Hybrid Tracker Based Optimal Path Tracking System of Autonomous Driving for Complex Road Environments
Path tracking system plays a key technology in autonomous driving. The system should be driven accurately along the lane and be careful not to cause any inconvenience to passengers. To address such tasks, this research proposes hybrid tracker based optimal path tracking system. By applying a deep le...
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doaj-8b43cdb398fe4f58b8c5861df836e2582021-05-27T23:01:02ZengIEEEIEEE Access2169-35362021-01-019717637177710.1109/ACCESS.2021.30788499427137Hybrid Tracker Based Optimal Path Tracking System of Autonomous Driving for Complex Road EnvironmentsEunbin Seo0https://orcid.org/0000-0002-1552-7329Seunggi Lee1https://orcid.org/0000-0001-8956-8361Gwanjun Shin2https://orcid.org/0000-0002-3691-4707Hoyeong Yeo3Yongseob Lim4Gyeungho Choi5Daegu Gyeongbuk Institute of Science and Technology, Daegu, South KoreaDaegu Gyeongbuk Institute of Science and Technology, Daegu, South KoreaDaegu Gyeongbuk Institute of Science and Technology, Daegu, South KoreaDaegu Gyeongbuk Institute of Science and Technology, Daegu, South KoreaDepartment of Robotics Engineering, Daegu Gyeongbuk Institute of Science and Technology, Daegu, South KoreaDepartment of Interdisciplinary Engineering, Daegu Gyeognbuk Institute of Science and Technology, Daegu, South KoreaPath tracking system plays a key technology in autonomous driving. The system should be driven accurately along the lane and be careful not to cause any inconvenience to passengers. To address such tasks, this research proposes hybrid tracker based optimal path tracking system. By applying a deep learning based lane detection algorithm and a designated fast lane fitting algorithm, this research developed a lane processing algorithm that shows a match rate with actual lanes with minimal computational cost. In addition, three modified path tracking algorithms were designed using the GPS based path or the vision based path. In the driving system, a match rate for the correct ideal path does not necessarily represent driving stability. This research proposes hybrid tracker based optimal path tracking system by applying the concept of an observer that selects the optimal tracker appropriately in complex road environments. The driving stability has been studied in complex road environments such as straight road with multiple 3-way junctions, roundabouts, intersections, and tunnels. Consequently, the proposed system experimentally showed the high performance with consistent driving comfort by maintaining the vehicle within the lanes accurately even in the presence of high complexity of road conditions. Code will be available in <underline><uri>https://github.com/DGIST-ARTIV</uri></underline>.https://ieeexplore.ieee.org/document/9427137/Intelligent vehiclesvehicle drivingautonomous vehiclespath trackinglane detectiondriving stability |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Eunbin Seo Seunggi Lee Gwanjun Shin Hoyeong Yeo Yongseob Lim Gyeungho Choi |
spellingShingle |
Eunbin Seo Seunggi Lee Gwanjun Shin Hoyeong Yeo Yongseob Lim Gyeungho Choi Hybrid Tracker Based Optimal Path Tracking System of Autonomous Driving for Complex Road Environments IEEE Access Intelligent vehicles vehicle driving autonomous vehicles path tracking lane detection driving stability |
author_facet |
Eunbin Seo Seunggi Lee Gwanjun Shin Hoyeong Yeo Yongseob Lim Gyeungho Choi |
author_sort |
Eunbin Seo |
title |
Hybrid Tracker Based Optimal Path Tracking System of Autonomous Driving for Complex Road Environments |
title_short |
Hybrid Tracker Based Optimal Path Tracking System of Autonomous Driving for Complex Road Environments |
title_full |
Hybrid Tracker Based Optimal Path Tracking System of Autonomous Driving for Complex Road Environments |
title_fullStr |
Hybrid Tracker Based Optimal Path Tracking System of Autonomous Driving for Complex Road Environments |
title_full_unstemmed |
Hybrid Tracker Based Optimal Path Tracking System of Autonomous Driving for Complex Road Environments |
title_sort |
hybrid tracker based optimal path tracking system of autonomous driving for complex road environments |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2021-01-01 |
description |
Path tracking system plays a key technology in autonomous driving. The system should be driven accurately along the lane and be careful not to cause any inconvenience to passengers. To address such tasks, this research proposes hybrid tracker based optimal path tracking system. By applying a deep learning based lane detection algorithm and a designated fast lane fitting algorithm, this research developed a lane processing algorithm that shows a match rate with actual lanes with minimal computational cost. In addition, three modified path tracking algorithms were designed using the GPS based path or the vision based path. In the driving system, a match rate for the correct ideal path does not necessarily represent driving stability. This research proposes hybrid tracker based optimal path tracking system by applying the concept of an observer that selects the optimal tracker appropriately in complex road environments. The driving stability has been studied in complex road environments such as straight road with multiple 3-way junctions, roundabouts, intersections, and tunnels. Consequently, the proposed system experimentally showed the high performance with consistent driving comfort by maintaining the vehicle within the lanes accurately even in the presence of high complexity of road conditions. Code will be available in <underline><uri>https://github.com/DGIST-ARTIV</uri></underline>. |
topic |
Intelligent vehicles vehicle driving autonomous vehicles path tracking lane detection driving stability |
url |
https://ieeexplore.ieee.org/document/9427137/ |
work_keys_str_mv |
AT eunbinseo hybridtrackerbasedoptimalpathtrackingsystemofautonomousdrivingforcomplexroadenvironments AT seunggilee hybridtrackerbasedoptimalpathtrackingsystemofautonomousdrivingforcomplexroadenvironments AT gwanjunshin hybridtrackerbasedoptimalpathtrackingsystemofautonomousdrivingforcomplexroadenvironments AT hoyeongyeo hybridtrackerbasedoptimalpathtrackingsystemofautonomousdrivingforcomplexroadenvironments AT yongseoblim hybridtrackerbasedoptimalpathtrackingsystemofautonomousdrivingforcomplexroadenvironments AT gyeunghochoi hybridtrackerbasedoptimalpathtrackingsystemofautonomousdrivingforcomplexroadenvironments |
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