Resilient and Trustworthy Robot and Vehicle Autonomy in Extreme and Competitive Environments

The iCPS Lab investigates resilient, stable, and intelligent autonomous systems that can operate reliably in challenging, uncertain, and competitive environments. Our research integrates machine learning, reinforcement learning, autonomous decision-making, and control to develop robotic systems that adapt to dynamic conditions while maintaining safe and stable behavior.

A key focus is robust autonomy under demanding operating conditions, where high speeds, uncertain dynamics, limited sensing, environmental disturbances, and interactions with other autonomous agents can challenge conventional control and planning methods. We investigate learning-enabled control and adaptive decision-making strategies that help robots respond to changing conditions, balance performance with stability, and make effective decisions in real time.

In competitive robotic settings, including autonomous racing as an application, we explore how intelligent control and strategic decision-making can improve maneuverability, trajectory tracking, and performance in the presence of competing agents. Across these applications, our goal is to bridge learning and control to advance autonomous systems that are not only capable and high-performing, but also resilient, predictable, and dependable in real-world deployment.

Publications:

• M. Elgouhary, and A. S. El-Wakeel, "Learning to Tune Pure Pursuit in Autonomous Racing: Joint Lookahead and Steering-Gain Control with PPO " IEEE Robotics and Automation Letters, 2026.

• M. Elgouhary, and A. S. El-Wakeel, "Robust Global-Local Behavior Arbitration via Continuous Command Fusion Under LiDAR Errors" IEEE Intelligent Vehicles Symposium, 2026.

part of " AI CRAFT: Artificial Intelligence Cybersecurity Readiness and Future Training", US DoD, DARPA. 24-26.

part of "Securing the Future: Fault Tolerance and Resilience in AI-Driven Autonomous Platforms through Chaos Engineering", New Frontiers in Research Fund-Exploration, CRCC, CA, 2025-2027.

Intelligent Cyber-Physical Systems for Autonomous Vehicles and Transportation Systems

At the ICPS Lab, our research focuses on advancing intelligent cyber-physical systems that integrate artificial intelligence, computer vision, adaptive perception, and connected vehicle technologies to support safer and smarter autonomous transportation. We investigate how autonomous vehicles and intelligent transportation infrastructure can perceive, understand, and respond to complex and dynamic road environments in real time. Building on our research, Sim2Real Dynamic Road Intersection Monitoring via Adaptive Vehicle BEV Transformation Model for the Internet of Vehicles, we explore simulation-to-real-world (Sim2Real) approaches and adaptive Bird’s-Eye View (BEV) transformation techniques that convert single-view vehicle camera observations into a unified top-down representation of road intersections. This approach aims to improve spatial awareness, traffic monitoring, and the detection of vehicles and other road users while addressing challenges associated with changing viewpoints and real-world operating conditions. By combining intelligent perception, adaptive scene representation, and Internet of Vehicles (IoV) connectivity, our research seeks to enable more reliable autonomous driving, improved intersection safety, and efficient, connected transportation systems.

Publications:

• R. Prajapati, and A. S. El-Wakeel "Sim2Real Dynamic Road Intersection Monitoring via Adaptive Vehicle BEV Transformation Model for the Internet of Vehicles", IEEE Internet of Things Journal. 2026

• D. Babalola, R. Prajapati and A. S. El-Wakeel "Real-Time Analysis of YOLOv12 and RT-DETR for Object Detection in Autonomous Driving" IEEE International Conference on Smart Mobility, Dubai, UAE, 2026.

• R. Prajapati, and A. S. El-Wakeel "Camera Perspective Transformation to Bird's Eye View via Spatial Transformer Model for Road Intersection Monitoring" , IEEE Smart Mobility Conference, Niagara Falls, ON, 2024.

part of " AI CRAFT: Artificial Intelligence Cybersecurity Readiness and Future Training", US DoD, DARPA. 24-26.

Recent & Selected Publications 

• M. Elgouhary, and A. S. El-Wakeel, "Learning to Tune Pure Pursuit in Autonomous Racing: Joint Lookahead and Steering-Gain Control with PPO " IEEE Robotics and Automation Letters, 2026.

• R. Prajapati, and A. S. El-Wakeel "Sim2Real Dynamic Road Intersection Monitoring via Adaptive Vehicle BEV Transformation Model for the Internet of Vehicles", IEEE Internet of Things Journal. 2026

• O. Agbo, M. Hefeida, and A. S. El-Wakeel "Hybrid-CNN Intrusion Detection Framework for CAN Networks in Connected and Autonomous Vehicles", IEEE Internet of Things Journal, 2025.

• M. Elgouhary, and A. S. El-Wakeel, "Robust Global-Local Behavior Arbitration via Continuous Command Fusion Under LiDAR Errors" IEEE Intelligent Vehicles Symposium, 2026.

• M. Elgouhary, and A. S. El-Wakeel, "Dynamic Lookahead Distance via Reinforcement Learning-Based Pure Pursuit for Autonomous Racing" IEEE Intelligent Vehicles Symposium, 2026.

• D. Babalola, R. Prajapati and A. S. El-Wakeel "Real-Time Analysis of YOLOv12 and RT-DETR for Object Detection in Autonomous Driving" IEEE International Conference on Smart Mobility, Dubai, UAE, 2026.

• M. Al Islam and A. S. El-Wakeel "Towards Context-Aware Autonomous Driving in Degraded Urban Environments Using LaneNet" IEEE International Conference on Smart Mobility, Dubai, UAE, 2026.

• M. Al Islam and A. S. El-Wakeel "Adversarial Robustness Analysis of Cloud-Assisted Autonomous Driving Systems" IEEE International Conference on Smart Mobility, Dubai, UAE, 2026.

• O. Agbo, M. Hefeida, and A. S. El-Wakeel "Optimized Deep Learning-based Intrusion Detection System for Connected Vehicles", SaT-CPS '25: Proceedings of the 2025 ACM Workshop on Secure and Trustworthy Cyber-physical Systems, ACM CODASPY, Pittsburgh, PA, 2025.

• R. Prajapati, and A. S. El-Wakeel "Camera Perspective Transformation to Bird's Eye View via Spatial Transformer Model for Road Intersection Monitoring" , IEEE Smart Mobility Conference, Niagara Falls, ON, 2024.

• R. Prajapati, and A. S. El-Wakeel "Cloud-based Federated Learning Framework for MRI Segmentation", IEEE International Conference on Communication, Denver, CO, 2024.

• S. Saleh, A. S. El-Wakeel, and A. Noureldin "5G-Enabled Vehicle Positioning using EKF With Dynamic Covariance Matrix Tuning,", IEEE CJECE, 2022. 

• A. Aboutaleb, A. S. El-Wakeel, H. Elghamrawy, and A. Noureldin "LiDAR/RISS/GNSS Dynamic Integration for Land Vehicle Robust Positioning in Challenging GNSS Environments" Remote Sensing, 2020.

• A. S. E-Wakeel*, A. Abdelrahman*, A. Noureldin, and H. S. Hassanein "Crowdsensing-Based Personalized Dynamic Route Planning for Smart Vehicles" IEEE Network, 2020. 

Best Paper Award:

• A. S. El-Wakeel, A. Noureldin, H. S. Hassanein and N. Zorba "Utilization of Wavelet Packet Sensor De-noising for Accurate Positioning in Intelligent Road Services", 14th International Wireless Communications and Mobile Computing Conference (IWCMC), Limassol, CY., 2018. "Best Paper Award" 

* Authors contributed equally. 

Italic font for the student Author.