TECHNICAL FIELD

This invention relates generally to the automotive vehicle control field, and more specifically to a new and useful method for determining driving policy in the automotive vehicle control field.

BACKGROUND

Automotive accidents are a major cause of deaths and injuries to human drivers. In order to improve safety and significantly reduce the number of fatalities, autonomous driving systems and control methods are being considered as an effective solution. Machine learning can play a significant role in developing such autonomous driving systems and control methods, wherein computing systems can be trained to drive safely and with minimal intervention from human drivers, according to a set of driving behavior rules for various real-world situations that can be collectively defined as driving policy. However, training such systems can require large quantities of accurate and salient data, and data saliency can be difficult to determine without excessive time and expense (e.g., through the use of human labeling, filtering, and/or other manual techniques for determination of data saliency, etc.).

Thus, there is a need in the automotive field to create a new and useful method for determining driving policy. This invention provides such a new and useful method.

