Overview
Development of a real-time risk awareness framework for autonomous Uncrewed Aircraft deployed to monitor Critical National Infrastructure from multiple “Drone-In-A-Box” installations, in proximity to multiple ground and air hazards
About this opportunity
We are seeking a highly motivated student to undertake a funded PhD project developing intelligent, risk-aware, Uncrewed Aircraft (UA) to enable scalable monitoring of Critical National Infrastructure (CNI) assets such as roads, railways and powerlines. This project builds on the recent success of the British Transport Police (BTP) in deploying a UK first Drone-In-A-Box capability by introducing high levels of autonomy to the UA allowing a single operator to manage a large number of aircraft at once, so-called Multiple Simultaneous Operation (MSO) .
MSO is not currently permitted due to the requirement that each UA have a dedicated Remote Pilot (RP) who is qualified to manage the risks that the flight poses to third parties, such as
- Failure of the aircraft leading to impact with a pedestrian or vehicle
- Failure of the aircraft leading to damage being caused to the CNI asset
- Collision with a low flying aircraft
This project will give the UA itself a high level of awareness of these risks, in real-time, allowing it to autonomously manage its flight appropriately to maintain an acceptable level of third-party risk exposure. Additionally, the identified risks will be presented to a human operator via an intuitive Human Machine Interface (HMI) giving them the ability to override certain restrictions if they deem it to be acceptable in the circumstances. For example, the aircraft may be permitted to fly closer to the public than normal if it is in support of locating a vulnerable person.
This risk awareness framework will include different quantification methodologies for each risk class and one or more of these will be developed in depth including robust verification and validation alongside real world trials to provide evidence to the Civil Aviation Authority (CAA) that MSO operations can be safely conducted.
During the first year you will be introduced to University’s existing police, CNI and CAA collaborators to fully understand the technical, operational and legal requirements and constraints related to MSO. In the second year and beyond, you will have access to both small scale and full-scale test facilities, along with experimental UA platforms to collect representative data. Additionally, access to real world operational environments and police/CNI equipment and staff will be available to facilitate your development.