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Next-Generation Resilient City Lab
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A lab that models human behavior in disasters and explores next-generation cities and transportation.
AboutAbout the lab
Building next-generation cities resilient to disasters and future crises
The Next-Generation Resilient City Lab conducts research, development, and activities toward forming cities that incorporate next-generation transportation and urban systems and that are resilient to future crises such as disasters.
The lab was established in April 2023 by Associate Professor Junji Urata.
Using methods such as behavior models, optimal control theory, simulation, and data science, the lab discusses how to form disaster-resilient communities and how to provide mobility support that improves livability for people of all generations.
Research topics are decided through discussion after hearing students' wishes, with the lab presenting the topics and approaches it can offer.
Key terms
- Software 2.0
- A development approach in which the model is flexibly determined from collected data, rather than the conventional approach in which people design a model and fit it
- Behavior model
- A model that expresses mathematically which option people choose, for example when traveling or evacuating
- Bilevel optimization
- A computation that incorporates evaluation by a simulator as a lower-level problem in order to find effective plans and measures
NewsLab news
View More ↗ResearchResearch themes
The lab aims to advance transportation research and planning for non-routine situations, valuing fundamental theories and methods while incorporating new technology trends. Its research is built around “computational resilient mobility informatics,” covering simulation and modeling of behavior in disasters, system management, and the development of community living infrastructure.
*Illustrative imageSoftware 2.0-Oriented Traffic Demand Simulator
The lab is advancing data-driven development of a parallel integrated simulator that reproduces the traffic demand arising during the post-disaster recovery period, using the Software 2.0 approach in which the model is flexibly determined from collected data.
*Illustrative imageBehavior Models That Represent Interaction and Anticipation
Using behavior models, the lab represents how interaction with other people's behavior and outlook on future risk influence evacuation choices during a disaster. Approximate computation and quantum annealing are also incorporated into the development.
*Illustrative imageTraffic Management During Disaster Recovery
Using bilevel optimization with the recovery-period demand simulator as the lower-level problem, the lab searches for effective advance plans and measures, such as shelter locations, distribution center opening hours, and networks of temporary buses and ride-sharing.
*Illustrative imageSustainable Community Living Infrastructure
The lab studies how to keep bus services and home-visit medical care running even in areas with shrinking populations, as well as the balance between generation, storage, and consumption of renewable energy. It also works on the spatial formation of regions and cities, including the placement of EV charging stations.
MembersFaculty
Members of the Next-Generation Resilient City Lab consist of faculty, doctoral students, master's students, undergraduate students, and administrative staff.As of 2026
- Associate ProfessorJunji Urata
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Installation of the Resilient Tie Block track system in the GCT 2 tunnel. ( CM007, )” MTA Capital Construction Mega Projects / CC BY 2.0 (cropped)
- Software 2.0-Oriented Traffic Demand Simulator: “Aerial view of a traffic jam, 14th Street and the Mall, Washington, D.C, 04-1937 - NARA - 513342” 作者不詳 / Public domain (cropped)
- Behavior Models That Represent Interaction and Anticipation: “Community members rehearse evacuation routes 130904-M-GX379-006” Lance Cpl. Anne Henry / Public domain (cropped)
- Traffic Management During Disaster Recovery: “Temporary bus stop, Belfast - geograph.org.uk - 1761494” Albert Bridge / CC BY-SA 2.0 (cropped)
- Sustainable Community Living Infrastructure: “Infrastructure of a Rural Community - geograph.org.uk - 5480098” Alan Hughes / CC BY-SA 2.0 (cropped)
- Related lab (Urban Policy Science Lab): “A view of a sub urban area of Guatemala City in Guatemala” Jose Hernandez / CC BY-SA 2.0 (cropped)
- Related lab (Public Psychology Lab): “Malaysia Federal Highway Traffic Jam” Countryball mys123 / CC BY 4.0 (cropped)
- Related lab (Transportation Systems Science Lab): “Traffic congestion along Ontario Highway 401 in Pickering, Ontario, Canada” Robert Jack 啸风 Will / CC BY-SA 2.0 (cropped)
- Related lab (Satellite Geodesy Lab): “ICEYE SAR satellite Netherlands” Defensie Nederland / CC BY-SA 4.0 (cropped)
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