Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racing

Johannes Betz, Hongrui Zheng, Alexander Liniger, Ugo Rosolia, Phillip Karle, Madhur Behl, Venkat Krovi, Rahul Mangharam

Research output: Contribution to journalArticlepeer-review

176 Scopus citations

Abstract

The rising popularity of self-driving cars has led to the emergence of a new research field in recent years: Autonomous racing. Researchers are developing software and hardware for high-performance race vehicles which aim to operate autonomously on the edge of the vehicle's limits: High speeds, high accelerations, low reaction times, highly uncertain, dynamic, and adversarial environments. This paper represents the first holistic survey that covers the research in the field of autonomous racing. We focus on the field of autonomous racecars only and display the algorithms, methods, and approaches used in the areas of perception, planning, control, and end-to-end learning. Further, with an increasing number of autonomous racing competitions, researchers now have access to high-performance platforms to test and evaluate their autonomy algorithms. This survey presents a comprehensive overview of the current autonomous racing platforms, emphasizing the software-hardware co-evolution to the current stage. Finally, based on additional discussion with leading researchers in the field, we conclude with a summary of open research challenges that will guide future researchers in this field.

Original languageEnglish
Pages (from-to)458-488
Number of pages31
JournalIEEE Open Journal of Intelligent Transportation Systems
Volume3
DOIs
StatePublished - 2022
Externally publishedYes

Keywords

  • Autonomous systems
  • advanced driver assistance
  • autonomous vehicles
  • control
  • intelligent vehicles
  • path planning
  • simultaneous localization and mapping

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