About the Project
The goal of this project is to develop a real-world testbed for an autonomous vehicle that will create real-world data to support the related research in the vehicle to everything (V2X), cybersecurity and autonomous control systems.
Autonomous vehicles in the road must face challenges of safety and security. They should quickly react on the foreseen accidences, and make the right decisions to protect passengers and pedestrians. In this background, the vehicle to everything (V2X) is a research topic to investigate communication between vehicles and other road infrastructure, as well as dig into their potentials to improve vehicle driving efficiency and general safety in road traffic. The additional information from the infrastructure can help the autonomous vehicles to have a good understanding of foreseen complicated real-world scenarios.
This project aims to deliver a real-world testbed (modular electric car platform) that:
- Arms and calibrates full perceptual sensors that a typical autonomous vehicle would need (e.g. 3D LiDAR, depth sensors, event cameras etc.).
- Installs typical communication protocols to vehicle (V2V), road infrastructure (V2I), pedestrian (V2P) and network/cloud(V2N/V2C).
- Equips efficient data collection and laundry framework.
The outcome of the project is supposed to support and achieve research of:
- Capturing a city-scale dataset for fully autonomous vehicles. This may include logs for perceptual sensor data, 3D geometric data of real-world streets/landmarks/pedestrians, as well as communication data for V2X.
- Creating a digital twin of real-world autonomous vehicles to provide a high-quality virtual simulation for perception, planning and control in autonomous driving.
- Developing a safe and scalable virtual environment for such connected and autonomous vehicles (CAV) to simulate the potential cyber-attacks and the possible defences, as well as find out how to best mitigate against ever-increasing cyber threats as connectivity increases.
The successful candidate will work closely with experts from IAAPS, as well as external collaborators from Cardiff University, University of Edinburgh and Imperial College London. At the end of this PhD project, the candidate will have acquired skills/techniques to plan and undertake independent research, and the candidate will be equipped to follow a variety of different postgraduate career paths.
The successful candidate is expected to have good knowledge of (1) sensor fusion, sensor calibration and synchronisation, as well as popular robotics simulator such as Gazebo; (2) popular large deep learning systems and their maths foundation; (3) coding skills in C/C++ and Python; (4) oral and academic writing skills.
The successful candidate should also have (or expect to achieve) a minimum of a UK Honours degree at 2.1 or above (or the equivalent) in Computer Science, Electronic Engineering or Mechanical Engineering. A master’s level qualification or publication would also be advantageous.
Non-UK applicants will also be required to have met the English language entry requirements of the University of Bath.
Enquiries and applications:
Formal applications should be made via the University of Bath’s online application form for a PhD in Computer Science (full-time).
More information about applying for a PhD at Bath may be found on our website.
Anticipated start date: 4 October 2021.
Based on your current searches we recommend the following search filters.
Based on your current search criteria we thought you might be interested in these.