci o prilogu
178-183.
2020.
objavljeno
10.1109/ZINC50678.2020.9161791
Podaci o matičnoj publikaciji
2020 Zooming Innovation in Consumer Technologies Conference (ZINC)
Bjelica, Milan
Novi Sad: Institute of Electrical and Electronics Engineers (IEEE)
978-1-7281-8259-9
Podaci o skupu
Zooming Innovation in Consumer Technologies Conference (ZINC 2020)
predavanje
26.05.2020-27.05.2020
Novi Sad, Srbija