Cruise control system uses AI to mimic driver behaviour

October 25, 2019 //By Christoph Hammerschmidt
Driver assistance system controls speed using artificial intelligence
Hyundai Motor Group is developing a cruise control system based on artificial intelligence. The technology analyzes the driver's individual driving behaviour and combines it with the vehicle's autonomous driving functions. The aim is to enhance the individual driving experience.

Hyundai's technology integrates artificial intelligence (AI) into the company's Advanced Driver Assistance System (ADAS). The system, called Machine Learning based Smart Cruise Control (SCC-ML), will go into series production already in Hyundai's next generation of vehicles, the company said in a press release.

SCC-ML combines AI and SCC into a system that analyzes and learns the driver's driving behavior. Through this machine learning, the new technology independently regulates the speed according to the same pattern as the driver. The system works as follows: Sensors such as the front camera and radar constantly record driving information and send it to a central computer. This computer extracts the relevant details from the collected information in order to identify the driver's typical driving patterns. This process of machine learning is controlled by AI. The system is programmed in such a way that it recognizes unsafe driving patterns and does not adopt them.

With currently available conventional cruise control systems, the driver manually adjusts the distance to the vehicle in front and the speed to be driven. Without machine learning, it is not yet possible to meticulously adapt the settings required for autonomous driving to the individual preferences of the driver. For drivers, this semi-autonomous driving feels strange and unfamiliar because it does not suit their driving style. This is why some drivers use the automatic speed control rather cautiously.

The algorithm captures three aspects of the manual driving pattern: distance to vehicles in front, how strongly the driver accelerates and how quickly he reacts to changes in the driving situation. External driving conditions and current speed requirements are also taken into account.


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