RoadMaPP – Smart Road & Street Maintenance, Pricing and Planning
Team: Nigel Davies (Lancaster University), John Polak (Imperial College London), Thomas Heinis (Imperial College London), Goran Strbac (Imperial College London), Mike Harding (Lancaster University).
Partners: Transport for London, Smart Streets Hub, InTouch Ltd, Connect Plus Services, Costain, UK Power Networks, JustPark
This project will involve development of three strands of work, led by teams from Lancaster and Imperial. The first strand involves identifying the trust issues involved in putting highways maintenance data into an IoT hub. A case study will be developed based around the M25 utilising an existing relationship with InTouch Ltd and Connect Plus Services. The second strand of work will build upon an existing framework for dynamic pricing in combined electric vehicle parking and charging markets. The third strand will develop the algorithms and tools necessary to clean, integrate and analyse the heterogeneous data coming from the large-scale sensor deployment of TfL as well as third parties. Key to enable trust in the results of the analysis is to design and deploy efficient and scalable algorithms for tracking the provenance of massive amounts of real-time events/data.
- Detailed understanding of the trust issues for a shared hub for maintenance activities in the Highways Sector including a concrete case study of real value to contractors in this sector.
- Development of a prototype trusted hub for shared maintenance information.
- Algorithms and analyses that will help TfL to plan road space and will be instrumental to the redesign of their road space planning tools.
- Analysis of the impact of different levels of shared user information on commercial, infrastructure performance, system and social outcomes and hence pinpoint key information assets.
- Investigation into the most significant barriers to information sharing in the relevant markets, both B2C and B2B and potential mitigations.
- Identification of potential vulnerabilities and failure modes for a comprehensively dynamically priced system and mitigations.