Leveraging Nash Equilibrium to Enhance Autonomous Driving

Leveraging Nash Equilibrium and Generative Adversarial Networks for Autonomous Driving

Autonomous driving in the context of Advanced Driver Assistance Systems (ADAS) and Highly Automated Driving (HAD) has evolved over the last couple of decades with an increasing significance towards Deep Learning principles from Artificial Intelligence. By combining this development with Nash Equilibrium, a concept from game theory, this paper discusses how we could establish and compute ground truths from vehicular videos used to train, test, and validate autonomous driving sensors and systems.

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Leveraging Nash Equilibrium and Generative Adversarial Networks for Autonomous Driving

By Naresh Neelakantan

Naresh Neelakantan is a senior architect (System Software) and product engineering services white papers provider from Sasken technologies limited.

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