Pilsen (Czech Republic)

Pilot Description

Policy Challenge: The city of Pilsen recently announced its smart city policy, with smart mobility being one of its cornerstones. The city was ranked 2nd in the 2016 Open Data ranking state struggle to solve Plzeň is the high traffic during rush hours. The traffic situation is soon going to be worsened by multiple road construction works planned for the coming years by the city, the policy makers in Czechia, with the largest yearly progress among Czech cities. As in the most modern cities, one of the major problems that the Plzeň the national railway and organisation. In addition, various road closures will occur due to the utility provider’s maintenance of gas and water pipelines, sewerage, and phone, electricity, optical and other cables. These different organisations do not necessarily coordinate their interference into the city's road network, which then causes major traffic issues once several road constructions work occur at the same time.

 

The main challenge for the city decision makers is to achieve an efficient coordination and planning of multiple road closures caused by different organisations, thus avoiding major traffic problems caused by road works performed at the same time and in the same part of the city. The city representative would furthermore like to have a smart interactive tool that can be used to communicate the schedule of road works and the impact these will have on the city traffic to its citizens

 

Policy Stage: Pilsen pilots falls in the policy implementation phase of the policy making cycle. There are two types of road works that occur:

  • Road construction works that are planned long before, per different policies of several organisations (city, region, state, national railway, utility providers etc.), with start date dependent on various factors such as availability of financing, weather conditions, administrative approval process etc.

  • Road works and urgent maintenance caused by accidents and crisis situations, such as water or gas pipelines breach, electricity cables interruption, sewerage maintenance etc. These situations are solved at a short notice and might negatively impact the city traffic if they occur together with larger constructions works of the previous point

The challenge therefore is in the policy implementation phase in a need to better manage operations decisions and to ensure that operations decisions reflect real-time city traffic conditions.

 

Data to be Used:  in the city (start date, expected duration, location, road worksTraffic model of the city. Data about the planned visualisation developed by the OpenTransportNet project (link). Real-time and historical data from more than 1000 road sensors installed in the streets and at 90 crossroads with traffic lights (in Datex II format). The real-time data from sensors are sent every 90'' to the server located at the city's traffic management centre - a routable, INSPIRE compatible map of EU that allows routing and dynamic Visualisation of traffic volumes (provided by Plan4All)OpenTransportMap, Plzeň application being currently processed). https://www.waze.com/ccp Traffic information crowdsourced data provided by Waze within the Connected Cities Data Exchange programme (extent of road closure: complete, one lane etc.). WMS-t containing the traffic model data currently used for the advanced traffic model

 

Other Pilsen Case Studies

About Pilsen

Pilsen is a city in the Czech Republic.[2] About 90 kilometres (56 miles) west of Prague in western Bohemia, it is the fourth most populous city in the Czech Republic.

The city is known worldwide for Pilsner beer, created by Bavarian brewer Josef Groll there in 1842.

 

Source:Wikipedia

The city of Plzeň recently announced its smart city policy, with mobility as one of its cornerstone domains. The city was ranked 2nd in the 2016 Open Data ranking in Czechia, with the largest yearly progress among Czech cities. The proposed solution fits in Plzeň's smart city strategy built around an effort to make its services more aligned with and responsive to citizen needs and in line with the evidence-based policy making approach.

About PoliVisu Partner: Sprava Informacnich Technologii Mest

Správa Informačních Technologií města Plzně is a pilot city in the project. Key focus is connected with an online visualization of main road construction impacts to the traffic in city Pilsen with possibility to coordinate it.

Collaboration Actions:  

Crowdsourced data: Pilsen already has crowdsourcing mechanisms in place. PoliVisu will therefore focus on the analytics and visualisation of the available crowdsourced data to support evidence-based policy making.

Crowdsourcing problems and issues in the city: Plzni.to is a city crowdsourcing tool for issues reporting with more than 2000 issues reported at the moment by the Plzen citizens. These issues cover various areas, ranging from vandalism damages on benches, street lighting and public transport stops, overloaded and missing trash cans, wrecked abandoned cars at the streets, children playgrounds, trees and bushes to maintain, to potholes in the streets etc. PoliVisu will use its tools to analyse the crowdsourced data and to gain deeper insights on the problems reported by the citizens. These findings shall be used to support policy making and take policy measures to prevent the occurrence of these issues in the ‘riskiest’ areas of the city.

Waze crowdsourced traffic data: Plzeň currently initiated the registration process for the Waze Connected Cities Data Exchange programme (https://www.waze.com/ccp). The crowdsourced data provided by Waze (combined with the road sensor data) shall be used to further enrich and improve the traffic modelling capabilities of the PoliVisu solution.

 

Expected Outcome: An efficient coordination of road works in the city thanks to a traffic prediction tool that is based on automated real-time recalculation of the city's traffic model after a traffic issue is submitted through a city-manager dashboard.

Predicting roadwork impact for better planning coordination

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

 

This website represents the view of the PoliVisu project only.