Search Results for author: Majid Moghadam

Found 4 papers, 3 papers with code

PID Optimization Using Lagrangian Mechanics

1 code implementation25 Sep 2023 Ethan Kou, Majid Moghadam

Creating a simulation of a system enables the tuning of control systems without the need for a physical system.

An End-to-end Deep Reinforcement Learning Approach for the Long-term Short-term Planning on the Frenet Space

1 code implementation26 Nov 2020 Majid Moghadam, Ali Alizadeh, Engin Tekin, Gabriel Hugh Elkaim

Tactical decision making and strategic motion planning for autonomous highway driving are challenging due to the complication of predicting other road users' behaviors, diversity of environments, and complexity of the traffic interactions.

Decision Making Motion Planning +4

Automated Lane Change Decision Making using Deep Reinforcement Learning in Dynamic and Uncertain Highway Environment

no code implementations18 Sep 2019 Ali Alizadeh, Majid Moghadam, Yunus Bicer, Nazim Kemal Ure, Ugur Yavas, Can Kurtulus

Autonomous lane changing is a critical feature for advanced autonomous driving systems, that involves several challenges such as uncertainty in other driver's behaviors and the trade-off between safety and agility.

Autonomous Driving Decision Making +2

A Hierarchical Architecture for Sequential Decision-Making in Autonomous Driving using Deep Reinforcement Learning

1 code implementation20 Jun 2019 Majid Moghadam, Gabriel Hugh Elkaim

Tactical decision making is a critical feature for advanced driving systems, that incorporates several challenges such as complexity of the uncertain environment and reliability of the autonomous system.

Autonomous Driving Decision Making +2

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