Hello World — Meet the City Modelling Lab!
Introducing Arup’s City Modelling Lab
We’re a mixture of domain experts (in transport, energy, climate change, air quality, and economics), data scientists, software engineers and designers working to make cities better. We’ve created this blog to share our journey as we apply new technologies and bleeding-edge analytics to model our cities.
Our Mission
We are doing this work because we believe that city planning needs need to change radically. To decarbonise our cities and make them cleaner and more equitable, we cannot use the same tools and approaches that we have been using for the past few decades.
As we pioneer new, agent-based approaches to simulating our cities, we will share our experiences, ambitions, technical victories, the lessons we learn — and everything in between.
Meet the team
We work for Arup, an independent firm of designers, engineers, architects, planners, consultants and technical specialists working across every aspect of today’s built environment. Most of the core team are based in London, but we’re lucky to work on projects all across the globe.
Our core team includes, in alphabetical order:
Nick Bec. I’m the Business Lead for the City Modelling Lab. I’ve a background in maths, computer science, operational / operations research, management consulting, and capability development. This mostly means I do lots of things that enable delivering our projects and research, such as managing our recruitment pipeline and team planning. I’m responsible for developing our offer for clients, defining project scopes, and then managing the delivery of some of our projects.
Paola Bueno. I am a researcher and consultant with experience and passion for the analysis of social and distributional consequences of transport planning decisions. I lead the Social and Equity growth area and I have spent the last 10 years learning and exploring novel and better ways for measuring equity.
Gerry Casey. I’m interested in evidence based decision making and modelling for enlightenment, not post-justification. I’ve an academic background in agent-based modelling with a focus on sustainability and not boiling the planet.
Theodore Chatziioannou. I am a data scientist with a background in transport planning and economic appraisal. I am interested in leveraging diverse analytical techniques to inform decision-making and support sustainable urban and regional development.
Daumantas Dulius: I am a Data Scientist with a background in high-energy physics, I enjoy modelling complex systems and using simulations to solve some of our most pressing problems.
Michael Fitzmaurice. I’m a software engineer with a background in building and operating software in the retail, higher education, broadcast media and online betting & gaming industries. I have spent the past few years developing software to solve transport-related problems.
Val Ismaili: I’m a data scientist with a background in national-scale public transport network analysis and building pedestrian micro-simulations for large venues. Currently researching the inequality of exposure to air pollution.
Kasia Kozlowska. I’m a data scientist with a background in mathematics and mathematical physics. I enjoy graphs, optimisation problems and writing code.
Neil Montague. I’m a data scientist with a background as a transport planner and civil engineer. My work in recent years has focused on large-scale data analytics and visualisation that inform major sustainable transport projects. My particular interests include geospatial analysis, interactive data visualisation, and sharing insights from data analytics in an accessible way.
Bryn Pickering. I’m an energy systems modeller with an interest in how we navigate the interactions between renewable energy and different energy-consuming sectors as we transition to a carbon-neutral society. I enjoy developing open-source software, munging spatio-temporal data, and thinking up new ways to visualise insights from complex analyses.
Ana Rodríguez Coterón. I am a transport engineer with experience in data analytics, process automation and geospatial analysis. I have a passion for digital innovation and strategic approaches. I enjoy using data to inform the development of transport strategies and multi-modal transport schemes.
Divya Sharma. I am a data scientist with a background in supply chain management and analytics. I have a passion for utilising data to drive policy changes, with the recognition that the best solution is one that comes from interdisciplinary alignment. I am specifically interested in a systems approach to equitable, sustainable transport solutions.
Yuhao Sun. I am a Data Scientist with a background in intelligence manufacturing and data-driven approaches. I have been mainly working on Agent-Based Models for different transport projects. Beyond the ABMs, I am passionate about using data analytics and machine learning to deliver novel solutions to complex problems.
Panos Tsoleridis: I am a transportation planner with a background in disaggregate behavioural modelling. I am interested in uncovering aspects of individual behaviour and latent constraints, which would have an influence on mobility-related choices. My aim is to assign those behavioural rules to the agents and see how they interact within the system, but also to understand how the system itself will change in the long term as a result of those interactions.
Our goals
Arup’s shared values, like our firm’s name, are derived from the beliefs and convictions of our founder, the engineer and philosopher Sir Ove Arup. The City Modelling project embodies Arup’s aim to shape a better world by setting an ambitious target to model complex city systems from the ground up. This is a paradigm shift from how cities have historically been planned.
The Challenges
Reducing the climate impact of transportation and connecting people to jobs and education — are just some of the challenges that city officials, public agencies, community groups and private businesses are tackling today. To design any change in our cities, these stakeholders need evidence.
Modelling is a well-established approach to simulate future scenarios. But the world is a complicated place, and traditional models were built in an age of expensive compute and small data. Hence, they use low-resolution or aggregated inputs and simplified mechanisms.
This makes traditional models hard to interpret and interrogate. Real mechanisms and interactions, like people catching the 07.48 train from Manchester Piccadilly, are replaced with simplified headways or flows. Precise events like when a person leaves work are replaced with a three-hour peak period. Complex choices people make, like how to travel are replaced with simplified elasticities.
Worst of all, traditional modelling approaches do not consider the individual. People are unique in their behaviours, values, restrictions and needs. By designing cities for the average person — we are missing the opportunity to design cities for actual people.
What’s next
We want to improve the fidelity and confidence of models, to make city planning human-sized — and provide better information about the consequences of policy decisions and infrastructure changes.
[They] attacked everything in life with a mix of extraordinary genius and naive incompetence, and it was often difficult to tell which was which.
Douglas Adams
Want to collaborate? We are interested in working with cities, local governments, transport authorities, and developers who want to be part of this journey with us. We have applied our research and development of agent-based models to simulate transport scenarios, but we are looking for partners who want to work with us to explore planning for electric vehicle adoption, air quality assessments that assess pollution-exposure rates, or the impact of road pricing on city accessibility.
If you would like to explore these- or any other city planning problems, get in touch: citymodelling@arup.com
