Convergence of Communications, Control, and Machine Learning for Secure and Autonomous Vehicle Navigation

no code implementations • 5 Jul 2023 • Tengchan Zeng, Aidin Ferdowsi, Omid Semiari, Walid Saad, Choong Seon Hong

For both cases, solutions using the convergence of communication theory, control theory, and machine learning are proposed to enable effective and secure CAV navigation.

Autonomous Navigation Decision Making +2

Wireless-Enabled Asynchronous Federated Fourier Neural Network for Turbulence Prediction in Urban Air Mobility (UAM)

no code implementations • 26 Dec 2021 • Tengchan Zeng, Omid Semiari, Walid Saad, Mehdi Bennis

In this paper, to characterize the wireless connectivity performance for UAM, a spatial model is proposed.

Federated Learning

Federated Learning on the Road: Autonomous Controller Design for Connected and Autonomous Vehicles

no code implementations • 5 Feb 2021 • Tengchan Zeng, Omid Semiari, Mingzhe Chen, Walid Saad, Mehdi Bennis

The results also validate the feasibility of the contract-theoretic incentive mechanism and show that the proposed mechanism can improve the convergence speed of the DFP algorithm by 40% compared to the baselines.

Autonomous Vehicles Federated Learning

Federated Learning in the Sky: Joint Power Allocation and Scheduling with UAV Swarms

no code implementations • 19 Feb 2020 • Tengchan Zeng, Omid Semiari, Mohammad Mozaffari, Mingzhe Chen, Walid Saad, Mehdi Bennis

Unmanned aerial vehicle (UAV) swarms must exploit machine learning (ML) in order to execute various tasks ranging from coordinated trajectory planning to cooperative target recognition.

Federated Learning Scheduling +1