We have created a demo of a digital twin

We are developing a simulator that incorporates various data related to transportation and urban mobility, visualizing and analyzing current challenges, and detecting future bottlenecks and potential issues by altering traffic flow and movement patterns. This simulator can be flexibly applied to multiple cities and regions, supporting the reproduction of mobility behaviors and the extraction of challenges based on urban characteristics. Furthermore, 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, we plan to link with edge AI to enable immediate decision-making and feedback control in locations close to the field. It is expected to be widely utilized as infrastructure that enables advanced decision-making support for urban transportation, regardless of whether it is public or private.

*The video is from around Meguro Station.