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Hybrid Tracker Based Optimal Path Tracking System of Autonomous Driving for Complex Road Environments

Hybrid Tracker Based Optimal Path Tracking System of Autonomous Driving for Complex Road Environments
Seo, EunbinLee, SeunggiShin, GwanjunYeo, HoyeongLim, YongseobChoi, Gyeungho
Issued Date
IEEE Access, v.9, pp.71763 - 71777
Author Keywords
RoadsStability analysisDeep learningAutonomous vehiclesGlobal Positioning SystemLane detectionComputational modelingIntelligent vehiclesvehicle drivingautonomous vehiclespath trackinglane detectiondriving stability
Road environmentTracking (position)Autonomous vehiclesDeep learningRoads and streetsAutonomous drivingComputational costsDriving stabilityDriving systemsFitting algorithmsKey technologiesProcessing algorithms
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 CCBY
Institute of Electrical and Electronics Engineers Inc.
Related Researcher
  • 임용섭 Lim, Yongseob
  • Research Interests Autonomous Vehicle and Aerial Robotic Systems and Control; Theory and Applications for Mechatronic Systems and Control; 자율 주행 및 비행 시스템 제어; 로봇공학 및 지능제어
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Appears in Collections:
Department of Interdisciplinary Studies Advanced Intelligent Mobility Research Group 1. Journal Articles
Department of Robotics and Mechatronics Engineering Autonomous Systems and Control Lab 1. Journal Articles


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