London’s Traffic Operations Digital Twin: The 5-Minute Interview With Andy Emmonds

“I took on board some live journey time data using Neo4j in our very first part of the digital twin. We were able to build something really simple. It was that proof of concept that basically elevated us with the executive recommendation to take it to the next level,” says Andy Emmonds, Chief Transport Analyst, Transport for London.

We met up with Andy Emmonds over the summer at our London GraphSummit event, and we’re excited to share his graph story with you here. Andy is the Chief Transport Analyst with Transport for London. His team uses graph technology as the basis of a digital twin to achieve quicker identification of incidents on the road, which impacts other sections of the transportation network. Neo4j is much more capable than relational databases when handling this interconnected data, enabling faster and more effective interventions.

It’s a fascinating use case, and we invite you to learn more about his work and his graph journey below. Enjoy!

Tell us about yourself.

Andy Emmonds: I’m Andy Emmonds. I work for TFL [Transport for London]. I help manage the road space – by that I mean, make the road space operate 24/7. So our directorate basically operates the traffic signals.

I take the data from the network and transform that into business intelligence, hopefully in real time. Without a graph database, without the application that the Neo4j brings to my digital twin, I couldn’t think about actually providing that operational information. So yeah, Neo4j is working for me.

What are some surprising results you’ve seen from using Neo4j?

Andy Emmonds: The fact that I can basically make relationships. One of the problems we’ve always had is what’s the reaction to an incident on the road network? How does an incident evolve? What happens to the incident? How does the traffic reassign around that incident?

We had no insight or knowledge of even how to think about putting that together. Now, we’re actually building a decision support system that actually will incorporate all that capability. So it’s thanks to having the graph database that we can think about doing those clever things.

Do you have any advice for someone getting started with Neo4j?

Andy Emmonds: I would just say keep it simple. I mean, we started out with a very, very simple application. When COVID hit, we wanted to get an understanding of how long it might take an ambulance to travel from a hospital to The Nightingale Centre.

I took on board some live journey time data using Neo4j in our very first part of the digital twin. We were able to build something really simple. It was that proof of concept that basically elevated us with the executive recommendation to take it to the next level.

What do you think is in store for the future of graph technology?

Andy Emmonds: I think that, essentially, we can develop a smart city model. That’s got to be the ultimate goal. Can we run smart cities? I’ve worked on a component of that – how does the road network run? Do we do that as a satellite of digital twins?

I think it’s basically thinking about how we’re going to bring those digital twins together and make them talk the same language, so that everything is sort of seamless. People can move around, and understand at one minute you want to do some shopping, then you want to go on the transport network, and then you want to do something different, maybe you want to be entertained. You can make it all seamless. That, I think, would be a great vision for London.