For software-defined vehicles (SDVs) to be accepted as a clear upgrade over their traditional counterparts, automakers must demonstrate their functional superiority. While software offerings around infotainment and streaming can prove enticing to customers, they are already becoming standard features in most new vehicles. One area that may warrant further attention is the driving experience itself. Work is already underway across numerous fronts to achieve this, including advanced driver assistance systems (ADAS), electronic braking systems (EBS), and software-enabled drive modes that allow drivers to alter the car’s centre of gravity and manage energy consumption.
The driving experience can also be augmented through better integration of weather data. Harnessing weather data and analytics can enable automakers to inform customers about road conditions in real-time, create more adaptive routing systems, and improve a range of driving software, including ADAS, autonomous driving (AD), and EBS. Lasse Lumiaho, Head of Automotive at Vaisala Xweather, believes leveraging weather data will necessarily become a core feature of tomorrow’s SDVs. “The impact of global warming is increasingly common, and cars will only become more sensitive to weather events as we transition towards being software-driven and electric,” he tells Automotive World. “Helping drivers navigate this new environment will be key.”
Real-time weather tracking
An effective and accurate weather monitoring system for SDVs constitutes two core components: atmospheric and road weather predictions.
Atmospheric data is aggregated from a wide variety of sources, both commercial and government. This builds a real-time profile of global weather that can subsequently be integrated with vehicle software to enable better routing and help drivers navigate around potential disruptions. Through its subscription based Xweather business, Vaisala offers several solutions for atmospheric data, including autonomous humidity and water vapour trackers and LiDAR-based devices that measure and analyse cloud activity. Additionally, Vaisala provides weather forecast data globally filling in the gaps between weather station locations. As part of a wider in-vehicle mapping system, profiles of these metrics can be used to alert drivers of potentially severe conditions and either propose alternative routes or discourage travel entirely.
Road condition monitoring is enabled by a purpose built forecast system that leverages more than 70 data sources, including roadside weather stations, to be able to forecast driving conditions. “In practice, this means providing real-time updates on how many millimetres of water, snow, or ice is on the road in a given area and making that information available to drivers,” explains Lumiaho. In the context of vehicle software, this means providing more granular data on how road conditions might materially impact safety and the broader driving experience. Xweather road weather data is available across the developed world, including much of North America, Europe, Japan, Australia, and New Zealand. Lumiaho notes that more work needs to be done to expand coverage into developing regions.
Together these two components constitute the bulk of Vaisala’s Xweather road monitoring platform for automotive applications, which can be integrated into vehicle software to provide drivers with continuous weather data. In November 2024, through a partnership with automotive data and software provider Nira Dynamics, Vaisala added a third component: connected car data. The company now integrates its automotive platform and existing AI and machine learning-based forecasting models with Nira’s billions of connected car data points.
“We’re looking at reducing accidents and saving lives when this data is embedded into SDVs,” remarks Lumiaho. “You could see areas where accidents occur in real time and issue warnings based on our road condition data—say, for example, due to slippery roads.” Data from connected cars could in turn be relayed to road maintenance teams to increase responsiveness and deal with potential issues before they worsen.
Facilitating future mobility
While the integration of up-to-date weather and road condition data promises to make vehicles safer across the board, its most meaningful applications could be found in enhancing the safety and useability of technologies currently reshaping the automotive landscape. Lumiaho previously told Automotive World about the potential for weather data to make more accurate and dynamic indications of electric vehicle (EV) range. “A gasoline engine is only about 25% efficient, and diesel is 40%, but an EV can be up to 95%. This means that when environmental conditions affect performance, it’s comparatively very noticeable.”
Air temperature alone can diminish an EV’s basic range by up to 40%, rising to 75% if roads are covered in snow or experiencing high winds. Supplying such information through the infotainment system, particularly when providing route options to drivers, could help them save time and money, or prevent the car from running out of energy in a charging dead zone. Beyond determining EV range, this data can be used to make recommendations on software-enabled driving modes—for example, suggesting a switch to eco-mode when driving in inclement weather. In addition, EBS can be dynamically reconfigured to help drivers navigate slippery conditions or severe winds.
Better integration of weather and road conditions data sets would also facilitate the rollout of more advanced software offerings like ADAS and AD. Lumiaho opines that such data could prove essential for facilitating these features on a number of fronts, including reliability, safety, and consumer trust. “If you use this data, the vehicle can better understand the friction of the road surface and thereby help to increase the availability and safety of these features.” AD could be disabled in conditions it is inadequately trained to navigate, while ADAS could be activated to hit the emergency brakes and prevent an accident. Beyond in-vehicle applications, Xweather data sets could also be used to better train ADAS and AD systems, improving their performance in extreme weather conditions.
If you want to make the most of the data, you’re going to need a live connection
Ultimately, Lumiaho believes that deeper integration of weather and road condition data will facilitate the realisation of SDVs across several fronts, demonstrating clear advantages over their more traditional counterparts. However, uneven connectivity—particularly in more remote locations—may impact the reliability of its real-time predictions. “If you want to make the most of the data, you’re going to need a live connection,” he states. “This also extends to ADAS and AD use-cases. Today’s sensors might be able to see what’s happening 200m ahead, but they can’t see around corners or what lies beyond an incline.”
With time, he believes that the usage of such data will become commonplace in automotive software, in part due to the increasingly common nature of extreme weather events. Consumers will see it not as an add-on or subscription option but a core SDV feature included as standard at purchase. “It’s definitely more of an add-on today, but safety should not be compromised because somebody did not subscribe for a service. We are already seeing software features from high-end vehicles trickling down into cheaper models, and I expect that the same will happen here.”
