Smart traffic lights, flexible use of kerbsides, segregated driverless zones, and sat-navs learning through artificial intelligence are among the ideas shortlisted in a national competition to design roads fit for driverless cars.
Launched in January by the National Infrastructure Commission, with Highways England and Innovate UK, Roads for the Future sought ideas for preparing the UK’s road network for the growth of connected and autonomous vehicles (CAVs). The Commission received 81 entries. The five shortlisted companies going through to the competition’s final round are:
- Aecom | Examining how smart signals could tell drivers and vehicles the right speed to go to arrive at the next set of traffic lights just as they turn green, helping to cut congestion and ending polluting ‘stop-go’ driving. The concept will be tested using a simulation model of the A59 in York
- Arup | Looking at how kerbsides with fixed features such as double yellow lines, parking bays and bus stops could become more flexible, changing use according to the time of day and levels of demand to meet the most pressing needs. The team will select a typical high street in London to test their FlexKerbs model
- City Science| Based in Exeter, this entry examines how sections of existing roads could be dedicated to driverless cars, making it easier to manage any risk and integrate CAVs into the existing transport network
- Immense | Addressing how the latest artificial intelligence could be used to help sat-nav systems to ‘learn’ better routes to improve the directions given, so that both driven and driverless cars could change course to avoid congestion. Working with Oxfordshire County Council, the concept will be tested using simulations of four busy local roads: Abingdon Road, Thames Street, Oxpens Road, and Botley Road
- Leeds City Council | Examining how data generated from digitally connected cars could be used to improve traffic light systems, allowing highway authorities to better manage traffic on their roads and reduce tailbacks. The team will use models of roads across Leeds for testing
These five teams will now receive up to £30,000 each to test their ideas, with a £50,000 prize available for the overall winner, to be announced in the autumn. Separately, four other commended entries are being put in contact with leading figures across Government and industry to test their ideas.
The five shortlisted entries will now have three months to develop their ideas further, each working with a range of partner organisations to fully develop their proposals.
Bridget Rosewell, commissioner for the National Infrastructure Commission, explained the idea behind the competition: “We cannot afford to focus purely on the technology under the bonnet – we also have to consider how our roads will work to support new driverless cars from the moment they arrive.
“We wanted to see how the rules of the road, road design and traffic management could all be adapted to accommodate these new vehicles – and these five entries particularly demonstrated the exciting potential there is to make the best use of those we already have.”
Laurence Oakes-Ash, chief executive of shortlisted City Science, commented: “We are excited to be part of this national initiative. With strategic planning, these technologies provide a significant opportunity to enhance mobility within our cities and regions, improve safety and reduce costs for users. This project will enable us to develop infrastructure design frameworks that will help move CAVs beyond the trial phases and into real-world use.”
Plans for the Roads for the Future competition were announced as part of the Chancellor’s Budget statement in November 2017. This latest stage of the competition comes ahead of publication of the country’s first-ever National Infrastructure Assessment, which will make recommendations on the future shape of the UK road network, as well as issues including low-carbon energy, water resilience, digital technology and the future funding of major infrastructure.
An overall winner will be announced in the autumn and will receive a £50,000 prize.