An agricultural system includes a target vehicle configured to harvest crops and a work vehicle. The work vehicle includes a controller. The controller includes a memory and a processor, and the controller is configured to receive or determine a plurality of vehicle paths as well as a location of the target vehicle. The controller is also configured to identify an active path of the plurality of vehicle paths based on the location of the target vehicle. The target path is a path traversed by the target vehicle.

An autonomous vehicle safety system may activate to prevent collisions by detecting that a planned trajectory may result in a collision. If the safety system is overly sensitive, it may cause false positive activations, and if the system isn't sensitive enough the collision avoidance system may not activate and prevent a collision, which is unacceptable. It may be impossible or prohibitively difficult to detect false positive activations of a safety system and it is unacceptable to risk a false negative, so tuning the safety system is notoriously difficult. Tuning the safety system may include detecting near-miss events using surrogate metrics, and tuning the safety system to increase or decrease a rate of near-miss events as a stand-in for false positives.

A method of operating a vehicle, such as an autonomous vehicle, includes the steps of receiving a message from roadside infrastructure via an electronic receiver and providing, by a computer system in communication with said electronic receiver, instructions based on the message to automatically implement countermeasure behavior by a vehicle system. Additionally or alternatively, the method may include the steps of receiving a message from another vehicle via an electronic receiver and providing, by a computer system in communication with said electronic receiver, instructions based on the message to automatically implement countermeasure behavior by a vehicle system.

Systems, components, and methodologies are provided for improvements in operation of automotive vehicles by enabling monitoring analysis and reaction to subtle sources of information that aid in prediction and response of vehicle control systems across a range of automation levels. Such systems, components, and methodologies include wheel-turn detection equipment for detecting a wheel angle of another vehicle to trigger a vehicle control system to perform an operation based on the detected wheel angle of the other vehicle.

A driver assistance method for an ego vehicle (EGO) travelling in a traffic lane, includes: identifying traffic surrounding the ego vehicle in the same traffic lane as the ego vehicle and in adjacent parallel lanes travelling in the same direction; determining a virtual barycentric target, including calculating a position of the virtual barycentric target, a speed of the virtual barycentric target, and an acceleration of the virtual barycentric target; calculating a longitudinal speed setpoint of the ego vehicle, an acceleration setpoint, and a torque setpoint, the longitudinal speed setpoint being a function of the position of the virtual barycentric target, the speed of the virtual barycentric target, and the acceleration of the virtual barycentric target.

A vehicle control device includes a first control unit that executes, when an abnormality of a driver of a vehicle is detected, stop control, a second control unit that executes, when the vehicle is determined to have a risk of collision, deceleration control, a determination unit that identifies an object around the vehicle as a target candidate of the collision and determines whether or not there is the risk of the collision with the identified target candidate, and a setting unit that sets, when the abnormality is detected, an operation mode of the deceleration control to a special mode from a normal mode, the normal mode provided for cases in which the abnormality is undetected. The determination unit expands a range for identifying the object around the vehicle as the target candidate of the collision in the special mode as compared with the range in the normal mode.

A deceleration support device in which an electronic control unit controls a speed reduction device to execute automatic deceleration control when an object that requires deceleration of a vehicle is detected and a braking/driving operation is not detected, and interrupt the automatic deceleration control when a driving operation is detected in a situation where the automatic deceleration control is being executed, and with an object that requires deceleration of the vehicle and does not prevent the vehicle from passing through a position of the object being defined as a specific object, the electronic control unit resumes the automatic deceleration control if it is determined that the object is not a specific object, but does not resume the automatic deceleration control if it is determined that the object is a specific object, when the driving operation is not detected in a situation where the automatic deceleration control is interrupted.

According to an aspect of the present disclosure, a collision warning apparatus of a vehicle may include an information acquisition device that obtains surrounding object information and vehicle information and a controller that generates collision prediction information of a surrounding object based on the surrounding object information and the vehicle information and provides a warning to an outside of the vehicle or generates control information for controlling braking of the vehicle while providing the warning to the outside of the vehicle based on the collision prediction information.

Systems and methods for distracted driving detection are described. A method includes receiving proximate vehicle data about a proximate vehicle proximate to the host vehicle. The method also includes estimating one or more baselines for a predetermined future time for the proximate vehicle from the proximate vehicle data. The method further includes comparing current kinematic data of the proximate vehicle data for the predetermined future time to the one or more baselines. The method includes generating distraction flags associated with the proximate vehicle based on the comparison. The method also includes controlling one or more vehicle systems of the host vehicle based on the generated distraction flags.

Path generation apparatus configured to generate target path of own vehicle traveling in own lane, includes: sensor configured to detect objects in surrounding area of own vehicle; and electronic control unit including processor and memory. Electronic control unit is configured to perform: recognizing adjacent vehicle traveling in adjacent lane adjacent to own lane from among detected objects; determining whether own lane is congested based on travel speed of own vehicle and determining whether adjacent lane is congested based on recognition result of adjacent lane; and generating target path of own vehicle. Generating target path includes generating target path on side away from adjacent lane with respect to that of case where own lane is determined to be congested and adjacent lane is determined to be congested, in case where own lane is determined to be congested and adjacent lane is determined not to be congested.