Winter maintenance is not just about knowing when and where action has been taken. It's about understanding whether those actions have improved road conditions. With better access to real-world road data, we can start measuring the results, not just the work performed.
Every winter, road authorities and maintenance teams make countless decisions about when, where and how to treat roads. These decisions are guided by weather forecasts, road weather stations, inspections and years of operational experience.
But once a decision has been made and an action carried out, an important question remains: Did it actually make a difference?
Traditionally, winter maintenance performance has often been evaluated through operational measures, such as response times, completed treatments and the amount of salt used. These are valuable indicators, but they don't necessarily tell us what happened on the road afterwards.
To understand the effectiveness of winter maintenance, we also need to look at the outcome.
Successful winter maintenance is about keeping roads safe and accessible while making responsible use of available resources. That means taking action when needed, but also recognizing when conditions are already good enough without additional treatment.
And this is where measuring performance becomes more complex.
A road may have been salted according to schedule, but did the friction actually improve? How long did the improvement last? Could another road section have required attention sooner? And when a decision was made not to salt, did the road remain safe afterwards?
These questions highlight an important distinction between measuring maintenance activities and measuring their results.
Both matter, but they tell us different things.
From completed actions to measurable results.
To evaluate winter maintenance effectively, road authorities need to consider several indicators. Some describe how efficiently maintenance operations are carried out, while others help assess the conditions experienced on the road.
For example:
Together, these indicators provide a broader picture of winter maintenance performance.
But one of the challenges has always been getting enough information about the actual road conditions, particularly across larger road networks.
Road weather stations provide valuable measurements at specific locations, while forecasts help anticipate where problems may develop. However, conditions can vary considerably between measurement points.
This is where observations from connected vehicles can add another perspective.
Consider a road section where slippery conditions have been detected. A maintenance team decides to salt the road. The action is completed and recorded, but how can the team determine whether the treatment achieved its intended effect?
By following road friction in real-time from connected vehicles before and after the treatment, it becomes possible to observe how conditions develop. If friction improves, that provides useful information about the outcome. If conditions remain slippery, further investigation or action may be needed.
Of course, road conditions are influenced by several factors, including temperature, precipitation, traffic and changing weather. An improvement in friction does not automatically mean that a particular maintenance action was the only cause.
Nevertheless, being able to observe these changes provides valuable information that would otherwise be difficult to obtain.
The same principle applies when no treatment is carried out.
Sometimes, the right decision is not to salt. But validating that decision requires knowing whether road conditions remained acceptable afterwards.
This is an important shift in perspective: from simply documenting what was done to understanding what happened as a result.
Modern vehicles continuously interact with the road surface. Through their existing sensors and vehicle dynamics systems, they generate information that can be used to estimate road friction and identify changing surface conditions.
NIRA's Winter Road Insights uses data from connected vehicles to make this information available for winter road monitoring and maintenance decisions.
By aggregating observations from vehicles travelling across the road network, the solution provides insights into road conditions with data updates every ten minutes.
Rather than relying on observations from selected locations alone, road authorities can gain a more detailed understanding of how conditions develop across the parts of their network covered by vehicle data.
Combined with weather information, maintenance records and existing monitoring methods, these insights can help teams follow up on treatment decisions and better understand the conditions that followed.
The value is not simply having more data. It's being able to connect maintenance activities with observations of the road conditions they are intended to improve.
Measuring winter maintenance effectiveness is not only about evaluating individual treatments. Over time, the information can also help identify patterns and support improvements in how maintenance is planned and managed.
Are certain road sections repeatedly experiencing low friction? How quickly are slippery conditions addressed? And how long do the effects of different treatments last?
These are questions that become easier to investigate when actual road condition data is available alongside operational information.
A practical example comes from Svevia, one of Sweden's largest road maintenance providers. By using NIRA's Winter Road Insights, Svevia can monitor how well road conditions meet the winter maintenance requirements set by the Swedish Transport Administration (Trafikverket).
Through friction-based performance indicators, Svevia can track compliance with defined service levels.
But the value goes beyond measuring compliance. By comparing road conditions across different periods and against a reference network, Svevia can also evaluate how quickly slippery conditions are addressed and how long the effects of anti-slip treatments last.
This creates opportunities to compare maintenance performance, identify areas for improvement and refine strategies based on observed road conditions rather than completed activities alone.
It's a practical example of how winter maintenance evaluation can move from simply recording what has been done to understanding the conditions achieved.
Connected vehicle data gives us a new way to understand how winter maintenance performs in practice. By providing real-world observations from vehicles travelling across the road network, it allows us to follow how road conditions develop over time and gain a clearer picture of what is happening on the roads.
More importantly, these insights make it possible to verify the results of maintenance activities. By monitoring friction before and after treatment, road authorities can see whether conditions have improved, evaluate the effectiveness of their actions and identify where further attention may be needed.
Rather than simply knowing what maintenance has been performed, connected vehicle data helps us understand what it has achieved. And with that knowledge, we can make more informed decisions and continuously improve winter maintenance strategies.