Feature-Based Lane Detection Algorithms for Track Following: A Comparative Study

Ahmed Hashem, Thomas Schlechter

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

1 Citation (Scopus)

Abstract

Autonomous driving has been gaining momentum in recent years and is today one of the hottest areas of research and development in the mobility sector. One of the basic tasks to cover in the field of autonomous driving is lane detection. Considering that lane keeping and controlled lane change are low level autonomy tasks, those tasks are essential to any project aiming to achieve a reasonable level of autonomous driving. As a students' playground, the University of Applied Sciences Upper Austria - along with its partners - is currently establishing a model car based future mobility race event. To make this happen, a ROS based model car is equipped with various known and newly to be developed algorithms enabling certain capabilities. Given the described topical context, in this paper two feature-based lane detection algorithms, namely Hough Line Transform algorithm and Sliding Window algorithm, are developed, tested and compared.

Original languageEnglish
Title of host publication2022 8th International Conference on Mechatronics and Robotics Engineering, ICMRE 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages169-173
Number of pages5
ISBN (Electronic)9781665483773
DOIs
Publication statusPublished - 2022
Event8th International Conference on Mechatronics and Robotics Engineering, ICMRE 2022 - Virtual, Munich, Germany
Duration: 10 Feb 202212 Feb 2022

Publication series

Name2022 8th International Conference on Mechatronics and Robotics Engineering, ICMRE 2022

Conference

Conference8th International Conference on Mechatronics and Robotics Engineering, ICMRE 2022
Country/TerritoryGermany
CityVirtual, Munich
Period10.02.202212.02.2022

Keywords

  • Future Mobility Cup
  • Hough Line Transform
  • Lane Detection
  • Sliding Window Algorithm

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