Increasing MaaS adoption with real-time journey detection and delay refunds

Public description

The recent "The Future of Transport" report identified that modal and regional silos are a significant barrier in the UK's transport system. Mobility as a Service (MaaS) can help to break down these barriers and may also encourage a 'modal shift' away from cars. However, journeys on these platforms must be user-centric, seamless and accessible.

Modal's proposed idea is an innovative software service to help improve MaaS and increase its user adoption. Our lead/potential customer is Transport for West Midlands (TfWM) who are working towards the goal of delivering a comprehensive MaaS offering. The service could be integrated into a future Transport for West Midlands (TfWM) MaaS app, or other transit apps, and would include:

Real-time detection of train journeys completed by app users without any user interaction Automated delay refunds on one or more train operating companies in the TfWM region Standardised 'Open Transport' APIs to facilitate the sharing of customer account (ticket and journey) data

Whilst scope of this project is limited to train services, it will lay the groundwork for expansion to other modes of transport such as buses, trams and micro-mobility.

Real-time journey information captured by us will underpin new services on MaaS/transit mobile apps, making them more user-centric. In addition to automated delay refunds, examples include personalised disruption information, carbon tracking and loyalty schemes. Analysis of journey data could identify non-seamless interchanges or 'last mile' issues.

Sharing customer information via standardised APIs means MaaS operators can integrate more easily with numerous transport operators and third party technology providers (e.g. Modal). This will help MaaS operators to expand and improve, making their service more accessible. In Phase 1 of the project, our R&D plan is to:

Better understand the needs and requirements of MaaS operators and transit apps Confirm the commercial and market opportunity

Develop a beta iOS app and journey detection model to deliver a 'step change' to the reliability and accuracy of Modal's existing service

In Phase 2, we will develop a productionised service and run a large scale trial with TfWM and/or another organisation. The trial will form the basis of a case study, demonstrating that our technology increases the adoption of MaaS.

Modal has already deployed similar technology on a mobile app for train commuters, All Change. All Change is rated 4.8 stars on the App Store, and pre-Covid reached ~1,500 users on South Western Railway.