Vaisala Xweather to add NIRA’s connected car data to their road condition platform

Vaisala Xweather announced a partnership with NIRA Dynamics for the release of an advanced data set. The integrated data set introduced into Vaisala Xweather’s platform connects advanced artificial intelligence (AI) and machine learning (ML) based road weather forecasting models with NIRA Dynamics’ billions of data points gathered from connected cars.

The future of driving is fueled by data
The future of driving is going to be heavily dependent on more accurate and real-time road weather and road condition data as the availability of autonomous and assisted driving features are highly influenced by the driving conditions. Currently, as seen in many Electric Vehicles (EVs), the assisted driving functionalities are disconnected to secure driver safety based on crude weather and road condition estimations, such as a temperature drop to under 4 degrees Celsius or a change in tire rolling resistance.

Real-time data from connected vehicles on tire grip, road friction, surface quality, and weather conditions combined with leading industry-specific weather forecasts create an aggregated data set with multiple use cases already today. Examples of these are reducing the likelihood of accidents by increasing the autonomous and assisted driving features’ availability in poorer road weather conditions, enhancing the condition of the road network with computer vision analysis of defects and assets, and minimizing resource consumption, such as the overuse of salt in winter road treatments benefiting all road users.

Third-party data brings future opportunities
The integration of connected car data from NIRA Dynamics into Vaisala Xweather’s platform will pave the way for future partnerships in road safety and condition data. Utilizing third-party data from various sources, Xweather is currently looking into opportunities for example in EV range optimization, road asset management, the insurance sector, and reducing road accidents through road condition alerting.

By harnessing real-time connected vehicle data and advanced road weather models, and combining it with insightful visualizations, this collaboration will lay the groundwork for future advancements in road safety, efficient maintenance, and the expansion of autonomous driving technologies.