A system and method to avoid collisions on highways, and to minimize the fatalities, injury, and damage when a collision is unavoidable. The system includes sensor means to detect other vehicles, and computing means to evaluate when a collision is imminent and to determine whether the collision is avoidable. If the collision is avoidable by a sequence of controlled accelerations and decelerations and steering, the system implements that sequence of actions automatically. If the collision is unavoidable, a different sequence is implemented to minimize the overall harm of the unavoidable collision. The system further includes indirect mitigation steps such as flashing the brake lights automatically. An optional post-collision strategy is implemented to prevent secondary collisions, particularly if the driver is incapacitated. Adjustment means enable the driver to set the type and timing of automatic interventions.

A system and method to avoid collisions on highways, and to minimize the fatalities, injury, and damage when a collision is unavoidable. The system includes sensor means to detect other vehicles, and computing means to evaluate when a collision is imminent and to determine whether the collision is avoidable. If the collision is avoidable by a sequence of controlled accelerations and decelerations and steering, the system implements that sequence of actions automatically. If the collision is unavoidable, a different sequence is implemented to minimize the overall harm of the unavoidable collision. The system further includes indirect mitigation steps such as flashing the brake lights automatically. An optional post-collision strategy is implemented to prevent secondary collisions, particularly if the driver is incapacitated. Adjustment means enable the driver to set the type and timing of automatic interventions.

Implementations a method using a collision detection device associated with a user to detect a moving object in an environment and provide an alert to the user are provided. In some implementations the environment comprises at least one transmitter of opportunity. In some implementations, the collision detection device comprises a receiver and a processor. In some implementations, the method comprises receiving at the collision detection device Wi-Fi signals reflected from the moving object where the Wi-Fi signals originate from a Wi-Fi source not associated with the moving object. The method further comprises detecting, measuring, and tracking the Doppler effect of the Wi-Fi signals at the collision detection device to track velocity vector relative to the collision detection device. The method further comprises calculating the time of arrival of the moving object based on the velocity vector relative to the location of the collision detection device. The method further comprises tracking the relative angle between the moving object and the collision detection device based on the velocity vector. The method further comprises predicting the occurrence of a collision between the moving object and the collision detection device based on the relative angle. The method further comprises providing a notification based on the predicting step.

In one embodiment, a process is performed during controlling Autonomous Driving Vehicle (ADV). Microphone signals sense sounds in an environment of the ADV. The microphone signals are combined and filtered to form an audio signal having the sounds sensed in the environment of the ADV. A neural network is applied to the audio signal to detect a presence of an audio signature of an emergency vehicle siren. If the siren is detected, a change in the audio signature to make a determination as to whether the emergency vehicle siren is a) moving towards the ADV, or b) not moving towards the ADV. The ADV can make a driving decision, such as slowing down, stopping, and/or steering to a side, based on if the emergency vehicle siren is moving towards the ADV.

A driver state detection device that accurately detects a state of a driver, such as fatigue and nodding off. A driver state detection device includes an acceleration sensor installed in a vehicle, a center-of-gravity movement amount detection unit that is attached to a component constituting the vehicle and detects a center-of-gravity movement amount of a body of a driver on the vehicle, and a driver state determination unit that determines a state of the driver based on magnitude of an amount of deviation between an acceleration of the vehicle obtained by the acceleration sensor and the center-of-gravity movement amount of the body of the driver detected by the center-of-gravity movement amount detection unit.

Embodiments of the invention are directed to a computer-implemented method that includes determining, by a vehicle controller associated with a vehicle, a typical driving behavior of a driver of the vehicle. The method also includes detecting, by the vehicle controller associated with the vehicle, that the driver has deviated from the typical driving behavior. The method also includes transmitting a notification that indicates that the driver has deviated from the typical driving behavior.

Implementations a method using a collision detection device associated with a user to detect a moving object in an environment and provide an alert to the user are provided. In some implementations the environment comprises at least one transmitter of opportunity. In some implementations, the collision detection device comprises a receiver and a processor. In some implementations, the method comprises receiving at the collision detection device Wi-Fi signals reflected from the moving object where the Wi-Fi signals originate from a Wi-Fi source not associated with the moving object. The method further comprises detecting, measuring, and tracking the Doppler effect of the Wi-Fi signals at the collision detection device to track velocity vector relative to the collision detection device. The method further comprises calculating the time of arrival of the moving object based on the velocity vector relative to the location of the collision detection device. The method further comprises tracking the relative angle between the moving object and the collision detection device based on the velocity vector. The method further comprises predicting the occurrence of a collision between the moving object and the collision detection device based on the relative angle. The method further comprises providing a notification based on the predicting step.

A method of processing data for a driving automation system, the method comprising steps of: obtaining sound data from a microphone of an autonomous vehicle; processing the sound data to obtain a sound characteristic; and updating a context of the autonomous vehicle based on the sound characteristic.

A method for detecting non-visible vehicles in a vehicle's environment, wherein each vehicle is equipped with at least one proximity sensor, the method comprising for a driven vehicle the steps of: screening, by a receiver of the proximity sensor, any incoming proximity signal capable of propagating through the air along a non-linear path; Receiving an incoming proximity signal coming from a non-visible vehicle (B); processing the received proximity signal to detect the non-visible vehicle; and warning a driver and/or an advanced driver-assistance system about the detected non-visible vehicle.

A method is disclosed to operate a motor vehicle using a driver assistance system. The driver assistance system includes, for at least one driver assistance system function, at least one criterion relating to a vehicle environment. The at least one criterion is defined for an adaptation of the driver assistance system function, a number of features of the environment of the vehicle are detected, a probability of the occurrence of at least one criterion is estimated on the basis of a combination of the detected features, and the driver assistance system function is adapted on the basis of the estimated probability.