A Traffic Modeler based app comes first in the Dubrovnik INSPIRE Hack

June 29, 2020

We are pleased to announce that the team which built a solution around Traffic Modeler, one of our visualisation tools, was awarded first place at the prestigious Dubrovnik INSPIRE Hackathon 2020

 

The demo created by the team focused on Františkovy Lázně, a small Czech town of about five thousand inhabitants. The results show that interactive traffic modelling can improve traffic planning in any city no matter its size. 

 

The demo was built in three steps. First, the team had to gather sufficient data on traffic network and traffic generators to be simulated. Next, the traffic model was calculated and imported into a spatial database for further processing by the Traffic Modeler. In the final step, different traffic scenarios were modeled and simulated using the tool's Application Programming Interface.

 

The demo competed against 11 other prototypes, and won. The jury awarded it first place because it best demonstrated the innovation potential along with impressive readiness level, sustainability and interoperability. The jury also said that Traffic Modelling from web browser, as the demo is officially known, combined different data sources better than competitor ideas.  

 

Commenting on the results, Daniel Beran, the team's leader, said: "We are extremely happy with the outcome. First place at the Inspire Hack is an excellent achievement. But we don't want to stop here. Our plan is to develop a web based Graphical User Interface similar to one already being used by the PoliVisu pilot city Pilsen. When ready, the app will allows users to calculate various traffic scenarios in near real time. They will only need a web browser and good internet connection to start experimenting."

 

 The Pilsen Traffic Model App

 

Congrats to Daniel and his team: Jan Blahník, Petr Trnka, Eva Podzimková, Zuzana Soukupová, Jan Sháněl, František Kolovský, Jan Šťastný, Jan Martolos, Karel Jedlička

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PoliVisu has received funding from the EU Horizon 2020 research and innovation programme under grant agreement No 769608.

 

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