UK motorways get £1m upgrade for self-driving cars
Loughborough University has teamed up with Highways England to pave the way for self-driving vehicles on the UK’s motorways.
This exciting new partnership, funded with £1 million, is focused on preparing the road infrastructure to accommodate connected and autonomous vehicles (CAVs). Research will explore how CAVs can navigate roadworks, merging and diverging sections, and lane markings to overcome potential challenges.
The project, known as CAVIAR (Connected and Autonomous Vehicles: Infrastructure Appraisal Readiness), was selected as a winner in Highway’s England’s innovation and air quality competition last year. With government backing, the team is now set to delve into the complexities of road infrastructure that may hinder the full autonomy of CAVs, along with other factors like weather conditions, road markings detection, traffic, and road conditions.
Professor Mohammed Quddus, an expert in Intelligent Transport Systems and the lead investigator on the project, shared his insights, saying: “While there have been significant investments and advancements in Connected and Autonomous Vehicles, it remains uncertain if our current road infrastructure, designed for traditional vehicles, is fully equipped to support the safe and efficient operations of CAVs.
“CAVIAR is designed to directly tackle this challenge by assessing how road layouts impact the operational capabilities of CAVs, including their ability to sense lanes and make informed decisions.”
The project will utilise data from various lane configurations to simulate how CAVs interact with dynamic lane changes and navigate through construction zones. The research team from ABCE, led by Professor Quddus, includes experts like Dr. Craig Morton, Dr. Alkis Papadoulis, Nicolette Formosa, Cansu Masera, and Jacky Man.
The primary objectives of the project include collecting relevant data from infrastructure and vehicles, developing a centralised data integration architecture, creating simulation models for failure scenarios, verifying simulations with data, and evaluating safety and motorway readiness for CAVs.