Autonomous vehicles

In the not too distant future, any of us could be sitting as passengers in a self-driving car – so safety and trustworthiness is paramount. At the University of Leicester our research concerns the quality of the software for autonomous vehicles from the model-based development and automated testing perspectives.

The DriverLeics Team develops algorithms for autonomous vehicles in complex urban scenarios which test the full capabilities of a simulated autonomous model against an autonomous agent. The challenges include accurate self-localisation, detection and classification of pedestrians against cyclists and vehicles and the safe completion of driving routes.

At the Royal Society Summer Science Exhibition the DriverLeics Team had a prime location on the main stage which featured a 1:8 scale track with autonomous vehicles plus:

  • A demo of a 1:8 self-driving car, in which you can control a pedestrian crossing the road
  • A chance to test your abilities against AI in difficult driving situations
  • An evolving self-driving AI trained by visitors

The DriveLeics Team

  • Jan Oliver Ringert, Lecturer/Team Leader 
  • Rayna Dimitrova, Lecturer
  • José Miguel Rojas, Lecturer 
  • Mohammad Mousavi, Professor 
  • Nervo Verdezoto‚Äč, Lecturer 
  • Syed Wali, MSc Student  
  • Ghalib Masood, MSc Student  
  • Diego Damasceno Nascimento, PhD Student  
  • Hugo Leonardo da Silva Araujo, PhD Student

Find out more on the DriverLeics website or contact driverleics@le.ac.uk

Audi Autonomous Driving Cup

A team of students from the University of Leicester recently participated in the Audi Autonomous Driving Cup in Ingolstadt, Germany.

Our team consisted of (l-r) Samuel Balco (Team Lead), Claudia Cauli (replacement for Long Chen), Zheheng Jiang, Ghalib Masood and Lei Tong. They were a diverse team of MSc and PhD students with academic degrees from China, Pakistan, the UK and Slovakia. 

The team's main interests and our current research are in the areas of formal verification, software engineering, computer vision, and machine learning. They are supported by institutional coaches with expertise in machine learning, software engineering (including validation and verification) and safety analysis and their applications in the automotive domain.