Skip to main content

Viva drives NYCDoT road safety data collection pilot

Viva sensors installed at 12 locations in Brooklyn, Bronx, Manhattan and Queens
By Adam Hill April 19, 2023 Read time: 2 mins
The pilot will help NYCDoT understand how people on different modes use the streets (© Leo Bruce Hempell | Dreamstime.com)

Viva sensors are being used in a New York City pilot to improve road safety.

New York City Department of Transportation (NYCDoT) has put Viva (the US name for UK firm VivaCity) sensors on streetlight poles in 12 locations in Brooklyn, Bronx, Manhattan and Queens to see if they are cheaper and more accurate than manual traffic counts.

The technology collects street activity data via camera, then classifies and counts road users in real time.

This will help "to generate detailed reports that will allow planners to better understand the uses of city streets and inform future street redesigns", NYCDoT says.

The Viva sensors identify and count up to nine different modes of travel, including pedestrians, cyclists, cars, buses, trucks and e-scooters.

They can see seasonal changes in travel patterns, show path and speed of travel, and detect near-miss incidents and turning movements.

Viva will provide street activity count data by analysing video footage from temporarily installed cameras or existing live feeds.

The agency will use the data to analyse the effectiveness and safety of its initiatives and street designs, and to prioritise projects for areas most in need of street improvements.

The sensor information will also help NYCDoT to better understand how people use the streets themselves - for instance, accessing bus stops or loading zones, visiting businesses, or preferred places to cycle.

NYCDoT insists: "The pilot prioritises privacy, identifying data-collection methods that protect privacy by removing identifying information of roadway users and discarding video frames after counts are collected on the device."

The project is a partnership between NYCDoT, New York City’s Office of Technology and Innovation and City University of New York.

It was funded primarily by a grant from the New York State Empire State Development Corporation, with support from Federal Raise and Safe Streets For All grants.

For more information on companies in this article

Related Content

  • Video analytics enhances urban rail safety
    December 16, 2016
    David Crawford explores some promising innovations for North American commuters. North America is experiencing a surge in commuter rail and metro development. The US now has 75 light rail and metro networks in operation; and California, in particular, is actively exploring ways of developing the state’s existing passenger rail operations into a fully integrated system.
  • New York sees a boom in cycling
    May 10, 2016
    According to New York City Department of Transportation’s (NYC DOT) 2016 Cycling in the City brief, New York City has seen a recent dramatic increase in cycling, with the claim that the city has seen a 320 per cent increase in daily cycling between 1990 and 2014 and a 68 per cent growth in daily cycling between 2010 and 2014. The brief uses data collected by the Department of Health and Mental Hygiene (DOHMH) as part of its annual Community Health Survey, where 25 per cent of adult New Yorkers (almost 1.
  • Trafik Stockholm uses data gathered from Bluetooth and Wi-Fi to alleviate congestion
    November 20, 2017
    Trafik Stockholm (TS) has chosen Blip Track technology from Denmark-based Blip Systems to alleviate congestion on the city's road by providing live traffic information via real-time and historical travel flow data from road users’ Bluetooth and Wi-Fi devices. Travel times are continuously updated in line with the behaviour of road users so that by considering their route and the time they depart, they can help to reduce bottlenecks and keep traffic moving. The technology provides a birds-eye view of the
  • Estimating winter road recovery time with traffic data
    February 15, 2013
    In Minnesota, US, the most common measure for snow management performance is the time it takes to completely clear a roadway after a snow event ends. Currently, the Minnesota Department of Transportation (MnDOT) relies on visual inspections by its field crews to estimate this bare pavement recovery time. To help MnDOT more accurately and reliably estimate the performance of its snow management activities, researchers from the University of Minnesota Duluth (UMD) have developed a prototype process that uses