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Cooperative Autonomous Driving Systems

The commercialisation of highly autonomous Advanced Driver Assistance Systems (ADAS), and fully autonomous vehicles, is currently hindered by technical, regulatory, and economical obstacles. The key question is how to devise cost effective solutions for safe, secure, and reliable implementation of autonomous functions, and ultimately autonomous cars.

We aim to exploit new opportunities by enabling cooperation among agents, i.e. road users and infrastructures, and designing novel solutions that could help in addressing three key technical challenges for autonomous driving systems: positioning, perception, and control of autonomous vehicles.

A multidisciplinary challenge, we're focusing on two particular aspects:

  1. Designing ultra-low-latency communications and computing platforms as enablers of cooperative autonomous driving systems. This involves various aspects of distributed computing and network 5G architecture design for highly reliable and low latency communisations
  2. Designing frameworks for application in localisation, perception, and control of autonomous driving systems using a variety of techniques and tools from Information Theory, Estimation Theory, Artificial Intelligence (Machine Learning) and predictive control

We lead or work on several national and international collaborative research projects with our industry partners.

Projects

CARMA
Cloud-Assisted Real-Time Methods for Autonomy (Secure Cloud-based Distributed Control (SCDC) Systems for Connected Autonomous Cars)
Funder: EPSRC, JLR
Partners: University of Surrey, Transport Research Laboratory
L3Pilot
Piloting Automated Driving on European Roads
Funder: Horizon 2020 programme
Partners: Volkswagen AG, JLR, Daimler AG, Delphi
AutopleX
Funder: Innovate UK
Partners: Highways England, Inrix Uk Ltd, Ricardo UK Limited, Siemens Public Limited, West Midlands Combined Authority
PETRAS
Privacy, Ethics, Trust, Reliability, Acceptability and Security
Funder: EPSRC
Information fusion for a collaborative perception on local dynamic map systems with a network of connected autonomous cars; Ordnance Survey/EPSRC PhD Programme
Funder: Ordnance Survey

People

Professor of Connected Autonomous Vehicles
 
 
Research Fellow
 
 
Dr Omar Al-Jarrah
Research Fellow
 

 
Yi Lu
Research Assistant – in partnership with the Cyber Security Centre
 
   
Eduardo Arnold
PhD Candidate (Cooperative perception assistance for connected and autonomous vehicles)
 
   
Ugur Ilker Atmaca
PhD candidate supervised in partnership with Cyber Security Centre
(Security Optimisation of Intelligent Transportation Systems)
 
   
Liz James
EngD Candidate (Onboard and off board data platforms)
 
   

Luc LeMero
PhD Candidate (Self-Supervised Learning Methods in Autonomous Vehicles)

 


 
Stephane Role
PhD Candidate (Localisation and mapping for connected and autonomous vehicles)
 
   
Tariq Sheik
PhD candidate supervised in partnership with Cyber Security Centre
(Opportunistic Encryption for Intelligent Transportation Systems)