Our traffic systems have become complexity monsters that desperately need to be orchestrated in order to coordinate the large and steadily growing variety of actors fighting for limited space. At the same time, we are forced to commit to major changes in our traffic systems to fight the climate change.
Luckily, open and widely available digital twins would enable the use of existing traffic visualization, traffic simulation and traffic optimization techniques to make data- and evidence-based decisions. Unfortunately, capturing and properly modeling the mobility patterns of all citizens in a digital twin requires labor-intensive gathering, harmonization, and combination of a wide range of different data sets. For mid- to large-sized areas this may easily take more than 6-person-months – making this approach prohibitively expensive for smaller cities. This is especially troubling, since the tools for simulation, analysis and optimization are already available as open source – if only the traffic models and mobility data were available as well.
We want to make the benefits of those tools available for everyone by significantly reducing the effort to build and integrate traffic models and digital twins. Moreover, we plan to publish our tool chain for building digital twins of cities open source and join the openMobility interest group for a joint development with the existing community. To showcase the current state of development, we will present early results from our first speed zone case study in the city of Leonberg. Our toolchain is based on existing open source tools, like Eclipse SUMO and TAPAS, and we hope to contribute towards a comprehensive set tools for the public.