AI in Transportation: Reflections from the Google, PA Consulting and DfT Hackathon

Last week, I attended the 谷歌 , PA Consulting , and Department for Transport (DfT), United Kingdom hackathon on AI in transportation, and spent the first day supporting hackathon attendees from the position of Chief Technologist at TRL Software . Talking about the birds and bees of data, where it comes from, what it looks like, how much, how often, quality, consistency, how clean and guidance towards what resources are available for doing more with transportation data. This event has been eye-opening and a testament to what AI can do in the transformation of the transport sector today.

The Hack Experience

The hackathon was a 2 day event which brought together a truly diverse group of people from their backgrounds, career journeys, specialisms, skills, interests and so had data scientists and software developers to transportation experts—all taking part. The mission? to see what kind of groundbreaking AI-driven ideas could be taken from group to concept to proof of concept addressing some of the most burning issues that face the transport sector today. The Google Town Hall was full, electric, the hum of collaboration and the buzz of creativity. From the get go in the morning the hack participants got stuck in, groups had met virtually before in person, ideas had been floated before the in person get go. Working the room and moving from team to team to answer questions, sound board ideas in respect to is this a mad idea to, has this been done before with transportation data, I was taken aback by the raw ingenuity and sheer determination of the players. (It was a room I very much enjoyed being in, despite the so many people)

The Role of AI in Transportation

I knew I was going to be thinking about the event that evening and for a few days following. What struck me the most was the lifting of the lid on the skills gap and what organisations are doing to stay match fit, you do not necessary see this from the outside and so very much helped build faith in a positive future. The shift from "we have some tech, what problems does it solve" and the "here is our solution and .. its powered by AI, dum dum der", to problem, solution, here is where [insert the very clever bid] and here is what we have achieved with AI - that is real, meaningful, not sales meh.

From my own observations of this hackathon, where I came in with a clear view that the role that AI plays is continuing to grow, the real potential to have a more central role in the future of transportation is just as true as it is for other domain areas. Here are a few critical areas where AI is set to have a deep impact:

• Traffic Management: We have already seen a number of AI-aided traffic management algorithms from academia, a few in the market place and results may vary. With goals of reducing stops and delays, consistent travel times and lower emissions, AI has a clear role in the future of urban mobility, its not longer just about the metal boxes with people in. Looking at some of the work with TRL Software and The Alan Turing Institute and the Turing Intern Network.
• Predictive Maintenance: The use of AI to predict when parts of the transportation infrastructure—such as roads, bridges, and railways—will need maintenance, a proactive rather than reactive approach, reducing network outages, expensive repairs and reducing downtime to ensure a smoother and safer transportation system. Nice.
• Public Transport: How you move, from where, your options, AI can clearly aid and sustain public transportation systems in the prediction, forecasting optimisation and scheduling. Thereby, more reliable and convenient services would be available to the users.
• Safety Enhancements: I am not even going to start calling out all of the has been done, could be done and future things.

A Week On: Reflections and Next Steps

A week on from this hackathon and I am still thinking about it. It was very pleasing to see the TRL team with their winning proposition and moving to the next round of judging at the DfT Transport AI strategy launch (which i really do hope to be at, please). Key to the hackathon was collaboration among technologists, data scientists, and folks who are experts in transportation. And the kind of hackathon also brought forth the requirement for transportation data, which needs to be not only open but also robust enough to lend itself to the creation of the kind of intelligent AI solutions required today. Here on, the road for AI in transportation will only get brighter. This will make AI a stronger means of tackling the modern challenges in transportation, as we collect more data and improve our algorithm. A focus should also be laid on ethical considerations, data privacy, and ensuring that all AI-driven solutions are fair and just.

So, to conclude, the hackathon supported by Google, PA Consulting, and DFT was simply brilliant, reflecting the way in which AI in transportation has surfaced its transformational power. As we move further, a transportation system becomes closer that is smart, safe, and efficient for all, based on the learnings and innovations realised while the hackathon was held.

It was an absolute pleasure to meet Chacasta Pritlove and the fabulous Katie Biltoo , thank you both for having me.