Apparatus for determining the ground speed of a vehicle, comprising a plurality of sensing systems each of which is configured to provide a respective data source indicative of the ground speed of the vehicle; a controller configured to receive each of the data sources from the plurality of sensing systems; wherein the controller is configured to arbitrate between the received plurality of data sources from the plurality of sensing systems, determine a ground speed parameter from one of the data sources, and output the ground speed parameter for use within the vehicle. The invention also resides in a method for determining the ground speed of a vehicle and a computer program product that embodies said method.

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 first vehicle in traffic can use machine learning and artificial intelligence to detect an imminent collision with a second vehicle or other object. A well-trained AI algorithm can select a sequence of actions (braking, swerving, or acceleratingdepending on the specific kinetics) to avoid the collision if possible, and to reduce or minimize the harm if unavoidable. With proper training, the AI model may also infer the intent and future actions of the second vehicle, as well as potential interference of other traffic agents. A good algorithm can also infer the intent of the driver of the first vehicle, for example based on prior driving habits. The AI algorithm may be implemented in a processor on the subject vehicle, potentially in communication with another processor at a fixed site such as a local access point or a central supercomputer. With super-fast AI solutions, lives will be saved!

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 first phantom vehicle is projected into one of a branch and a circle lane of a roundabout in association with a first autonomous vehicle. The first autonomous vehicle is caused to enter the circle lane upon predicting no collision with oncoming vehicles. The first autonomous vehicle is caused to exit from the roundabout.

A method and/or computer program product controls an operational mode of a self-driving vehicle (SDV) that is initially being operated in a nominal autonomous mode. Detectors on an SDV detect an erratically driven vehicle (EDV) that is being operated in an unsafe manner within a predetermined distance of an SDV. In response to detecting the EDV, a driving mode device in the SDV changes an operational mode of the SDV from the nominal autonomous mode to an evasive autonomous mode.

A method controls an operational mode of a self-driving vehicle (SDV). One or more physical detectors detect an erratically driven vehicle (EDV) that is being operated in an unsafe manner within a predetermined distance of an SDV that is initially being operated in an evasive autonomous mode. One or more processors retrieve traffic pattern data for other SDVs, and examine the traffic pattern data to 1) determine a first traffic flow of the other SDVs while operating in the evasive autonomous mode, and 2) determine a second traffic flow of the other SDVs while operating in a manual mode. In response to determining that the first traffic flow has a higher accident rate than the second traffic flow, an operational mode device changes the operational mode of the SDV from the evasive autonomous mode to the manual mode.

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.

An adaptive vehicle control system that includes processors, memory modules communicatively coupled to the processors, and machine readable instructions stored in the one or more memory modules that cause the adaptive vehicle control system to determine an autonomous operation profile of a target vehicle positioned in a vehicle operating environment, wherein the vehicle operating environment includes a roadway having one or more lanes, determine an autonomous operation profile of one of more neighboring vehicles positioned within the vehicle operating environment, compare the autonomous operation profile of at least one of the one or more neighboring vehicles with the autonomous operation profile of the target vehicle, and alter a condition of the target vehicle such that the autonomous operation profile of the target vehicle matches an autonomous operation profile of an individual neighboring vehicle of the one or more neighboring vehicles positioned in the same lane as the target vehicle.