SafeDriveRL: Combining Non-cooperative Game Theory with Reinforcement Learning to Explore and Mitigate Human-based Uncertainty for Autonomous Vehicles-Reference-Cited by-同舟云学术

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SafeDriveRL: Combining Non-cooperative Game Theory with Reinforcement Learning to Explore and Mitigate Human-based Uncertainty for Autonomous Vehicles

Published:2024-04-15 Issue: Volume:28 Page:214-220
ISSN:
Container-title:Proceedings of the 19th International Symposium on Software Engineering for Adaptive and Self-Managing Systems
language:
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Author:

Chan Kenneth H.¹^ORCID,Zilberman Sol¹^ORCID,Polanco Nick¹^ORCID,Siegel Joshua E.¹^ORCID,Cheng Betty H. C.¹^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Michigan State University, East Lansing, Michigan, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3643915.3644089

Reference42 articles.

1. 2023. Ford's BlueCruise Ousts GM's Super Cruise as CR's Top-Rated Active Driving Assistance System. https://www.consumerreports.org/cars/car-safety/active-driving-assistance-systems-review-a2103632203/.

2. Deep Reinforcement Learning: A Brief Survey

3. Lejla Banjanovic-Mehmedovic, Edin Halilovic, Ivan Bosankic, Mehmed Kantardzic, and Suad Kasapovic. 2016. Autonomous vehicle-to-vehicle (v2v) decision making in roundabout using game theory. International journal of advanced computer science and applications 7, 8 (2016).

4. Brian Bell. 2022. Autonomous vehicles can be tricked into dangerous driving behavior. https://www.universityofcalifornia.edu/news/autonomous-vehicles-can-be-tricked-dangerous-driving-behavior.

5. Stefan Blomkvist. 2002. Persona-an overview. Retrieved November 22 (2002), 2004.

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