As we look forward to the new Conference in Leeds within 2024, it is perhaps a good time to reflect on some of the main discussion points raised at the 2023 UKLRC in July this year. Hosted in Newcastle, it was a fantastic conference filled with expert knowledge, best practice and, above all, a profound sense of optimism for the future.  
Read more about the hottest topics of the Conference - Data and AI - within this special 'Tramways & Urban Transit' report by David Foster... 
Data, data analysis and artificial intelligence: they may not be 
the first things that come to mind when you think of light 
rail operations. However the UK Light Rail Conference proved how such topics, including the use of AI, are helping 
make the industry more efficient and safer. 
‘Big Data’ is becoming an important resource, as Andy Willetts, Principal Consultant for Amey Digital Consulting explained. ‘Big Data’ is generated throughthe interaction of mobile devices and phones with the internet and with each other.  
To give an idea of how much data is generated, Mr Willetts said that 188 million e-mails are sent globally every minute and that Facebook and YouTube receive one million and 4.5m hits every minute respectively. 
Mr Willets explained how ‘Big Data’ can be used by transport operators to “help determine the condition of in-service 
equipment to predict when maintenance should be performed” or could be vital to asset planning so that “rail planners can plan 
works efficiently and reduce overheads”. 
Chris Bax, Head of Transport Advisory at Amey Consulting, took the potential for use of ‘Big Data’ even further. He explained how every interaction with the mobile network generates a ‘data point’. From these data points, Mr Bax said that people can be located – anonymously and fully GDPR compliant – “in time and space” in order to create ‘people movement analytics’. This enables an overview of how the population moves around. 
Mr Bax explained how this data can be used to help build long term transport plans, to help improve timetabling or even to plan 
the movement of people through a station or interchange. 
Answering every problem? 
Some solutions seem like the answer to every problem. Tram-train is one. Or is it? 
Rob Carroll, Principal Engineer for Mott Macdonald argued: 
“It’s never going to be a solution for all your transport needs but it can meet a lot of different circumstances”. 
So, how do you find out? 
Mott Macdonald has developed Tram-Train Implementation Support (T-TSIT), a program that provides a quick assessment of the suitability of using tram-train. The program is fed with data about the proposed use and then makes a calculation, ranking the results ‘green’, ‘amber’ or ‘red’. For example, T-TSIT ranks both the Sheffield – Rotherham and Cardiff Core Valleys Line schemes green. 
However, T-TSIT has been used to assess 40 potential schemes, including many supplied by Network Rail’s Restoring Your Railway 
team, and found 17 that were not suitable for tram-train.  
Artificial intelligence is playing a greater role in data analysis. Mott Macdonald’s Maxime Stagnitto explained how its MM Rail Decarb system can be used to provide a detailed plan – including future-proofing– for electrification schemes long before ground is broken. 
“We calculate a fitness score using data and costs – anything you have to go through to electrify through obstacles,” he said, “that we run through the optimisation engine which is the AI bit.” 
What happens, said Mr Stagnitto, is akin to “natural selection”. 
Poor scoring candidates are taken out of the simulation. The best bits of high scoring candidates are merged together to create 
new candidates. 
“You create a new generation,” said Mr Stagnitto, “which goes through this loop over and over again, hundreds and thousands 
of times, until you converge at an optimal solution. Rather than going through trillions of candidates, it will only go through a few 
thousand to bring a result much faster.” 
The results generated by MM Rail Decarb can show whether bi-modes or battery power might be better than full electrification. 
It can also show where to place substations and the available capacity of the supply points and their distance from the railway. 
“This is going to be useful for transport bodies and all the people involved in decision making,” said Mr Stagnitto. “We see this as a support to decision makers either by guiding them in the right 
direction or providing supporting evidence for the appraisal process.” 
Rob Carroll, Principal Engineer, Light Rail for Mott MacDonald, questioned whether light-rail is really a solution for every need. The company has developed Tram-Train Implementation Support (T-TSIT), a program that provides a quick assessment of the suitability of using tram-train (Neil Pulling) 
More traditional routes for data analysis and data modelling are still required, particularly when it comes to safety. Mark Davis, General Manager of London Trams, couldn’t praise the Rail Safety & Standard Boards’ SafetyRisk Model highly enough when it came 
to studying the results of its new safety measures.  
The risk of driver fatigue has been reduced by 95% and the risk of a tram overturning is down by 76%. 
“That’s not a guess and me picking numbers out of the air,” he said. “That is actually using the risk model to determine how we’ve managed to reduce risk.” 
However, Mr Davis also explained how London Trams has used geo-targeting to get across important safety messages.  
Geotargeting, like the generation of ‘Big Data’, also uses the feedback generated by phones and mobile devices interacting with the internet and each other.  
London Trams needed to inform people about the hazards 
of not paying attention while crossing tramways after a rise in incidents of people being hit by trams or tram drivers making 
hazard brake applications as a result of inattentive car drivers. 
“We needed to do something to change the way we deliver the safety message,” he said. “We didn’t want to put a campaign on 
board a tram because that’s not targeting the people whom we needed to target. We needed the people who aren’t on the trams to keep their eyes about them.” 
A Be Tram Aware video was sent to people’s devices on social media when they were within 2km (1.2 miles) of the tramway, 
specifically targeting 16-30 year olds. 
Using geo-targeting meant that it got 
5.7m impressions. 
“It’s the first time we’ve done anything like that, targeting people who live and work around the tramway because we needed to 
get that message out,” Mr Davis said. 
Finally, Matt Johnston, Managing Director of Mainspring, explained how data can be used to measure the growth and confidence 
of the light rail industry. 
“How can we measure confidence globally?” he said. “What we measure are things like tram orders. The market continues 
to grow in terms of orders and options for vehicles. You can see almost record numbers for 2023 across the globe and that’s not 
unique to one particular continent. 
We are ordering more trams as a planet.” 
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