Scoping Study into Deriving Transport Benefits from Big Data and the Internet

Tender description

Big Data is already transforming the way we conduct science, deliver healthcare, improve performance, run cities and operate businesses. However, in the transport sector benefits exploitation is at a much lower level of maturity. Data from across the transport system, in particular from sensor connectivity, has the potential to create a truly integrated inter-modal transport system that maximises efficiency gains, improves asset management and enhances the customer experience. Data, analysis and integration underpin the effective delivery of a number of emerging and potentially transformative technological developments, i.e. Intelligent Transport Systems (ITS), Smart Cities, Mobility as a Service (MaaS), and Connected and Autonomous Vehicles (CAV). Based on what is happening in other sectors it would appear that there is great potential for deriving direct transport benefits, and wider societal benefits, from Big Data and the Internet of Things (IoT) particularly in our cities. However, in order to realise this potential, it is important for the DfT and the wider transport community to understand the likely data, data analytic and integration techniques, potential business models that can support an Open-by-Default data model, data access to enable their exploitation and learn from best practice from elsewhere. This specification sets out the Department for Transport’s (DfT) requirement for a contractor to deliver a scoping study that investigates the data, and potential enablers and barriers to derive tangible transport benefits from Big Data and IoT in smart cities. This work is to inform the future work programme, which may involve further research in the next financial year. The successful supplier must be able to demonstrate that their team and approach has the sufficient range and quality of skills to assess the evidence critically, draw meaningful conclusions and be able to complete the research this financial year. We welcome collaborative bids that include input from relevant specialists (e.g. academics and data practitioners) that add real value to the project.