Trajectory Tracking Control for Lane Change Maneuvers in Autonomous Vehicles

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

Abstract

This research advances autonomous vehicle capabilities by developing novel trajectory planning and control techniques for lane changes using free-driving and vehicle-following modes. This study addresses the critical challenge of enhancing lane change precision to minimize accident risks on highways. A quintic polynomial is used for trajectory generation, and a PID controller is employed for trajectory tracking, integrating collision prevention strategies for safety assurance. The contributions of this work include the development of an efficient control scheme that adapts to dynamic traffic conditions and improves the robustness of lane-changing maneuvers. The proposed approach significantly enhances the accuracy and reliability of autonomous lane changes, providing a pathway for safer autonomous driving in complex highway scenarios.

Original languageEnglish
Title of host publication2024 18th International Conference on Control, Automation, Robotics and Vision, ICARCV 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages891-896
Number of pages6
ISBN (Electronic)9798331518493
DOIs
StatePublished - 2024
Event18th International Conference on Control, Automation, Robotics and Vision, ICARCV 2024 - Dubai, United Arab Emirates
Duration: 12 Dec 202415 Dec 2024

Publication series

Name2024 18th International Conference on Control, Automation, Robotics and Vision, ICARCV 2024

Conference

Conference18th International Conference on Control, Automation, Robotics and Vision, ICARCV 2024
Country/TerritoryUnited Arab Emirates
CityDubai
Period12/12/2415/12/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

Keywords

  • Autonomous vehicles
  • lane change
  • trajectory generation and control

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Control and Optimization

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