Connected car testing goes live in Coventry

A project to create one of the world’s most advanced environments for connected and autonomous driving has entered its second phase of testing, with connected cars going on trial on public roads to prepare the UK’s road networks for self-driving cars.

The second phase of the UK CITE consortium will see Jaguar Land Rover trial a range of intelligent connected features such as emergency electronic brake light warning, emergency vehicle warning, and in-vehicle signage for road works warning and traffic condition warning.

The UK CITE project will create the UK’s first fully connected infrastructure, using a combination of wireless technologies, which can enable real-world testing in a safe and managed way. The project is worth a total of £7.1m including investment from the Government and Highways England.

“To realise the full benefit of self-driving cars, we need to understand the infrastructure that’s needed to support them,” said Colin Lee, Jaguar Land Rover V2X manager. “Connectivity not only takes us a step closer to making this a reality but it also creates the platform to bring a great array of connected safety features to our customers in the near future.”

Work by Transport for West Midlands and Coventry City Council enabled the installation of critical infrastructure on urban roads in advance of the installation of 35 of Siemens’ ESCoS road side units on the M40 and M42 motorways.

These units provide the technical platform for real-time data exchange between vehicles and traffic control equipment. Vodafone Group supported this phase of activity with the provision of 30 smartphones and network connectivity for infrastructure to vehicle communications.

In addition to on-road testing, simulation plays a key role in taking the project into its next phase. HORIBA MIRA is developing a simulation system to model the connected vehicles and Coventry University will be using the data from the live vehicle trials and scaling it into a larger virtual environment using simulation modelling.