Transforming Infrastructure Through Digital Twins

Reports from the American Society of Civil Engineers over the last decade have indicated that Pennsylvania’s infrastructure, particularly its roads and transit systems, is aging and requires attention in order to improve mobility, economic growth, and equity.

A collaboration between Carnegie Mellon University (CMU) and Fujitsu, a global leader in technology solutions and services, is advancing digital twin technologies in southwestern Pennsylvania to address these challenges. The digital twin technologies, including sensors, data, software, and algorithms, are deployed to closely monitor, predict, and manage their physical counterparts using computing, artificial intelligence (AI), and sensing technologies. 

Department of Civil and Environmental Engineering professor Sean Qian has worked with Fujitsu Research to develop digital twin models since 2021, expanding their collaboration with the company in Pittsburgh in 2022. Recent support from the Pennsylvania Infrastructure Technology Alliance (PITA) has allowed their joint research to grow, particularly in making southwestern Pennsylvania’s methods of transportation safer, smarter, and more equitable. 

“The collaboration with Fujitsu enables enriching the digital-twin platform with a better understanding of human behavior and developing more real-world use cases,” Qian said. “The expertise of both teams are complementary. ”

“Fujitsu develops social digital twin technologies to tackle a wide range of complex societal challenges and build a more sustainable world. Our work with CMU draws on our respective strengths and expertise to reexamine persistent issues in transportation from both a planning and operations perspective,” said Daiki Masumoto, Fellow and Head of the Converging Technologies Laboratory of Fujitsu Research. “We’re very excited to see how this project can contribute to realizing safer and smarter mobility for people in Pennsylvania and driving new local economic opportunities.” 

"Our work with CMU draws on our respective strengths and expertise to reexamine persistent issues in transportation from both a planning and operations perspective"

Building on traditional mesoscopic transportation simulations, breakthrough sensing and AI technologies allow digital twins to model human behavior, traffic flow, mobility services, and infrastructure in unprecedented detail. Taking into account factors such as route choices, travel times, vehicle types, and tolling, the models built by Qian and his collaborators enable the simulation of any region, any community, in any scale, and at any given time. 

The result is a robust data set at the hands of regional stakeholders, such as the City of Pittsburgh and the Southwestern Pennsylvania Commission, that can be used to predict the impacts of transportation operations as well as inform public policy, capital investments, and infrastructure systems. The project team is actively engaging these entities to demonstrate the effectiveness and diverse uses of the technologies.

 “This work has potential to impact both the public and private sectors, as it could inform political decision-making processes and engage regional businesses,” says Qian. “Improving infrastructure can both stimulate the economy and improve the overall quality of life in southwestern Pennsylvania.”

While finding its roots in the Pittsburgh region, the technologies developed in this work are replicable worldwide. In fact, Qian and Fujitsu’s social digital twin models have already been successfully implemented in some European and Asian countries, and the team looks forward to bringing these sustainable and innovative technologies to more communities in the future.

The grant from PITA has strengthened the collaboration between Qian and Fujitsu as CMU’s relationship with the company continues to deepen. Fujitsu’s research space in Pittsburgh also employs graduates from Qian’s Mobility Data Analytics Center and continues to grow its Pittsburgh presence, highlighting the importance of nurturing the next generation of innovators for the future of academia, industry, and regional economic development.