Abstract: System and method for real-time, automatic, recognition of large time-scale driving patterns employs a statistical pattern recognition framework, implemented by means of feed-forward neural network utilizing models developed for recognizing, for example, four classes of driving environments, namely highway, main road, suburban traffic and city traffic, from vehicle performance data. A vehicle control application effects changes in vehicle performance aspects based on the recognized driving environment.

Abstract: System and method for controlling a vehicle that includes sensing driver control information from each of at least two foot actuated pedals of a vehicle. The sensed information is electronically analyzed and a driver desired vehicle acceleration is determined from the sensed information. An acceleration affecting system of the vehicle is then controlled to urge the vehicle toward the driver desired vehicle acceleration. The sensed driver vehicle control information may be translated into an electronic format suitable for being electronically analyzed, but in most instances will already be in such a format and no translation is necessary. Both positive and negative determinations of driver desired vehicle acceleration are accommodated which generally correspond to desired faster travel and desired slower travel, respectively, when the vehicle is in forward motion.