Hamid Taghavifar

Assistant Professor

Concordia University

Canada

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Hamid Taghavifar is an Assistant Professor at Concordia University in Canada. His research focuses on autonomous driving, human-centric cyber-physical systems, and optimal vehicle control, as evidenced by his recent publications. His work includes advancements in reinforcement learning and control algorithms aimed at improving the reliability and performance of automated vehicle systems.

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2021

Collaborators (1)

Chongfeng Wei

The Queen's University Belfast

UNITED KINGDOM

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Hamid Taghavifar

Research Interests

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Articles (23)

No One at the Wheel? Advancing Reliability and Trust for the Autonomous Driving Era

Behaviorally-Aware Multi-Agent RL With Dynamic Optimization for Autonomous Driving

Event-Triggered Adaptive Optimal Control of Vehicular Platoons via Fuzzy ADP With Prescribed Performance

T3-ANFIS: Type-3 Adaptive Neuro-Fuzzy Inference System With a Noniterative Learning Algorithm

A finite-time path-tracking control algorithm for nonholonomic mobile robots with unknown dynamics and subject to wheel slippage/skid disturbances

Integrating deep reinforcement learning and social-behavioral cues: A new human-centric cyber-physical approach in automated vehicle decision-making

Gaussian Process With Automatic Relevance Determination Predictive Model for Energy Management of Electric Direct-Drive Wheels: Experimental Validation

A Constrained Fuzzy Control for Robotic Systems

A Fast Nonsingleton Type-3 Fuzzy Predictive Controller for Nonholonomic Robots Under Sensor and Actuator Faults and Measurement Errors

Fault Detection and Isolation in Wind Turbines: Type-3 Fuzzy Logic Systems and Adaptive Random Search Learning

Socially Intelligent Path-Planning for Autonomous Vehicles Using Type-2 Fuzzy Estimated Social Psychology Models

Socially Intelligent Reinforcement Learning for Optimal Automated Vehicle Control in Traffic Scenarios

Adaptive Synthesized Fault-Tolerant Autonomous Ground Vehicle Control With Guaranteed Performance and Saturated Input

A non‐linear fractional‐order type‐3 fuzzy control for enhanced path‐tracking performance of autonomous cars

Adaptive Robust Terminal Sliding Mode Control with Integral Backstepping Synthesized Method for Autonomous Ground Vehicle Control

Adaptive robust control algorithm for enhanced path-tracking performance of automated driving in critical scenarios

Robust AISMC-neural network observer-based control of high-speed autonomous vehicles with unknown dynamics

Optimal reinforcement learning and probabilistic-risk-based path planning and following of autonomous vehicles with obstacle avoidance

Input-output feedback linearization control of a tractor with n-trailers mechanism considering the path curvature

In-wheel motor vibration control for distributed-driven electric vehicles

Integrated control of vehicle stability by nonlinear observer-based exponential-like sliding mode neural network system

Adaptive immersion and invariance induced optimal robust control of unmanned surface vessels with structured/unstructured uncertainties

RISE-based integrated motion control of autonomous ground vehicles with asymptotic prescribed performance

Collaborators (1)

Chongfeng Wei

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