Modal Shift Active Travel

Power Up Your Modal Shift & Active Travel Schemes With AI Computer Vision Technology

Learn more about how our AI-powered computer vision sensor can support and help improve modal shift schemes, by providing accurate insights and data to better inform decisions. The true performance and impact of Active travel projects need not be a guessing game anymore.

What's inside:

  • Why computer vision sensors are a more superior solution for traffic management insights
  • An overview of the features & benefits of computer vision sensors for:
    ○ Classification and counting of up to 32 classes of road users
    ○ Vehicle path detection
    ○ Median Journey Time
    ○ Speed and Zonal speed
    ○ Vehicle Path detection
    ○ and more
  • See how our client, Oxfordshire County Council has developed active travel schemes to support more walking and cycling

Be part of the evolution in traffic monitoring and network management using a robust AI-powered solution - Download our brochure now to learn more!

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Want to learn more about VivaCity?

Discover the Power of Computer Vision for
Traffic Monitoring and Signal Control by VivaCity

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At VivaCity, our vision is to make cities smarter, safer and more sustainable. Our AI sensors provide insights to local authorities to support strategy planning decisions.

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Our solution can  gather anonymous, real-time, multimodal traffic data and that is used by controller cabinet to optimise signalling, in an adaptable and efficient way, based on real-life needs.

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VivaCity was awarded the Queen’s Enterprise Award for Innovation in 2021 in the UK. Our sensors have been deployed in over 70 towns and cities across the UK, Europe and Australia.

A selection of our clients and partners:

Transport for London
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Transport for West Midlands
Monmouthshire
Cambridgeshire County Council
City of Port Phillip - Australia
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Vaisala
Ricardo Research - White PNG
Hackney
Cross River Partnership
WM5G
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VIVACITY

Improving traffic insights with Artificial Intelligence. Continuous 24/7 urban classification with complete anonymity