Skip to main content

New Zealand to trial mobile road weather data acquisition

From September 2016, MetService and the New Zealand Transport Agency will commence a road weather mobile data acquisition trial, in conjunction with road contractors Fulton Hogan and Downer. The aim of the trial is to provide MetService, the Transport Agency, road contractors and the travelling public with pre-warning of challenging and dangerous driving conditions or potential road closures during severe weather. The six-month trial follows a pilot sensor-assessment process and aims to expand road
August 16, 2016 Read time: 2 mins
From September 2016, MetService and the 6296 New Zealand Transport Agency will commence a road weather mobile data acquisition trial, in conjunction with road contractors Fulton Hogan and Downer.
 
The aim of the trial is to provide MetService, the Transport Agency, road contractors and the travelling public with pre-warning of challenging and dangerous driving conditions or potential road closures during severe weather.

The six-month trial follows a pilot sensor-assessment process and aims to expand road weather observation assets by evaluating the use of a range of vehicle-mounted sensors for monitoring road weather conditions across the network.

As the vehicles travel the road network, they transmit real-time data continuously to provide observations of road and air temperature, rain, snow, slush, water film height, ice content, humidity and dew point temperature. Some of the sensors are capable of taking measurements up to 100 times per second. Data can be viewed on smartphones connected to the sensors by Bluetooth and transmitted on cellular networks for subsequent analysis.
 
The data collected will deliver key insights for improving road weather forecasting and road safety in locations for which there is currently no weather information available.
 
MetService says this technology will help enhance road weather modelling systems and provide access to a wide range of previously unavailable data to assist with planning and operational activities.
 
Drivers of the sensor vehicles have immediate access to data to inform them of dangerous driving conditions, and fleet operators will have better quality, more timely information for fleet management.
 
Data from mobile sensors will complement information from MetService’s existing road weather station network, which covers over 40 state highway trouble spots.

For more information on companies in this article

Related Content

  • New traffic service offering from Inrix
    October 28, 2013
    According to Inrix, its latest Inrix XD Traffic service covers 6.4 million kilometres of road in 37 countries and provides twice the amount of road coverage than has previously been available to automakers, transportation agencies, fleets and media worldwide. Inrix XD Traffic delivers insight into what’s happening on the road independent of the country or map provider, with features such as: detailed traffic speeds for every mile down to 250 metre increments; map independence; sophisticated analysis of
  • New Zealand trials parking bay sensor technology
    February 19, 2015
    Wellington City Council in New Zealand has begun to trial Smart Parking’s bay sensor technology with the installation of an initial 72 sensors. On completion of a successful trial, which is scheduled to run to the end of April, the council plans a US$1.05 million rollout of 4,000 sensors across the inner city streets. The parking solution will also include Smart Parking’s SmartApp which will allow motorists to identify streets with available bays and avoid driving around searching for a spot on roads which
  • Georgia DoT showcases its connectivity
    March 3, 2020
    Georgia DoT’s regional connected vehicle programme could be a model for the rest of the US. Adam Hill speaks to two men involved in making it a reality – and takes a look at the state’s first-ever Tech Showcase
  • Simulating the effects of optimal mobility
    May 30, 2024
    Simulation-based optimisation is the foundation for real-time predictive analytics when it comes to optimal traffic signal programming, explain Sunny Chakravarty of Econolite and Lorenzo Meschini of PTV Group