Learning Driver Models for Automated Vehicles via Knowledge Sharing and Personalization

no code implementations • 31 Aug 2023 • Wissam Kontar, Xinzhi Zhong, Soyoung Ahn

This paper describes a framework for learning Automated Vehicles (AVs) driver models via knowledge sharing between vehicles and personalization.

Federated Learning Management

Bayesian Methods in Automated Vehicle's Car-following Uncertainties: Enabling Strategic Decision Making

no code implementations • 25 Oct 2022 • Wissam Kontar, Soyoung Ahn

This paper proposes a methodology to estimate uncertainty in automated vehicle (AV) dynamics in real time via Bayesian inference.

Bayesian Inference Decision Making

The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning

no code implementations • 9 Nov 2021 • Raed Kontar, Naichen Shi, Xubo Yue, Seokhyun Chung, Eunshin Byon, Mosharaf Chowdhury, Judy Jin, Wissam Kontar, Neda Masoud, Maher Noueihed, Chinedum E. Okwudire, Garvesh Raskutti, Romesh Saigal, Karandeep Singh, Zhisheng Ye

The Internet of Things (IoT) is on the verge of a major paradigm shift.

Federated Learning Meta-Learning +1

Predicting Vehicles' Longitudinal Trajectories and Lane Changes on Highway On-Ramps

no code implementations • 23 Aug 2021 • Nachuan Li, Riley Fischer, Wissam Kontar, Soyoung Ahn

Vehicles on highway on-ramps are one of the leading contributors to congestion.