Cold comfort

Delivering short-term road weather information to road users in Arctic conditions is no simple task as Heikki Konttaniemi, Timo Sukuvaara, Marjo Hippi, Johan Casselgren and Matti Autioniemi explain.

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Experimental road weather station: if awareness of adverse conditions was location specific, the risk of accidents would be decreased as much as by 20 per cent

Arctic special conditions stand for characteristics such as very long distances, sparse population and major temperature and precipitation variations. In these special and often extreme circumstances all the businesses, infrastructure and people still need to function safely and securely.

Currently, the changing climate creates more and more frequent and extreme weather conditions. Despite of these facts, the mobility of people and goods in the North will increase drastically as there are a lot interests in the arctic natural resources. This is true especially in Northern Finland due to its location in the center of the whole Barents region. In the Arctic Business Forum 2014, the upcoming investments in the Barents are now estimated to be as much as €155 billion. As the density of traffic increases in special climatic conditions, it is essential for the people and businesses to have fluent transport and logistics as disruptions mean not only financial losses but also possible injuries or fatalities. As an example, tourism as a one major industry is especially vulnerable to image losses caused by incidents.

Conditional Critical

According to VTT, in Finland the bad weather conditions are a factor in 20 – 25 per cent of the road accidents. If the road users had awareness of road conditions, the accident risk would be 10 per cent lower. If that awareness was location specific, the risk would be decreased as much as by 20 per cent. According to studies done by Tampere Technical University, the risk of accident will drastically increase when the road is snowy, slushy or icy. The risk is even five times bigger when there is for example ice and loose snow on the surface when compared to dry road surfaces. The EU has set ambitious goals in halving the road fatalities by 2020 and moving towards zero fatalities in a long run. Anticipating and reacting to road weather and slipperiness will therefore definitely have a role in the big picture even at EU level.

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Snapshot from public Intelligent Road web interface

Modern sensors and communication technologies as a tool for collecting and transmitting relevant information from the road. Currently the road weather and road surface condition information is acquired through weather forecasts, road weather stations and road weather cameras. The problem is that especially in areas with long distances, there are not enough observations available. However, the latest technological development has enabled us to gather that information by the use of mobile sensors attached to vehicles. In the future, the vehicles will communicate road condition information centrally to a cloud or form ad-hoc networks with other vehicles and the infrastructure to exchange data. The vehicles will detect slipperiness, among other things, enabling the design of new services based on accurate location-specific data.

Some steps towards this kind of development have been taken in a Finnish-Swedish Intelligent Road project, which is implemented in Northern parts of Finland and Sweden by Lapland University of Applied Sciences, Finnish Meteorological Institute and Luleå Technical University. The project creates a demonstration system for collecting, communicating, and analyzing and visualizing road weather and road surface condition information.

In the project, there are several frequently travelling heavy trucks as well as passenger vehicles that are continuously gathering data on the road surface condition but also on the ambient temperature and humidity. These ‘mobile road weather stations’ have integrated data-acquisition systems designed to collect, process, transmit and receive real-time data from different sensors and data sources. The real-time data is GPS positioned and time stamped for detection of location-specific road surface condition information. The in-vehicle systems use optical measurement in detecting the road surface conditions (icy, slushy, wet, snowy, dry), friction estimations, and road surface temperature and water layer thicknesses on the road surface.

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Snapshot from the app in development that will also be able to give real-time information of the sensors installed on the vehicle

As for stationary measurements, there are around 500 road weather stations around the Finnish main road network mostly located in southern part of Finland. However, the Finnish Meteorological Institute (FMI) has built a special experimental road weather station for Sodankylä, Finnish Lapland in order to create new kind of road weather services. The idea is to combine data from the station, areal meteorological measurements and large scale meteorological services for delivering advanced road user services. The station contains wireless communication systems for IEEE 802.11g and IEEE 802.11p for communicating with the by passing vehicles equipped with compatible systems.

Weather or not…

On top of the measurements on the road, the meteorological forecasts have an important role when forecasting the road weather. In the future, the observations carried out automatically by vehicles will have more and more important role when modelling the road weather and giving local specific and real time road weather warnings in the future. Road weather model predicts what happens on the road surface due to different weather phenomena. The FMI road weather model predicts for example road surface temperature, road condition and friction. The length of the road weather forecasts are typically from nowcasting scale (2…6 hours) up to several days. The road weather model uses meteorological observations, road weather station information as well as numerical weather prediction as input data.

How to use the data for services

The both mobile and stationary measurements as well as meteorological data combined form a set of data that in the future will enable the service providers to tailor new services for various segments of road users.

38_Cold Comfort Facts boxThe role of Intelligent Road project is to demonstrate services which are exploiting this data. The public Intelligent Road web interface features types of data available and places it on Google Maps layer. FMI has a public web access to the measurements carried out in their experimental station in Sodankylä. The web application is accessible through A vehicle passing by the station will receive the services from the station via in-vehicle computer or a mobile device.

One way to deliver the information is through navigation apps that warn the driver of slippery conditions ahead or on-spot. Currently, the Lapland University of Applied Sciences is developing an app which is able to communicate this information but also gives real-time information of the sensors installed in the vehicle.

The main target groups for such applications are regular road-users, professional transport and winter road maintenance.

Currently the project consortium is looking to design and test new services in larger scale in close collaboration with authorities and end-users while involving SMEs comprehensively throughout the value chain. 


Heikki Konttaniemi is project manager in Arctic Power research unit of Lapland University of Applied Sciences. Timo Sukuvaara and Marjo Hippi are from the Finnish Meteorological Institute. Johan Casselgren works at Luleå Technical University and Matti Autioniemi represents the Arctic Power unit of Lapland University of Applied Sciences.