We created a demo of a digital twin

We are developing a simulator that incorporates diverse data on traffic and urban mobility, visualizing and analyzing current challenges, while also detecting future bottlenecks and potential issues by varying traffic volume and flow patterns. This simulator can be flexibly applied to multiple cities and regions, supporting the reproduction of mobility behavior and extraction of challenges tailored to urban characteristics. Moreover, this analytical foundation is aimed at evolving into a digital twin that reflects the overall situation of the city in real-time, and in the future, it is expected to support immediate decision-making and feedback control close to the site in cooperation with edge AI. We envision a broad application as an infrastructure that enables advanced decision-making support for urban transportation, for both public and private sectors.

*The video is from the area around Meguro Station.