Continental uses recognition of roadway conditions for active driving safety
In a first application, the Road Condition Observer uses the sensors present in the vehicle to classify the road as dry, wet, snowy or icy. Thanks to this classification, driver assistance systems, such as the triggering time of the emergency brake assist, can be adapted to the possibly longer braking distance due to poorer weather conditions.
Currently, the wet condition detection is already in the extended testing of vehicle manufacturers. For the Road Condition Observer, Continental uses existing sensors in the vehicle to gain information on the grip of the road surface. With these data, the system can adjust the function of driver assistance systems to the actual road conditions.
Currently it is solely the driver’s task to assess the weather and combine it with his observations in the vehicle environment in order to draw the correct conclusions about the supposed road condition. In the future, the Road Condition Observer is intended to support the driver and enable driver assistance systems to recognize adverse conditions and to respond appropriately and in a timely manner. This ability will become even more important in the future, as automated driving also means that the assessment of the road situation is made possible by systematic means. Automated vehicle must know if it is smooth, so it can drive safely around the next bend.
For decades the automotive industry has been researching the friction coefficient as an interaction between tire and road as far as possible in order to use this information to secure its own vehicle. This size measures the force a tire can transfer to the road – the “grip” of the tires. However, all previous attempts in this direction failed due to inadequate sensors and a lack of cost-effective computing capacities. Now it has been possible to develop a system that detects the road condition and allows a classification in dry, wet, snowy and icy conditions. In addition to the driving dynamics sensors, a mono camera is also used. The advantage of this is that Electronic Stability Control (ESC) is available in most vehicles, and mono cameras are available in more and more vehicles due to the growing spread of driver assistance systems. The Road Condition Observer can classify the road conditions by evaluating the campervan of the environment directly in front of the car, comparing it with vehicle dynamics data from the ESC, knowledge of local and regional weather data (temperature, wiper activity and data from the cloud) and tire behavior. From this, a friction value class can be derived in the following step.
If possible, such a system should be implemented with the existing sensor system. With respect to the wet condition detection, the provider has already implemented this feature. In addition to wet condition detection, the next step will include a vehicle dynamics model integrated into the ESC control unit, which can detect the low friction value and then optimize the ESC activity. In the course of further development, the Road Condition Observer will be integrated into an expanded 360-degree environment model. This is the prerequisite for a more comprehensive understanding of the entire driving scene. The environmental model is created by the fusion of different information sources. The integration of road geometry, self-localization, traffic control recognition, model-based tracking of moving objects as well as recognition of passable free spaces play a role. This results in a comprehensive data basis for secure, automated vehicle management in all weather conditions.
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