Audi is taking another step towards safer and smarter mobility. With the car-to-X service, it uses highly accurate herd data for the first time to improve "Local Hazard Alerts".
The new version basically includes a new procedure that estimates the coefficient of friction with tire slip and uses car-to-cloud application. This technology detects the smallest changes in grip on the road surface, uploads the data to the cloud for processing, and warns oncoming drivers about changes in grip, icing or other slippery conditions in near real time.
Thanks to the CAR-to-X communication technology used, the models produced by Audi since 2017 warn each other about issues such as broken down vehicles, accidents, traffic congestion, icing on the road surface or limited visibility. Analyzing such a variety of data, the system makes available 'LHA-Local Distress Alerts', which covers many measures such as ESC activation, rain and light sensors, windshield wipers, headlights, emergency calls and airbag triggers.
In order to make this warning faster and more precise, Audi is preparing to take the next step by improving the service with high-accuracy herd data and collaborated with Swedish company NIRA Dynamics AB. Two companies, this application, Car.Software Org. and adapted it to improve the hazard warnings developed by HERE Technologies.
The system calculates the coefficient of friction between the spinning tire and the road surface using chassis signals such as wheel speed and acceleration values. Effective not only in extreme situations where chassis control systems intervene, but under normal driving conditions, the system allows the sensor data to be turned into open data by keeping the acquired sensor data both in the car itself and transmitting it to the cloud in NIRA Dynamics AB.
This data collected from many cars is then combined with data such as current and historical weather information and then transmitted by the NIRA cloud to service provider HERE Technologies. When integrated with the HERE location platform, the unified data intelligence creates the road network as a precise three-dimensional model. HERE servers send warning information to cars entering or driving into poorly conditioned areas. Thus, the driver who sees a warning in the Audi virtual cockpit or on the optional head up display screen is enabled to drive accordingly.
Number of cars is a factor in success
One of the most important factors in the success of the system is the number of vehicles. The more cars transmitting data, the better the system can learn, analyze, create maps, inform or warn drivers depending on the situation. This also constitutes the core principle of swarm data (SD) and swarm intelligence (SI), an area on which Audi has focused and gained important information in recent years.
In 2021, more than 1,7 million cars from the Volkswagen Group are projected to contribute data for this improved hazard warning service in Europe, a significant advantage, to over 2022 million by 3. The service is currently available on new models from Audi, Volkswagen, SEAT, Škoda, Porsche, Bentley and Lamborghini.
The first customer application where automobile data is applied to analysis
The project, whose main responsibility is Volkswagen Group's company Car.Software, was designed in such a way that as many drivers as possible could benefit from these safety benefits, regardless of the group brand.
Together with our group brands and strategic partners, we were able to develop a digital service within a few months while using our own software skills and economies of scale. ” said.
It will offer many benefits
The system can bring many benefits with it. By using existing friction coefficient maps based on the data pool, municipalities, for example, can optimize their snow removal services in real time and reduce the environmental impact by using less road salt. Driver assistance systems, on the other hand, can precondition themselves and adapt with even greater precision to the road situation. The navigation system can take into account road conditions to provide a more accurate calculation of the expected arrival time. Tire maintenance services can be improved by determining the skid control, wear level and performance level of the tire.