08.07.20
New £1m project to prepare UK motorways for self-driving vehicles
A new partnership between Loughborough University and Highways England will aim to prepare the UK’s motorways for self-driving vehicles.
The new £1m project will look into accommodating connected and autonomous vehicles (CAVs), with research into operations at roadworks, merging and diverging sections as well as lane markings, to anticipate the challenges these vehicles may face.
The CAVIAR (Connected and Autonomous Vehicles: Infrastructure Appraisal Readiness) project, was announced as a winner in Highway’s England’s innovation and air quality competition last year, and given a £1m Government fund to develop the project.
Road infrastructure and its complexities may be one of the things limiting the potential of CAVs ability to operate fully autonomously, as well as other factors including weather conditions, road marking detection, traffic and road conditions.
Professor of Intelligent Transport Systems, Mohammed Quddus, the principal investigator on the project, and also of ABCE, 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.
“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.”
Data from different lane configurations will be used to simulate how CAVs respond to dynamic lane changes and investigate whether they can safety navigate through configurations of construction zones.
The team from ABCE, led by Professor Quddus, also includes Dr Craig Morton, Dr Alkis Papadoulis, Nicolette Formosa, Cansu Masera and Jacky Man.
With main project objectives being to use infrastructure and vehicle to get relevant data, create centralised data integration architecture, build simulation models for failure scenarios, verify simulations with data and to appraise safety and motorway readiness for CAVs.
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