Skip to main content

Demonstration zone launched to develop connected and automated vehicles, Canada

A new autonomous vehicle (AV) demonstration zone has launched to allow researchers to hone the technology and test AVs in a range of everyday, real-life traffic scenarios in Ontario, Canada. Called the Autonomous Vehicle Innovation Network (AVIN), the Canadian government has invested $80 million (£61 million) over a five-year period in support of the project.
November 10, 2017 Read time: 2 mins
A new autonomous vehicle (AV) demonstration zone has launched to allow researchers to hone the technology and test AVs in a range of everyday, real-life traffic scenarios in Ontario, Canada. Called the Autonomous Vehicle Innovation Network (AVIN), the Canadian government has invested $80 million (£61 million) over a five-year period in support of the project.

Premier Kathleen Wynne officially opened the AVIN Demonstration Zone, to see first-hand how the space will help researchers continue to improve the technology. The province is partnering with Ontario Centres of Excellence in AVIN, which will bring together industry and academia to capitalize on the economic opportunities of connected and autonomous vehicles (C/AVs) while developing the emerging technology and infrastructure.

In addition to the Demonstration Zone, AVIN includes a Research and Development Partnership Fund, to foster collaboration among automakers, technology leaders and Ontario-based small and medium-sized enterprises to develop and commercialize C/AV technologies. Collaborations may also involve post-secondary institutions and municipalities. A Talent Development Program will help support internships and fellowships for students and recent graduates with Ontario companies advancing C/AV technologies. Additionally, a central hub (a new online destination) and specialized team will act as a focal point to conduct research, share information, build connections and raise awareness among industry, research institutions and other interested C/AV stakeholders.

Steven Del Duca, minister of transportation, said: “Connected and automated vehicle technologies demonstrate opportunities to enhance road safety and reduce traffic congestion and pollution. Ontario’s comprehensive approach, encompassing smart regulation and strengthening our innovation ecosystem, is ensuring the province proactively shapes and promotes emerging vehicle and transportation technologies to help meet our goals. AVIN is a significant step forward to ensure the investments and planning we are making in building Ontario’s transportation infrastructure network now meets the demands of the future.”

Related Content

  • VDOT chooses StreetLight Data for on-demand traffic intelligence
    January 22, 2018
    The Virginia Department of Transportation (VDOT) has selected StreetLight Data (SLD) to provide on-demand traffic and transportation intelligence. It aims to enable local and state planning agencies to transform Big Data from their mobile devices into useful mobility metrics via its regional subscription to SLD’s Insight platform. The service also offers unlimited analyses of real-world travel patterns in the state and is available for designated employees and engineering firms.
  • Canada invests in Peel Region transit 
    February 3, 2021
    Projects in Southern Ontario include low-emission buses and e-fare collection system
  • Huawei opens door to new opportunities in transport & logistics
    December 18, 2024
    By addressing the four key elements of a transportation network’s composition with a state-of-the-art digital solution, Huawei is bringing significant performance uplifts to all aspects of railway operations
  • Evaluation of machine vision market in Italy
    August 11, 2015
    The European Machine Vision Association (EMVA) has published its 2015 market report, Machine Vision in Italy, which evaluates the machine vision market in the country for the first time. It covers the vision industry, its customers and the main applications as well as technical and commercial trends. In addition, the network for machine vision is described, including clusters, research centers and associations, trade shows and special magazines, supplemented by market and growth drivers and an estimate