Up to this point, urban planners have mostly used digital twins for operations, management, and maintenance of assets and services. But increasingly, urban planning has gone beyond these digital twin use cases and involves design and planning for now and the future (sustainability). For example, recent survey findings from U.S.-based IT firm Altair showed that digital twins help 92% of organizations with their sustainability goals.
Having a digital replica of city infrastructure allows for simulations, scenario assessments, and design optimization without the risk of real-world mistakes. By 2030, ABI Research expects cities to save more than US$282 billion annually by using digital twin software.
Digital Twin Models for Urban Planning
The three core models of urban digital twins are 3D modeling, physics modeling, and dynamic modeling.
3D Modeling of the Static Built Environment
As an integral aspect of urban planning, 3D modeling of the built city environment using a digital win allows for the creation of accurate geospatial models of various physical assets in a city. Some of those assets may include buildings, roads, and green spaces. This application lets city planners decide what spatial dimensions and environmental characteristics are optimal for new infrastructure. Light Detection and Ranging (LiDAR), satellite imagery, and mapping resources are important technologies to capture the necessary data used in the simulation.
With physics-based 3D modeling, engineers experiment with the following factors:
- Physical properties related to materials (concrete walls, trees, water areas, etc.)
- Electromagnetics like optics and photonics
- Fluid flow
- Noise and acoustics
- Thermal propagation
In an urban application, physics simulation typically refers to flood water levels, in-building airflow, the spreading of pollution, energy flow and transfer, city streetlights, and telecommunications networks. These digital twin use cases rely on mathematical formulas and Artificial Intelligence (AI) to model physics and to discover which characteristics are altered over time.
The third and final component of urban digital twins is the dynamic modeling of vehicle and pedestrian traffic. Common use cases involve evacuation simulations and traffic flow models that ensure safe and smooth mobility within a city. Using Internet of Things (IoT) sensors, crime and accident levels can also be modeled statistically. Indeed, digital twins can make the future city a lot safer to live in for the 80% of the world population expected to reside in urban areas by 2050.
Solving Urban Design Challenges with Virtual Prototyping and Scenario Simulation
Already being deployed in industries like energy, utilities, and manufacturing, virtual prototyping and scenario simulation gives urban planners the chance to address design issues before deploying or implementing anything. For example, a city may have a carbon emissions level target in mind and can use the digital twin to develop urban designs, strategies, and regulations to meet that target. Basically, it allows for trial and error without the need for any significant investments.
Generative Design Automates Urban Planning
In generative design, you tell the AI-supported software what criteria you want and provide several 3D models that meet your expectations. After that, the designs can be refined even further, with the help of Machine Learning (ML). The program gets to know exactly what you want and helps users create the ideal model. For the context of building a smart city, generative design can automate the design process of network infrastructure, surveillance cameras, streetlights, and the geometry of buildings.
To further understand how urban digital twins can be used, let’s take a look at a few case studies.
Urban Digital Twin Case Study #1: Virtual Singapore
Dassault Systèmes, a leader in the simulation and modeling of industrial systems, built a virtual version of the city of Singapore in 2018 to improve smart city planning. For example, urban planners could play around with energy consumption levels, opening shop hours based on passersby, skyscraper airflows, traffic light management, and wireless network expansion. Other use cases include crowd dispersion simulation for emergency procedures, planning for gray and green urban infrastructure, creating new analytical applications and better architectural decision-making.
To read about 15 other urban digital twin case studies, download the report: Urban Planning and Digital Twins
Urban Digital Twin Case Study #2: Paris Streetlights and CCTV
French-based Siradel co-designed the smart lighting and wireless Closed-Circuit Television (CCTV) in Paris by collecting data from various points. The approach required the simulation of the following three criteria:
- Light sources
- CCTV fixed camera network Field of View (FoV)
- 5 Gigahertz (GHz) Wi-Fi-based mesh wireless connectivity between lampposts
Involving 148 cameras on 116 poles, this project resulted in the maximization of coverage in a more cost-effective manner.
Urban Digital Twin Case Study #3: City of York Traffic Flow Management
The very first real-time transport model used for urban traffic planning was implemented by the northern England city of York—using PTV Group’s traffic modeling software Optima. This York Optima model utilizes 100 live traffic flow sensors, more than 100 live signal controllers, live speed data from TomTom, and roadworks information. PTV Optima lets city planners test various scenarios for the short, medium, and long-term future pertaining to traffic flow and emissions (making the future city greener). PTV’s solutions facilitate a more anticipatory approach to scheming urban transportation networks.
Can’t Talk about Designing Future Cities without Mentioning Digital Twins
Smart cities go hand-in-hand with urban digital twins. The two are inherently intertwined, as the future of urban planning is about making our lives easier and safer in an environmentally-friendly way. The simulation software that comes with digital twin technology lets urban planners tailor their designs and strategies before making any permanent actions. Often, what seems like a great idea doesn’t come to fruition. Having a virtual replica of the city—and all the data that come with it—allows for definitive answers to future city designs and removes all the guesswork.
If you’re interested in learning more about using digital twins for urban planning, download ABI Research’s Urban Planning and Digital Twins research report. This report is part of the company’s Smart Urban Infrastructure Research Service.