Klimator x Automotive Market
Road weather intelligence made available through predictive and detective data - empowering the trajectory towards safe, sustainable, and autonomous driving.
Never permit perilous road weather to jeopardize the safety or operability of vehicles. Klimator's road weather intelligence is a critical component when connecting the surrounding environment to the vehicle, bridging the gap between nature and innovation. Resulting in information enabling proactive AD and ADAS systems and next level of safety.
RCD is a cloud-based solution providing information about the current and forecasted road weather on an entire road network. RCD has the unique ability to unleash world-leading forecasts, based on 30 years of research, that allows the vehicle to see beyond the line of sight. Automakers use RCD to empower AD and ADAS systems with proactive insights.
Road weather detection that allows the vehicle to act on what’s AHEAD while in motion, enabling proactive driving – replacing unsafe reactive driving. Klimator’s AHEAD solution is an embedded sensor fusion technology providing extensive real-time information about the prevailing road surface.
The best way to prevent unsafe driving is to equip vehicles with technologies that support proactive motion, instead of relying on reactive measures. AHEAD enhances the operability of the onboard system by feeding continuous data streams on the prevailing road surfaces AHEAD, enabling the vehicle to act in the right way, at the right time.
Visualization of slip risk in driver information system
Enable intelligent ADAS solutions in ”non-dry” conditions
Enable safe scalability of AD
Enable more efficient driving
Our base model has global coverage and our enhanced model covers the majority of Europe as well as critical areas in the US. We are continuously expanding our enhanced model coverage. Contact us for more information on the exact areas.
Our models are built and developed on the knowledge basis of road climatology, using a combination of ruled-based algorithms and machine learning to find correlations between road surface, surroundings, and the micro-weather. Vehicle data is not a required input to obtain the necessary and valued output. However, vehicle data can be a useful input in real-time cross-validation, which we often employ when working with OEMs.
We validate in numerous steps, both qualitative and quantitative. The overall approach we employ is out-of-bag cross-validation - which we do on every forecast and for every station, continuously and on the entire road network. We also employ qualitative validation with laser data for selected road stretches and periods.
With our unparalleled legacy within road climatology research, being the founding entity of the topic, we have know-how no other can contend with. Important to understand is that we apply our knowledge for our customers to gain a fundamental understanding of the prevailing and future road conditions and not the general weather, which many other market actors sell in sophisticated, but essentially ineffective, packages.
Our abilities have resulted in a unique set of USPs that we proudly highlight:
Accuracy can be determined once the scope of service, requirements, and definition of accuracy is established with OEM. Also, requirements on accuracy tend to vary depending on the use case. Contact us for more information.
Klimator is foremost a software company. However, for testing and after-market applications we provide a hardware setup, which may be seen below. In automotive serial production applications, customers acquire sensors on their own according to our specifications.
Yes, in theory. But practically it is not advised, as recalibration needs to be performed as well as reinstallation, resulting in higher costs and ineffective project execution.
Installation and calibration (predefined calibration routine).
The road is seldom homogenous, as the wheel tracks usually have a different road condition that the rest of the road surface. Hence, we need two laser points to cover the two areas of interest, in the wheel track as well as in between. This provides us with a good data set that represents the prevailing condition of the road surface AHEAD of the vehicle.
Depends on the conditions. But in good conditions, we have a range of approximately 50 m.
Europe, Japan, the US
Yes, we have multiple ongoing projects combining these technologies.
We have collected a couple of examples of different weather situations based on how they...
Most of us understand that some parts of a road are more slippery than others. But we...
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The fair and meeting place for everyone who works with safety on roads and streets.
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