Platform

Inspiration

Access on the UK rail network is a real challenge - around 14 million UK residents identify as disabled, and many others, such as anxious travellers, and people with luggage may need additional assistance in order to travel confidently.

Rail companies have both a legal obligation and a commercial incentive to maximise the accessibility of their networks. With passenger numbers falling on UK rail for the first time in years, the suppressed demand from disabled customers cannot be ignored.

Half of disabled passengers say they would travel more often if access was easier, opening up this untapped market. We want to support disabled customers to travel confidently around the rail network, and help rail companies maximise their potential.

What it does

Platform provides three key elements that the current system of station assistance does not address:

Reassurance: With thousands of customers every year not even receiving confirmation of their assistance, our app provides information that reassures customers, and lets them know they’re on the right track.

Personalisation: Customers currently have to resubmit their information every time they book assistance - Platform remembers their information and requirements, saving time for both them and railway staff.

Flexibility: Plans change, but the current booking system doesn’t allow changes to be made mid-journey. Our app enables customers to update their plans or requirements in real time, and communicate these with station staff on the go.

It currently enables customers to build a profile, containing their specific accessibility requirements, which is then stored. They can then send journey requests to station staff, letting them know they're on their way.

How we built it

Our product is a mobile application constructed using android-studio. The language used is Kotlin, and FireBase was also used in order to facilitate communication between the staff and customer apps.

Challenges we ran into

GPS tracking proved to be too challenging to incorporate in the time available, but we would like to incorporate this in a future development.

Accomplishments that we're proud of

We have developed an app that allows a customer profile to plan a journey and submit their requirements to a staff profile in real time - this is already a big step up from what is available now!

What we learned

There are a lot of variables to take into consideration when dealing with customers requiring assistance. Though we have included some options in our MVP, our discussions with the experts have shown that we will likely need to refine this over time - this is why the customer feedback element is so important.

As our users may have various impairments that impact their use of the app, we have to consider what adaptations we can include to ensure inclusivity - this is why we have included the voice command option in the journey planner as a start. We know there are many other things we can do, such as a large text option, and audio updates (e.g, the app will speak when a customer is approaching their station).

What's next for Platform

We have some wireframes to develop further which are shown in the presentation, and we have some longer-term pipeline developments as well:

Including station wayfinding in the app, potentially using bluetooth beacons or station scanning and image recognition. This would be particularly helpful for those with visual impairments, or anxious travellers.
We know that not all customers requiring assistance will be confident using technology. We would like to develop an SMS communication system as an alternative option, helping to bring additional benefits to customers who are less tech-savvy, and enable staff to create profiles on behalf of customers if they would like this option.
We would like to build an algorithm to help us prioritise customers during busy times (this may be a problem for busier stations such as King's Cross or Birmingham New Street) - for example, a customer on a through train will need assistance more quickly than one on a terminating train (as the terminating train will remain in the station for longer).
We can build on this with machine learning to predict busy periods, and use this to inform allocation of staff resources to assist customers. This could also be used to predict delays before they happen, and we can inform customers pro-actively about potential disruption, and their travel options.