Skip to main content

Ontario MOT upgrades highway infrastructure data collection

Geo-intelligence and asset integrity solutions provider Fugro has supplied the Ministry of Transportation of Ontario (MTO), Canada, with its automatic road analysers Aran 7000 and Aran 9000 to collect critical highway infrastructure data. MTO uses the systems as complementary parts of their fleet of asset management tools and utilises the data to assess the health of Ontario’s highway network in its efforts to extend the lifespan of its road network and infrastructure. The Aran 7000 is a fully port
December 14, 2016 Read time: 2 mins
Geo-intelligence and asset integrity solutions provider Fugro has supplied the Ministry of Transportation of Ontario (MTO), Canada, with its automatic road analysers Aran 7000 and Aran 9000 to collect critical highway infrastructure data.

MTO uses the systems as complementary parts of their fleet of asset management tools and utilises the data to assess the health of Ontario’s highway network in its efforts to extend the lifespan of its road network and infrastructure.  

The Aran 7000 is a fully portable road profiling solution for roughness, smoothness, rutting and texture measurement while the Aran 9000 is a fully integrated data collection system equipped with lasers, cameras and accelerometers to measure a road’s profile and to provide an inventory of road assets. The devices enable the Ministry to obtain continuous and improved infrastructure data on highways and roadways, where conducting a manual survey is time consuming and unsafe for staff.

As technology has evolved, MTO’s ability to measure conditions accurately has increased and currently it is updating existing paving contracts to include a requirement for automated data collection. Pavement smoothness is of high importance for MTO and the travelling public. Each time a contractor completes a construction, resurfacing, or rehabilitation project, they are required to use an inertial profiler to measure the surface quality using the International Roughness Index (IRI).

According to Jason Wade, pavement evaluation supervisor for MTO, combining pavement data collection activities using the Aran 9000 and 7000enables them to provide the most cost effective and appropriate solution, in the right place and at the right time. The two platforms provide seamless data integration into MTO’s Vision and iVision specialist software and web application systems. This allows MTO to make well informed decisions on pavement performance and rehabilitation.

Related Content

  • February 23, 2017
    LiDAR sets its sights on future problems
    AAdvances in LiDAR are helping transport authorities improve services and identify potential problem areas, as geospatial technology expert Dr Neil Slatcher explains. The effects of climate change on the transport infrastructure have long been a cause of concern within the transportation sector - and not only on the structures themselves but also on the surrounding areas. This year, those concerns have become reality with landslides, structural collapses and surfacing issues impacting services across the wo
  • June 22, 2012
    $3 million data collection contract
    Fugro Roadware has won a twoyear, US$3 million, contract from the US SHRP 2 (Strategic Highway Research Programme 2), for the collection of roadway data at highway speed, using ARANs (Automatic Road Analysers) on selected roads, within the six SHRP 2 naturalistic driving study sites.
  • May 12, 2021
    Webinar: AI and road asset management
    Vaisala RoadAI creates faster, more detailed, accurate and cost-effective road condition surveys
  • November 14, 2013
    Bluetooth sensors monitor travel times on Ontario’s busiest highway
    Danish wireless technology company Blip Systems and its Canadian partner G4Apps have installed wireless sensors to help reduce traffic congestion on one of Ontario’s busiest highways, the Queen Elizabeth Way, which averages close to 200,000 vehicles per day. The Ontario Ministry of Transportation (MTO) is using Blip Systems’ combined Bluetooth and wi-fi sensors to verify travel time prediction algorithms. BlipTrack sensor are mounted on posts at strategic points in the road network and detect wireless