PhD Research Student
Amina is a PhD Research student in the Advanced Virtual Engineering Research Centre (AVRRC). She is working with Professor Roy Kalawsky, Professor Mohammed Quddus and Professor Wen-Hua Chen under the “Intelligent Mobility mini-CDT”. Her research is on developing a Reference Architecture for Resilient Autonomous Vehicle Systems.
Amina’s research focuses on various aspects of Intelligent Vehicles. She seeks to develop a resilient transport system architecture that can adapt and evolve to meet the needs of future automated transport systems and regulatory constraints. Also to define a reference architecture that can be executed to allow exploration of alternative architecture solutions by exploring techniques that have their foundations in a variety of technologies, including:
- Vehicle to Vehicle and Vehicle to Infrastructure communications (V2V & V2I)
- LIDAR systems
- Multi-sensor Fusion
- Systems Modelling
- Computer Vision
- Systems Architecture
She obtained a Master‘s degree in Computer vision and Image processing and a Bachelor’s Degree in Maths and Computer Science from Sidi Mohamed Ben Abdellah University in Fez, Morocco.
Around 90% of accidents are caused by human error. Designing vehicles, so that they can drive themselves without human interaction has been of growing interest for government and automotive companies. Autonomous vehicles could also change the face of the economy, infrastructure and even society in addition to transforming the automotive industry. Autonomous vehicles have the potential to provide further benefits beyond safety, increasing the capacity of road networks, reducing congestion and saving fuel. In order to tackle this, research on intelligent mobility systems and robotics have contributed to the numerous technological solutions.
In addition, new software tools are being developed by research communities. Although it might take many years for autonomous vehicles to be fully functional, safe and in use in public areas, there are still major advances required in the area of algorithms and new statistical references. In order to perfect autonomous systems, other factors need to be taken into account that would allow us to integrate crucial components such as sensors, vehicles to vehicle communications, vehicle to infrastructure communications.
These different systems will create a plethora of data and increased reliance on more interconnected systems known as System of systems. As the automobile industries tries to broaden their horizons and develop their products, the requirement to develop more efficient, intelligent and safe autonomous vehicles. An aspect of this project is to research and develop a resilient transport system architecture that can adapt and evolve to meet the needs of future automated transport systems and regulatory constraints. Another objective of the research is to define a reference architecture that can be executed to allow exploration of alternative architecture solutions.
In this project, we will create a functional architecture using low cost sensors with techniques for sensor fusion to achieve better perception of the environment, objects, and obstacle detection in various weather conditions. Two main goals in this project are based on a system of system perspective to create a framework which would be able to simulate the traffic and environment dynamic and also define a feasible strategy of communication for connected vehicles. Using these several techniques, the end goal is to provide an end to end simulation of the reference architecture and demonstrate resilient within the transport system architecture that can adapt and accommodate different automated transport systems.