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Details of Grant 

EPSRC Reference: EP/F005156/1
Principal Investigator: Polak, Professor JW
Other Investigators:
Singh, Professor S Austin, Professor J
Researcher Co-Investigators:
Professor M Smith
Project Partners:
Department: Civil & Environmental Engineering
Organisation: Imperial College London
Scheme: Standard Research
Starts: 01 January 2008 Ends: 30 June 2011 Value (£): 1,442,820
EPSRC Research Topic Classifications:
Information & Knowledge Mgmt Intelligent & Expert Systems
Transport Ops & Management
EPSRC Industrial Sector Classifications:
Transport Systems and Vehicles
Related Grants:
Panel History:
Panel DatePanel NameOutcome
21 Mar 2007 Future Intelligent Transport Systems (FITS) (Eng) Announced
Summary on Grant Application Form
FREEFLOW aims to fundamentally change how we use transport data, by using it to generate transport intelligence. Currently we are collecting more (and better) data about our transport networks, such as journey times and the location of buses. We process data in different ways and then supply it to users / individual travellers and service suppliers as well as network operators and travel information providers. But our present techniques for handling data are not good enough to help us actively manage transport. Instead, we often just react to network problems. Both the public and those responsible for networks want new intelligence to help them make better decisions - instead of being told about a queue, drivers want to know how to avoid it and network managers want to know why it is there and how to reduce it. This is a challenge, even with the relatively small data volume today. But soon there will be many new sources of data and so there is a clear opportunity to actively fill a market gap, before we are overwhelmed with data. This is a global problem, so has great potential for the UK to exploit. And this is not just a transport problem / the military already have sharp awareness of situations their data implies and make critical decisions from it. FREEFLOW therefore fuses transport policy requirements of better services with innovation from outside transport, to generate transport intelligence for urban areas. We want to deliver services that users will really want to use and so dramatically improve how they travel / no just make small changes. We will look for new sources of data, such as from CCTV, to help services evolve. We aim to research how to use intelligent decision support to deliver market ready products. These will deliver policy outcomes of improved safety, reduced congestion and safeguarding the environment, and measure the changes we make through demonstrations in York and London. We aim to make a noticeable change that will stimulate a global market and make life easier for travellers too. Hence our vision is to deliver: Improving transport user decisions and performance, by turning data into intelligence
Key Findings
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Potential use in non-academic contexts
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Date Materialised
Sectors submitted by the Researcher
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Further Information:  
Organisation Website: http://www.imperial.ac.uk