Navigating Innovations in Sensor Fusion and Digital Twins
This research project investigates the use of a sensor-driven digital twin as a validation and safety assessment framework for autonomous vehicle collision-prevention systems. The study focuses on how multi-sensor perception—combining camera-based computer vision, LiDAR distance sensing, and mmWave radar velocity measurement—can be reliably evaluated within a controlled virtual environment.
A YOLO-based perception model is used to detect objects from camera input, while LiDAR and radar data provide accurate spatial and velocity information. These sensor streams are fused to estimate Time-To-Collision (TTC) values, enabling early identification of collision risks. The digital twin acts as a continuously updated virtual representation of the physical sensing system, allowing system behaviour to be analysed safely and repeatably without the risks associated with real-world testing.
By positioning the digital twin as a core component rather than a visualisation tool, this research demonstrates how virtual validation can support robust safety analysis, sensor redundancy, and future scalability in autonomous driving systems.
Latest Posts
My Journey
I am Raffay Hassan, a final-year Computer Systems Engineering student based in London, with a strong research interest in autonomous systems, digital twins, and sensor fusion. My academic work focuses on building real-world, safety-critical systems that combine embedded hardware, AI-based perception, and simulation-driven validation. I have hands-on experience working with LiDAR–camera fusion, object detection pipelines such as YOLO, and autonomous driving simulation environments.
Alongside my studies, I have contributed to research at the London Digital Twin Research Centre, where I worked on autonomous driving datasets, perception benchmarking, and sensor calibration tools. My broader technical background spans embedded systems, FPGA design, signal processing, and IoT systems, with projects shortlisted for industrial showcases. Through this blog, I document my research journey, technical experiments, and insights into digital twin–based validation for autonomous and intelligent systems.
Connect With me on Linkedln
