IBM announced that it has patented a cognitive system to manage the safety of self-driving vehicles.
The machine learning system developed by IBM scientists helps to shift control of an autonomous vehicle between a human driver and a vehicle control processor in the event of a potential emergency, providing a safety measure that can contribute to accident prevention.
For example, if a self-driving vehicle experiences an operational anomaly, e.g. a faulty braking system, a burned out headlight, poor visibility and/or road conditions, a comparison may be made by the system as to whether the on-board self-driving vehicle control processor or a human driver is in a better position to handle the operational anomaly. If the comparison determines that the vehicle control processor is better able to handle the anomaly, the vehicle is placed in autonomous mode.
IBM was granted U.S. Patent #9,566,986: Controlling driving modes of self-driving vehicles for this invention.
“Self-driving vehicles hold great promise and potential, but protecting the safety of passengers and other drivers remains a top priority for vehicle developers and manufacturers,” said James Kozloski, manager, Computational Neuroscience and Multiscale Brain Modeling, IBM Research and co-inventor on the patent.
“We are focused on finding new ways to leverage our understanding of the human brain and inventing systems that can help those enterprises improve the safety of autonomous vehicles on the road.”
The IBM innovations can help vehicles become:
1) Self-learning – powered by cognitive capability that continuously learns and gives advice based on behavior of the driver, passengers, and other vehicles
2) Self-socializing – connecting with other vehicles and the world around them
3) Self-driving – moving from limited automation to becoming fully autonomous
4) Self-configuring – adapting to a driver’s personal preferences
5) Self-integrating – integrating into the IoT, connecting traffic, weather, and mobility events with changing location