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Researchers to develop social digital twin tech for smarter cities
The researchers are working with Fujitsu to develop a platform that delivers a broad set of solutions for a variety of social issues based on accurate simulations of the movements of people and vehicles.
Carnegie Mellon University researchers in the US are collaborating with Japanese technology company Fujitsu to develop social digital twin technology.
The researchers anticipate the technology will play an active role in improving efforts to ease congestion, positively influence travel behaviour, and ultimately help create safer, more sustainable cities in the future.
Digital twins in global communities
A social digital twin digitally reproduces the relationships and connections between people, goods, the economy and society to offer a simulation, prediction and decision-making environment for solving diverse and complex social issues.
This research is the first attempt between Fujitsu and CMU to explore future applications of social digital twins in global communities.
A project through CMU’s Mobility Analytics Centre (MAC) will leverage real-world data, including input of traffic regulations and the movement of vehicles, to evaluate the effectiveness of measures designed to dynamically estimate and control traffic flow.
Another project with CMU’s Computational Behaviour Lab in the School of Computer Science’s Robotics Institute will extend current capabilities in 3D modelling of pedestrians and forecasting their behaviour over time in urban environments. This technology can be used to monitor activity on streets and determine where issues or accidents may be taking place.
The researchers anticipate that the technology will play an active role in improving efforts to ease congestion, and positively influence travel behaviour
Fujitsu and CMU will draw on the findings of these projects to create foundational technologies for social digital twins that will simulate traffic networks and movement patterns of people in real-time. That work will build on the deployment of the researchers’ projects with CMU’s transportation research institute, Traffic21.
Within the project, Fujitsu and CMU will leverage converging technologies, advanced technologies that combine computer sciences and knowledge from the humanities and social sciences. These technologies aim to solve diverse and complex issues faced by cities working toward the realisation of a sustainable society.
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The researchers aim to develop a new platform that delivers a broad set of solutions for a variety of social issues based on highly accurate simulations of the movements of people and vehicles, which will help them visualise and predict future actions and possible risks based on human behaviour.
By using the newly developed social digital twin platform to analyse and predict the behaviour of people and movements of vehicles, the effects and potential risks of proposed interventions can be reflected in advance to optimise outcomes of urban planning and policy.
Fujitsu and CMU’s research will initially focus on developing advanced sensing technology to better understand people’s movements, improve behaviour forecasting through artificial intelligence, and create social digital twin models to simulate how people interact with goods, the economy and society.
Researchers will additionally continue their efforts to contribute to the realisation of safe and sustainable next-generation smart cities by promoting measures to mitigate pandemics
Researchers can use the digital models to test solutions to adjust traffic regulations and toll systems to improve traffic flow.
In addition to the analysis of traffic congestion and ways to deliver economic efficiency, Fujitsu and CMU will further leverage the social digital twin platform to promote the verification of detailed measures to solve environmental issues, including reduction of carbon dioxide emissions and improving urban transportation networks.
The researchers will additionally continue their efforts to contribute to the realisation of safe and sustainable next-generation smart cities by promoting measures to mitigate pandemics and ensure the flexible, efficient allocation of medical resources while driving economic growth.
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How can social digital twins improve urban traffic congestion management?What AI methods enhance behavior forecasting in social digital twin models?How do social digital twins simulate interactions between people and economy?In what ways can digital twins optimize pandemic response and medical resource allocation?How can digital twin technology contribute to reducing urban carbon emissions?AI and Machine LearningAnalyticsCarnegie Mellon UniversitycongestionConnectivity & Datadigital twinsFujitsumobilityRoad
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