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

   Betz, Johannes ; Zheng, Hongrui ; Liniger, Alexander ; Rosolia, Ugo ; Karle, Phillip ; Behl, Madhur ; Krovi, Venkat ; Mangharam, Rahul ( February 2022 , ArXivorg)

   The rising popularity of self-driving cars has led to the emergence of a new research field in the 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 vehicles 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 that are used in the fields of perception, planning and control as well as end-to-end learning. Further, with an increasing number of autonomous racing competitions, researchers now have access to a range of high performance platforms to test and evaluate their autonomy algorithms. This survey presents a comprehensive overview of the current autonomous racing platforms emphasizing both 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. 

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2. Location Spoofing Attacks on Autonomous Fleets

   https://doi.org/10.14722/vehiclesec.2023.23031  

   Yang, Jinghan ; Estornell, Andew ; Vorobeychik, Yevgeniy ( January 2023 , Symposium on Vehicles Security and Privacy)
3. On-the-Fly Decentralized Tasking of Autonomous Vehicles

   https://doi.org/10.1109/CDC40024.2019.9029554  

   Tadewos, Tadewos G. ; Shamgah, Laya ; Karimoddini, Ali ( December 2019 , 2019 IEEE 58th Conference on Decision and Control (CDC))
4. On Self-assessment of Proficiency of Autonomous Systems

   https://doi.org/10.1109/ICASSP.2019.8682730  

   Djuric, Petar M. ; Closas, Pau ( May 2019 , 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP))
5. On avoiding Moving Objects for indoor autonomous quadrotors

   https://doi.org/10.1109/COASE.2016.7743447  

   Shin, Donghyeok ; Kim, Junwhan ; Yu, Byunggu ; Jeong, Dong H. ( August 2016 , 2016 IEEE International Conference on Automation Science and Engineering (CASE),)

   A mini quadrotor can be used in many applications, such as indoor airborne surveillance, payload delivery, and warehouse monitoring. In these applications, vision-based autonomous navigation is one of the most interesting research topics because precise navigation can be implemented based on vision analysis. However, pixel-based vision analysis approaches require a high-powered computer, which is inappropriate to be attached to a small indoor quadrotor. This paper proposes a method called the Motion-vector-based Moving Objects Detection. This method detects and avoids obstacles using stereo motion vectors instead of individual pixels, thereby substantially reducing the data processing requirement. Although this method can also be used in the avoidance of stationary obstacles by taking into account the ego-motion of the quadrotor, this paper primarily focuses on providing our empirical verification on the real-time avoidance of moving objects. 

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