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Traffic and mobility analytics for developing road traffic

Published 31.1.2019

Being able to predict traffic jams and exceptions and provide information about them quickly benefits all road users. We researched and tested new methods of using artificial intelligence for traffic volume counts and predicting traffic jams and exceptions.

Towards an extensive base of basic information for versatile uses

As a part of the digitalisation project by the Finnish Transport Infrastructure Agency (FTIA, previously Finnish Transport Agency), we researched, tested and developed modern technological solutions for collecting traffic and mobility data in road, water and railway traffic. The goal was to create an extensive base of basic information and a snapshot that can be used for construction, maintenance, information services, redirecting traffic, distributing information and planning routes.

Crowdsourced data collection resulted in application for traffic information

In cooperation with volunteer road users and a partner, we developed and tested crowdsourced data collection with mobile devices. The result was the first version of a mobile device application (LiviApp) that contains the properties of the popular Traffic situation service by FTIA combined with the Feedback channel services by FTIA and ELY centres. The app will be launched during 2019.

Artificial intelligence, laser scanner and big data in the cloud

New data collection methods were also researched for improving safety in road tunnels. Based on a combination of data from video recording and laser scanner, artificial intelligence was taught to recognise normal traffic flow and any exceptions to it. Exceptions would create an automatic signal in traffic control that could limit traffic in the tunnel or close it completely as well as starting rescue operations when necessary. The research provided a good basis for using this technology more extensively in the road network.

During the digitalisation project, a mainly cloud-based processing and analysis environment for big data was constructed. This environment enables the controlled storage, processing and information services of real-time observation data and more static, large quantities of data, such as image and video data, in a cost-effective and scalable way.

Public transport services and open data for various needs

The project also developed and implemented a register and open data service for public transport state funding and key figures, and a more user-friendly Reittiopas in cooperation with HSL.

The public automatic identification system (AIS) data from marine traffic, vessel visits in harbours, railway traffic and configuration data and road traffic data from automatic measurement stations and road weather stations were published as open data in the Digitraffic service.

 

Inquiries:

Head of Unit Jari Myllärinen, FTIA information department, tel. +358 29 534 3636

Analytics Specialist Pekka Kinnunen, FTIA information department, tel. +358 29 534 3250

E-mail address format: [email protected]


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