SRN IMPACT (InterModal Performance Analysis of Citizens Travel)

Lead Participant: TRAVELAI LTD

Abstract

TravelAi proposes SRN IMPACT (InterModal Performance Analysis of Citizen Travels) to digitize travel demand surveying. We propose a state-of-the-art, automatic, digital, travel-demand-survey tool that will allow Highways England (HE) to see the movement of users between the SRN, minor roads, plane, rail, bus and metro networks. Using a smartphone’s sensors and TravelAi deep learning informed mode detection IP to automatically crowdsource rich and accurate quantitative travel-behaviour data, deliver qualitative, personalised questionnaires, and adapt its operation to external event-based triggers. Our tool will be made available for local, regional and national authorities to use. Hertfordshire County Council (HCC) sit on a DfT working group seeking new digital technologies for use in solving transport issues. HCC is responsible for 634 sqm with an urban south and rural north. It is the only county to be dissected by 4 motorways (M25, M1, A1(M), M11) with 3 major airports on its borders (Luton, Heathrow, & Stansted) making Hertfordshire a critical transport hub for the south east. Rail connectivity includes the Thameslink service taking residents directly into central London, East Coast services & London Midland. HCC are an active partner and the first of many we will recruit as testers during the real world deployment. The anticipated benefits from addressing these themes include: • Improved connectivity within the SRN and rest of the regional road network • Data today, able to inform present and future operational decisions for CAVs and SRN • Improved network capacity utilisation • Improved and more personalised engagement with customers • Greater understanding of the interoperability of different transport modes • Data to inform MaaS implementation and service bundling • Operational resilience Why SRN IMPACT is value for money:- The DfT's National Travel Survey and Transport for London's Travel Demand Survey each survey 8,000 households for 1 week at costs of £2.5m and £1.5m, respectively. Up to 27% of the cost of these paper-based surveys are 1-to-1 interviews and data entry and cleaning. By automating data collection, our proposed solution stands to yield savings well in excess of its development cost within its first use in a large-scale deployment. HE will have a 2Y license to use the solution across the SRN e.g. in its own app or in Transport Focus-led surveys.

Lead Participant

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Participant

TRAVELAI LTD

Publications

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