Abstract: The system includes a road scenario sensor, a vehicle control unit, and a computer processing unit. The road scenario sensor detects upcoming road scenarios for the system vehicle. The computer processing unit receives an input from the road scenario sensor and determines a upcoming driving event based upon the detected upcoming road scenarios. The computer processing unit compares the upcoming driving event with an ideal emissions model having acceptable emission thresholds to determine an adaptive driving strategy. The adaptive driving strategy configures the system vehicle to reduce emissions for the upcoming upcoming driving event. The adaptive driving strategy optionally includes an optimal acceleration rate and/or an optimal power management strategy. The optimal acceleration rate is based upon the required speed of the vehicle at the upcoming driving event and the distance from the vehicle to the upcoming driving event, and the ideal emissions model having acceptable emission thresholds.

Abstract: A method for facilitating the avoidance of a vehicle collision with an object includes the following steps: a) providing an environment for generating training examples, b) evolving a good driver using a visual input, c) evolving a crash predictor using a visual input, and d) outputting a warning signal.

Abstract: A method for facilitating the avoidance of a vehicle collision with an object includes the following steps: a) providing a neural network, b) evolving a good driver, c) evolving a crash predictor, and d) outputting a graded warning signal.

Abstract: A method for facilitating the avoidance of a vehicle collision with an object includes the following steps: a) providing an environment for generating training examples, b) evolving a good driver using a visual input, c) evolving a crash predictor using a visual input, and d) outputting a warning signal.

Abstract: A method for facilitating the avoidance of a vehicle collision with an object includes the following steps: a) providing a neural network, b) evolving a good driver, c) evolving a crash predictor, and d) outputting a graded warning signal.

Abstract: An object detection system includes at least one sound receiving element, a processing unit, a storage element and a sound database. The sound receiving element receives sound waves emitted from an object. The sound receiving element transforms the sound waves into a signal. The processing unit receives the signal from the sound receiving unit. The sound database is stored in the storage element. The sound database includes a plurality of sound types and a plurality of attributes associated with each sound type. Each attribute has a predefined value. Each sound type is associated with each attribute in accordance with Bayesian's rule, such that a conditional probability of each sound type is defined for an occurrence of each attribute.

Abstract: An apparatus for facilitating avoidance of a vehicle collision with an object, comprises a vision sensor providing image data, and an image analyzer, operable to provide an estimated time to collision of the vehicle with the object. The estimated time to collision is determined from a rate of expansion of an image element corresponding to the object within the image data, and the apparatus provides a warning if the estimated time to collision is less than or approximately equal to a predetermined time.

Abstract: An apparatus for facilitating avoidance of a vehicle collision with an object, comprises a vision sensor providing image data, and an image analyzer, operable to provide an estimated time to collision of the vehicle with the object. The estimated time to collision is determined from a rate of expansion of an image element corresponding to the object within the image data, and the apparatus provides a warning if the estimated time to collision is less than or approximately equal to a predetermined time.