A9 Safety Group wins prestigious road safety award

The A9 Safety Group in the UK has won the CIHT John Smart Road Safety Award, for a range of interventions along more than 200km of carriageway, including the implementation of 50 SPECS3 average speed cameras, supplied by Vysionics. The A9 SPECS3 installation has been in operation since October 2014, and is already delivering impressive changes to driver behaviour. Whilst it is still too early to report on casualty analysis, key performance indicators are already demonstrating that drivers have improved the
June 12, 2015 Read time: 2 mins

The A9 Safety Group in the UK has won the CIHT John Smart Road Safety Award, for a range of interventions along more than 200km of carriageway, including the implementation of 50 SPECS3 average speed cameras, supplied by 604 Vysionics.

The A9 SPECS3 installation has been in operation since October 2014, and is already delivering impressive changes to driver behaviour.  Whilst it is still too early to report on casualty analysis, key performance indicators are already demonstrating that drivers have improved the way they use the route, which should ultimately make it safer.  According to Vysionics, examples include the fact that overall speeding has dropped from one in three to one in 15 journeys, journey time reliability has improved and journey time reliability has improved. In addition, fewer than ten tickets per day overall have been issued, in traffic volumes of up to 24,000.

The SPECS3 cameras are mounted on highly visible columns, typically located at 5km intervals, covering both single and dual carriageway sections.  As a result, they act as a regular reminder that the route is being monitored along its length, resulting in a more considered driving behaviour.  

The judging panel commented that they were “impressed with the scale of the measures, which combine a package of engineering, education and communications strategies, and enforcement to address a significant road safety problem on an extensive route”.

Detection, Monitoring & Machine Vision Enforcement

For more information on companies in this article

Related Content

  • Call for targeted safety measures to prevent road deaths among young drivers
    January 26, 2017
    Zero tolerance on drink driving, additional hazard perception training and graduated forms of licensing should become the norm to help tackle the risks faced by young drivers and motorcycle riders in Europe, according to the YEARS report (Young Europeans Acting for Road Safety. More than 3,800 young people (aged 18-24) are killed each year on EU roads – the biggest single cause of death for this age group. A report by the European Transport Safety Council (ETSC) and the UK Parliamentary Advisory Council
    Read More
  • In-vehicle vision-based systems and autonomous vehicles
    January 11, 2013
    The Artificial Vision and Intelligent Systems Laboratory (VisLab) of Italy’s Parma University has built itself a fine pedigree in basic and applied research which has developed machine vision algorithms and intelligent systems for the automotive field. In 1998, a VisLab-equipped Lancia Thema named ‘Argo’ travelled along the famous Mille Miglia race route and completed 98 per cent of it autonomously using then-current technology. In 2005, VisLab provided the vision element of the Terramax, a collaborative un
    Read More
  • Automating seat belt compliance a priority for road safety
    February 2, 2012
    Finland's VTT is developing a mobile, automated seatbelt compliance system. Here, the organisation's Matti Kutila discusses progress
    Read More
  • Healthy prospects for floating vehicle data systems
    February 3, 2012
    Elmar Brockfeld, Alexander Sohr and Peter Wagner from the German Aerospace Center's Institute of Transport Systems look at the prospects for floating vehicle data systems. Although Floating Vehicle Data (FVD) or probe vehicle fleets have been around for about a decade, the idea behind them is of course much older: from probe vehicles that flow with the traffic it should be possible to get a precise, fast and spatially near-complete picture of the prevailing traffic flow conditions in an area under surveilla
    Read More

Highlighted Content