Last month, Pilsen's Deputy for Transport and Environment, Michal Vozobule, talked to DNES, the second largest newspaper in the Czech Republic, about the project and how it's helping local policy makers to improve traffic in the city. Below is a translated version of the interview which appeared in print on 24 February 2020.
The PoliVisu project aims to gather relevant data and create analytical tools to support important policy decisions. Pilsen, along with Ghent in Belgium and Issy-les-Moulineax in France, is the third pilot city involved. The focus of the project is broad. It covers not only cars and public transport but also pedestrians and cyclists, as well as the parking system. “The results are important when deciding on future projects and their implementation. That is one of the reasons why this project is part of the Smart City of Pilsen, whose main goal is to improve the life of citizens in the West Bohemian metropolis,” said Michal Vozobule.
DNES: Why do you focus on transport?
M.V.: The transport is essential for urban life. Pilsen has already had a traffic model, but thanks to PoliVisu, it has been significantly refined and enriched with other functions. This will provide the city with valuable information that can be considered when making decisions, whether it's visualizing the impact of planned closures and traffic restrictions or identifying information on risky areas in terms of traffic and other minor offenses. A few months ago, international experts met with representatives of the city in Pilsen, discussing a total of 82 measures in eight areas, exploring their benefits and identifying the goals which Pilsen wants to achieve in the coming years. The project includes not only the creation of maps, but also the optimization of the political decision-making process and the transfer of examples of good practice from abroad.
DNES: What does the data show?
M.V.: As part of the application development, experts work with so-called big data, which they process into maps to clearly display the traffic situation. Data is collected from sensors located in the city, for example, induction loops installed in the city streets at crossroads. The planned outputs include the provision of data on real traffic in the city, its visualization and subsequent use for traffic dispatching or navigation applications. It is also about creating a model to predict the impact of closures and restrictions. Thus, when planning road works, it is possible to see a change in traffic intensity before they start, thanks to the interconnection with the traffic data model. This is important when deciding on the future projects and their implementation.
DNES: What else can the project make easier?
M.V.. Since we will have both current and historical traffic levels, it will be much easier to evaluate how a traffic measure has contributed to improving the traffic situation in the city. In addition, there will be another set of maps based on the combination of different data sources. These maps will combine traffic sensor data with municipal and state police data on traffic offences and traffic accidents. It will be possible to investigate where and what type of minor offenses occur. We will be able to identify locations where speeding or parking offenses are most frequent, but also problems with public order and the like. Based on this data, the city management can then design and implement effective solutions for the identified risk areas.
DNES: Could you give a specific example?
M.V.: For example, the Traffic Modeller application can model what is happening to traffic at various closures and restrictions using Superdio data based on the city traffic model. The Traffic Modeller does not require traffic specialists and basically anyone can use it. The map indicates which roads or lanes will be restricted or closed, when and to what extent, and the application will, within a few seconds, show where traffic from these sections will be transferred to. If we put all constructions or restrictions in a given year into the Traffic Modeller, we will see on the model how traffic will behave. It is then possible to move some constructions and deadlines to prevent traffic collapse.
DNES: How did you get involved in the project?
M.V.: PoliVisu is a follow up of the Open Transport Net (OTN) project which was financed from previous EU's CIP program supporting competitiveness and innovation. In 2017, a traffic map was developed by Pilsen, which visualized transport intensity in the city. This allowed us to better assess the impacts of large scale road construction works on the transport intensity and the extent of exhaustion of the transport capacity of city roads in Pilsen from May to November 2018. Within this period, a call for proposals was published by the European Commission. A Belgium company IS-practice was preparing a new proposal as a follow up project of OTN and asked us whether would like to be a pilot city for testing new technologies. Naturally we were interested because the new PoliVisu project offered us the opportunity to continue and improve our work on traffic visualization.
DNES: The City of Pilsen is one of three pilot cities testing new tools. Who exactly works on this project?
M.V.: Information technology administration of the city of Pilsen. Our IT specialists have preliminary data for defining the expected outputs and cooperate with technical partners on the development of applications. Several Czech companies and research organizations are represented in the PoliVisu project as technical partners, dealing with transport issues in the city of Pilsen. EDIP s.r.o. prepares data modeling above the street network, InnoConnect s.r.o. develops analytical maps with data from traffic detectors (induction loops), Plan4All z.s. association develops an application for traffic modeling. HELP SERVICE REMOTE SENSING company develops an instrument for metadata description.
DNES: Is there anything you would like to recommend to cities interested in participation in Horizon 2020 projects?
M.V.: Cities are facing similar problems. The H2020 projects can provide an experience on how to proceed or what to avoid or what know-how to use. And that is exactly the added value of the PoliVisu project. It enables us to share data, experiment with it via visualization to predict consequences. We are confident this will lead to better, sustainable policy decisions and to a more effective management of the city operations.