Assistance systems relies on camera signals to detect aquaplaning early on

April 16, 2018 // By Christoph Hammerschmidt
To warn drivers of aquaplaning risks, Continental is developing a new system that evaluates the images from the Surround View camera and specific vibration patterns in tire sensors. The principle can also be applied to robot vehicles.

Dry, icy, snowy or wet: knowledge of road conditions is an essential safety factor, as accidents in difficult weather conditions are mainly caused by a loss of grip between the tires and the road surface. Aquaplaning situations represent a special risk, which are extremely dangerous not only for manually controlled vehicles but also for automated ones:  If there is a solid film of water on the road, the water pressure between the tire contact patch and the road may cause the front wheels to begin to float. Braking and steering are then no longer possible and the driver loses control of the vehicle.

With the Road Condition Observer, Continental has already presented a solution that makes it possible to detect the road condition with regard to the grip between the tires and the road. Now the technology company has begun to develop innovative sensor-assisted concepts that warn the driver in good time of an imminent loss of grip. The system developed by Continental comprises all components: from tires, tire sensors, cameras, algorithms and brake actuation to the man-machine interface. The aim of the development is to predict the risk of aquaplaning and to detect a potential floating of the front wheels as early as possible so that the driver can be warned in time.

Using information from Surround View cameras and eTIS (electronic-Tire Information System) sensors mounted in the tire, a warning is triggered to the driver indicating imminent aquaplaning. To detect such situations, the system evaluates images from Surround View cameras installed in the side mirrors, radiator grille and rear. When there is a lot of water on the road, the camera images show a specific spray pattern of the tires that can be identified as aquaplaning. For example, excessive water displacement in all directions under the tire is a characteristic feature. In the first test phase of the new system, the algorithms for moisture detection in predicting potential aquaplaning conditions already delivered a very high hit rate.


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