RCD

RCD empowers systems to take data-driven decisions at the right time

Klimator’s RCD provides expert road weather forecasts with high precision on any given road network. The solution integrates into any system that benefits from knowing the road weather condition up to 18 hours ahead of time - from the temperature of the road to the probability of a specific segment being slippery.

0-18h forecast over full road network

25-250 m segments

One global specification

RCD is made possible by machine learning, ruled-based models and big data

RCD is made possible by combining machine learning, ruled-based algorithms, and vast amounts of real-life road and environment data. Our models and big data enable us to understand the present and predict the future.

By using any road network and dynamically segmenting it, RCD internally models the road network including its surrounding topography (Road section characteristics). Using a proprietary model and arrangement for collection and processing of live and historical data from different data sources:

Stationary data source
Dynamic data source
Meteorological data source

RCD algorithms model the current and forecasted road condition down to a road segment resolution of 25 meters per segment. The method is unparalleled as it uses extensive knowledge of the microclimate and the surrounding topography when forecasting the road status.

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:
Unique resolution of 25-250m road segments
Full coverage 0-18h forecast over a complete road network
One global specification
Broad coverage
15 min forecast update
Map agnostic
Ability to integrate new data sources
Proactive data instead of reactive data
Data that goes RCD the line of sight - providing critical information at the right time

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.

One solution for multiple markets

Automotive

RCD is used as predictive data for "ADAS (Advanced Driver Assistance Systems)" and AD (Autonomous Driving) – to increase functionality and performance – allowing the driver and the vehicle to plan and act proactively for the safest and best possible driving experience. Most common use cases:

Increased driver information
Enhanced ADAS functionalities
Safe and scalable AD
Optimization

Smart City

Cities connect large amounts of people in dense areas through the invention of roads and smart transport solutions. Cities must function and flow efficiently and effectively to avoid disorder. When a city experiences disorder due to changed weather conditions, huge monetary losses are often the consequence. People end up late for work, production and deliveries fail due to a stand-still, and the police-and response force is hugely limited. Klimator provides RCD to smart cities that want to avoid such disorders.

With RCD our customers access tools and data so they can plan, act and alert to minimize the impact of such hazardous road weather, saving resources, time and lives.

RCD is massively useful to airports, traffic management operators, winter maintenance contractors, logistics companies as well as pedestrians and bikers. Read more about how we provide solutions and value to smart cities under our Klimator x Smart City page.

Predictive Road Weather Intelligence

Achieve next level safety with Klimator

DaaS Business Model RCD - predictive data for proactive driving