Skip to main content

Motorbike safety can be measured objectively, says AIT

The Austrian Institute of Technology (AIT) and TU Wien (Vienna University of Technology) has developed a motorcycle probe vehicle to better understand the causes of motorbike accidents. The vehicle was deployed as a measurement method to evaluate popular motorcycle routes in Austria’s capital. Peter Saleh, road safety expert at the AIT Center for Mobility Systems, says: “Our aim is to give those who operate roads the precise information they need in order to reduce the danger in these areas efficiently,
August 30, 2018 Read time: 2 mins
The 6625 Austrian Institute of Technology (AIT) and TU Wien (Vienna University of Technology) has developed a motorcycle probe vehicle to better understand the causes of motorbike accidents. The vehicle was deployed as a measurement method to evaluate popular motorcycle routes in Austria’s capital.


Peter Saleh, road safety expert at the AIT Center for Mobility Systems, says: “Our aim is to give those who operate roads the precise information they need in order to reduce the danger in these areas efficiently, sustainably and cost-effectively.”

The motorbike, a KTM 1290 Super Adventure, was equipped with high precision sensors and video systems. The side cases were packed with recording technology which documented the condition of the bike.

Test drives gathered data on vehicle dynamics, trajectory and routing. This was augmented with weather, traffic volume and route environment and then analysed through machine learning to reveal road sections which pose a risk for motorcyclists.

According to Saleh, every road section which was classed as dangerous - after being driven along and analysed - had been the site of serious accidents in the past.

“The AIT/TU Wien research team is therefore in a position to anticipate future accident trends and can assess motorcycle safety on a scientific basis, even before anything has happened,” Saleh adds.

For more information on companies in this article

Related Content

  • Ford Mobility: analytics aids transport proactivity
    April 2, 2020
    Ford Mobility has demonstrated how data analytics can help implement London's transport strategy in areas such as traffic re-timing and in eliminating all road fatalities (Vision Zero) by 2041.
  • Bringing V2I and V2V communications to workzone safety
    January 26, 2012
    Imran Hayee of the University of Minnesota Duluth's Department of Electrical and Computer Engineering talks about efforts to bring V2I and V2V communications into work zones. With USDOT backing and under the auspices of the ITS Joint Program Office Connected Vehicle Research (formerly IntelliDrive) research programme, M. Imran Hayee of the University of Minnesota Duluth's Department of Electrical and Computer Engineering along with team of his students, have been conducting research into the application of
  • AECOM-led consortium secures funding for CAV pilot scheme
    April 13, 2017
    An AECOM-led consortium has secured more than US$5.2 million (£4.2 million) of funding from Innovate UK and the Centre for Connected & Autonomous Vehicles (CCAV) to deliver a pilot scheme that could pave the way for the use of connected and autonomous vehicles to move people around airports, hospitals, business parks, shopping and tourist centres. The pilot project includes the design, development and testing of new autonomous and connected pods on-demand (PODs), culminating in on-road public trials at L
  • Indian state launches new road accident data management system
    July 28, 2015
    The Indian state of Himachal Pradesh has officially launched its first road accident data management system (RADMS) for the management, analysis and evaluation of road traffic accident data. Designed and developed by TRL, the UK’s Transport Research Laboratory, the new system streamlines and centralises the management of accident data, making it easier to identify and introduce measures to reduce the volume and severity of accidents. Hosted at the Himachal Pradesh State Data Centre in Shimla, the RADMS,