Phase 1 expects to fund 30 projects with up to £75,000, up to a total of £2m (US$2.5m). It is expected that a second phase will follow involving R&D contracts being awarded to businesses chosen from the successful Phase 1 applicants. Funding of between £500,000 and £1 million is expected to be allocated for each Phase 2 contract, in order to develop a prototype and undertake field testing for 12 months.
“Location data and technology will help improve transport services, enabling the efficient delivery of new networks and transport corridors,” says Lord True CBE, Minister of State at the Cabinet Office. “Location data helps connect people with the jobs they need, the goods and services they want, and the places they want to go. This competition will help position the UK as a global science superpower, and start to unlock £2 billion of economic value per year in our transport sector.”
“Data is key for innovation in transport to flourish,” says Rachel Maclean MP, Parliamentary Under Secretary of State at the Department for Transport. “Whether helping manage our transport networks, or rolling out connected autonomous vehicles, data is helping provide the new digital tools to change how we travel. I’m excited to see the winners of this competition and how they will make our journeys of the future easier, cleaner and more efficient.”
Dr Ian Campbell, executive chair, Innovate UK adds, “As the UK’s Innovation Agency, Innovate UK is tasked with delivering measurable economic and societal impact across the UK. I am delighted that we are delivering this potentially game-changing competition, cementing the UK’s reputation as a world leader in shaping the future of mobility. There is clear demand for innovation and we are utilising the proven Small Business Research Initiative (SBRI) process to bring together transport challenges and innovators in order to deliver novel solutions.”
Projects must demonstrate reasonable use of geospatial data and technology. Examples of this could include: earth observation and satellite-derived data; artificial intelligence / machine learning (AI/ML) algorithms applied to spatial datasets; Internet of Things (IoT) sensors capturing spatial information surveying, 3D laser scanning or spatial imaging; advanced geographic information system (GIS) analysis or geo-visualization and environment modelling.