MACHINE LEARNING: A car that interprets the behavior of its driver and can offer alerts about when that driver seems to be inattentive or impaired is an example of machine learning. Typically, this concept refers to a computer that can gather and interpret data via an algorithm and then improve the performance over time. Many consider machine learning an attempt to automate the scientific method. If a well-programmed machine encounters enough examples it will begin to recognize certain patterns and be able to identify patterns or diagnose problems. Machine learning algorithms are used in everything from computer vision to search engines, and credit card fraud detection to handwriting recognition.
AVOIDING ACCIDENTS AT NIGHT: Driving in the dark can be dangerous. According to the European Car Council, 42% of accidents occur at night, despite the fact that traffic is much higher in the daytime. Reduced visibility is a large factor. After classifying a driver and learning the methods used to approach curves, the new system can alert a driver acting abnormally. If the driver changed behavior because of visibility, the new system will have warned the driver and allowed him or her to correct the speed and direction of the car, with the aim of avoiding accidents.
The Institute of Electrical and Electronics Engineers, Inc.-USA, contributed to the information contained in the TV portion of this report.