Launching in beta in Trainline’s voice app, personalised voice alerts provide customers with enhanced real-time updates on disruption to their journey.
Using natural language processing and machine-learning, Trainline’s team of data scientists and voice technology experts have created a rail disruption model, utilising data from train operators’ Twitter accounts, more advanced than anything currently available to UK train travellers.
Users simply give the app basic voice commands, such as ‘how is my commute doing?’ or ‘is this train running on time?’ to receive the alerts.
The new feature is another milestone in Trainline’s mission to create smarter rail and coach journeys globally with cutting-edge tech, using artificial intelligence and data science capabilities to optimise the travel experience.
Using natural language processing, the artificial intelligence analyses vast amounts of data collected from train operator Twitter feeds on rail disruptions.
The notification system works firstly by automatically classifying the importance of the message.
It then uses a second layer of contextual scoring, which calculates which stations the disruption is affecting, as well as how this will impact each individual train.
This information is used to build a picture of which lines, tracks and rail services are being disrupted.
Once the content and importance of the message has been determined, the artificial intelligence can automatically match this to individual journeys.
When a customer asks the Trainline voice app about their journey, they will be alerted about disruption, often before this data is available through the national rail data feeds.
The customer is even shown the history of the disruption, so they can see its scale, when it started, how it has unfolded and what is being done to fix it.
Dave Slocombe, senior director of product at Trainline, said “We’re proud to be launching another industry first.
“Through our voice app – designed to be used on the go – we can now offer customers faster and smarter updates on their journeys, helping them limit the impact of rail disruption.
“By creating an AI that can read information being shared on train operators’ Twitter feeds, we were able to overcome a key challenge in collecting data quickly from a variety of different sources.
“It’s another example of how Trainline is harnessing the power of AI, big data and voice tech to make travel a smoother experience for everyone.”