A new £1 million project has been launched to ensure the nation’s motorways can accommodate connected and autonomous vehicles.
The new project, a partnership involving Loughborough University and Highways England, will get underway immediately and is a crucial step towards truck platooning and the introduction of driverless autonomous vehicles.
While the project will look specifically at England’s motorway network, its will help to realise the government’s target of having self-driving vehicles on the UK’s roads by 2021. Named CAVIAR (Connected and Autonomous Vehicles: Infrastructure Appraisal Readiness), the new research project was announced as a winner in Highways England’s innovation and air quality competition last year.
And it comes at a vital time as British businesses seek to be at the forefront of emerging autonomous and connected vehicle technologies. Last year, SMMT’s Connected And Autonomous Vehicles Report highlighted the enormous potential of CAVs to the UK economy.
It concluded that CAVs could be worth £62 billion a year to the UK economy by 2030, creating 420,000 new jobs and more than 20,000 new jobs in UK automotive alone. It also estimated that CAV technology could save more than 3,900 lives between 2019 and 2030 and prevent around 47,000 serious accidents during the same time frame.
Furthermore, the report suggests that one in every five miles travelled by consumers in the UK could be autonomous by 2030.
Professor of Intelligent Transport Systems, Mohammed Quddus, the principal investigator on the project, said, “To date there is significant investment and advancement in Connected and Autonomous Vehicles.
“It is, however, not known whether existing road infrastructure, which was designed for conventional vehicles, is ready for the safe and efficient operations of CAVs. CAVIAR directly addresses this challenge.”
He added, “Although CAVs are designed with existing infrastructure in mind, ensuring they are safe to operate on motorways will require evaluating how road layouts affects their operational boundaries such as their ability to sense lanes and make appropriate decisions.”
As part of the project, researchers will look at operations at roadworks, merging and diverging sections (across lanes and at junctions) and lane markings to understand the challenges connected and autonomous vehicles (CAVs) may face. This will directly inform the development of commercial vehicle automonomous technology, such as that involved in vehicle platooning.
Real-world data from different lane configurations will be collected and fed into simulation models to calibrate and examine how CAVs respond to dynamic lane changes.
Digital maps representing dynamic lane configurations will be transmitted to CAVs in advance for informed routing decisions.
In terms of lane markings, the platform will be utilised to understand how environmental conditions affect a CAV’s ability to detect lane markings, such as snow, and low lighting – for example at night.
For merging and diverging scenarios, inconsistencies in geometric configurations will be appraised to examine whether CAVs are able to merge safely from the local road network (low speed) to the motorway network (high speed).