<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-07-08T08:44:08Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/762F86F2-83AC-43E0-B986-B447164E2B7D" ns1:id="762F86F2-83AC-43E0-B986-B447164E2B7D"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/6AB6DBFA-E12A-4EA3-B9C5-79AE617F60F6" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/667E1602-BE33-4114-AF1B-94FF085E06A8" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/667E1602-BE33-4114-AF1B-94FF085E06A8" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2019-02-28T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/443EEB61-21CD-4CAC-B923-6681264C0507" ns1:rel="FUND" ns1:start="2018-03-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">133456</ns2:identifier></ns2:identifiers><ns2:title>Customer interchange intelligence</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Feasibility Studies</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>&amp;quot;Interchanges can be a major 'pain point' for passenger transport. Transport organisations currently have a limited view of the interchange activities of individual customers, and are therefore unable to improve their interchange experience at a reasonable cost.

This project's vision is to improve experiences in rail stations when customers interchange between different modes of transport (e.g. from rail to bus or car, or vice versa). The vision will be realised by Q Shy developing 'customer interchange intelligence' software and models with the support of VTEC and RDG. The software service will provide detailed insight of these interchanges and intelligent, personalised communication with customers before and during their interchange journey (e.g. a real-time mobile 'push notification' for service exceptions and disruptions, or an estimated interchange time).

The technological challenge is using real-time customer data and transport data, combined with complex algorithms, including machine learning, to deliver a better experience without investment in physical infrastructure. The nearest state-of-the-art technologies are:

* Transit mobile apps that provide real-time disruption updates (e.g. Google Maps, Citymapper)
* 'Big data' services that analyse mobile and WiFi network data to understand patterns in people's transport usage (e.g. O2 Smart Steps, TfL WiFi trial)

Neither of these technologies specifically address the interchange 'pain point', or support transport organisations with the detailed data needed to alleviate or remove pains. In the case of the 'mobile network big data' services, the location of an individual is imprecise, so the models cannot accurately determine their transport interchange movements.

Q Shy's service will allow it to exploit the exploding intelligent mobility market, expected to be worth &amp;pound;900b by 2025\. VTEC, and other transport organisations, will benefit from technology that helps to improve their stations and interchanges, and deliver more intelligent, personalised customer service.

This opportunity has been created because there is growing demand on the UK's transport system, however there are limits to the time and money that can be spent on infrastructure projects. It is therefore recognised that a transition to intelligent mobility (IM) is required to make transport systems more efficient, meet higher customer expectations, and reduce environmental impact.&amp;quot;</ns2:abstractText></ns2:project>