Assistance System Relies on Camera Signals to Detect Aquaplaning Early

Continental’s solution detects road condition by sensing the grip between the tires and the road, and coupled with data from cameras, sends a warning to the driver.

 

By Christoph Hammerschmidt, Contributing Editor

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.

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.

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.

In addition to camera data, Continental also uses information from the tires themselves to identify the risk of aquaplaning. This concept evaluates signals from the eTIS sensors built into the inner surface layer of the tire. “We use the signal from the acceleration sensor in the eTIS electronic tire information system and search for a specific signal pattern,” explains Andreas Wolf, Head of the Body & Security division at Continental. A tire model processes the incoming radial acceleration of the tire in contact with the road.

On wet roads—when enough water is carried out of the tread to ensure safe grip—the signal shows a characteristic pattern. As soon as a water wedge starts to form in the area in front of the tire contact area and there is excessive water on the road surface, the acceleration signal begins to oscillate in a characteristic way and thus indicates an early aquaplaning risk. Since the eTIS sensor can also detect the residual tread pattern of the tire, this data can be used to calculate a safe speed for a specific wet road condition and pass it on to the driver.

Tests have shown that aquaplaning assistance will also have the potential to intervene in actual aquaplaning situations in the future by applying the rear brakes in a controlled manner in order to generate a certain degree of braking torque distribution, thus keeping the maneuverability and stability of the vehicle within the physical limits.

This article was originally published in eeNews Automotive. It is reprinted here with permission.

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