Austria, Hungary, Slovenia set up middle Europe driverless region

The transport ministers of Austria, Hungary and Slovenia have signed an agreement to cooperate on the development of autonomous vehicles and e-mobility. The agreement advocates creating an Austrian-Hungarian-Slovenian driverless region to help develop and understand the latest mobility technologies and vehicles, according to a report in the Austrian newspaper Oberösterreichische Nachrichten. A test-track for autonomous vehicles stretching from Graz, Austria, to Zalaegerszeg in Hungary, via Maribor, Sl
April 3, 2018 Read time: 2 mins
The transport ministers of Austria, Hungary and Slovenia have signed an agreement to cooperate on the development of autonomous vehicles and e-mobility.


The agreement advocates creating an Austrian-Hungarian-Slovenian driverless region to help develop and understand the latest mobility technologies and vehicles, according to a report in the Austrian newspaper Oberösterreichische Nachrichten.

A test-track for autonomous vehicles stretching from Graz, Austria, to Zalaegerszeg in Hungary, via Maribor, Slovenia, may be constructed, the report noted.

The signing ceremony was also attended by European Transport Commissioner Violeta Bulc, the Slovenian member of the EU Commission.

Driverless cars and their impact on road design is being studied by the Vienna-based 2682 Austrian Institute of Technology through its interdisciplinary via-AUTONOM programme. Under scrutiny are new forms and technologies of road infrastructure that would facilitate safe and efficient automated road transport. It is studying how road infrastructure can optimise automated driving functions such as lane planning, proactive driving behaviour, pre-crash support and an “enhanced electronic horizon”.

In the world of big data, the institute if looking at which infrastructure and vehicle data are relevant to support autonomous driving, and how can they be combined. The project aims to investigate road infrastructure measures that have the highest effectiveness for the transition period with automated vehicles and non-automated road users.

Another objective is to identify where those measures must be implemented. To this end, via-AUTONOM develops a risk model to identify critical spots and road sections - intersections, roadwork zones and curves with limited sight distance – that may hold back increased use of automated vehicles.

For more information on companies in this article

Related Content

  • Call for papers extended for ASECAP Days 2025
    October 1, 2024
    Next year, motorway operators from across Europe will gather in Madrid from May 26-28 for the 52nd ASECAP Days event that will focus on the continuing shift to greener mobility.
    Read More
  • China: IRF Geneva supports the World Transport Convention 2018
    May 16, 2018
    IRF Geneva’s long-standing partnership and collaboration with China Highways and Transportation Society (CHTS) and with the Government of China will be at centre stage again this year. This will be seen at the World Transport Convention 2018 to be hosted in Beijing from 18th to 21st June. The 2017 edition of the World Transport Convention (WTC) was hosted by the China Association for Science and Technology (CAST) and organised by the China Highway & Transportation Society (CHTS). It also had the support o
    Read More
  • Europe’s green roads future
    June 17, 2020
    The European Commission’s Green Deal recognises that sustainable road infrastructure will keep Europe’s highways at the core of the continent's economy
    Read More
  • New approach needed in Europe to help improve motorcycle safety
    August 22, 2012
    The European Commission is proposing that part of its controversial new Anti-Tampering regulations for motorcycles should be re-written to prevent custom motorcycle builders from using long-forks. This is the latest in a series of requirements in the regulations to attracted criticisms from motorcycle manufacturers, dealers, safety campaigners and enthusiasts groups.
    Read More

Highlighted Content