A vehicle collision avoidance assist apparatus keeps stopping a collision avoidance control when a forbiddance condition is satisfied, and a collision condition is satisfied. The forbiddance condition is a condition that the collision angle is equal to or greater than a predetermined collision angle threshold. The collision condition is a condition that an own vehicle is going to collide with an object. While the own vehicle turns, the apparatus acquires an own vehicle turning angle which the own vehicle has turned about a turning center from when the own vehicle starts turning and sets the predetermined collision angle threshold such that the predetermined collision angle threshold set for the greater own vehicle turning angle is smaller than the predetermined collision angle threshold set for the smaller own vehicle turning angle.

A vehicle collision avoidance assist apparatus keeps stopping a collision avoidance control to avoid a collision of an own vehicle with an object ahead of the own vehicle when the own vehicle turns, a predetermined condition is satisfied, and a collision condition is satisfied. While the own vehicle turns, the apparatus acquires an own vehicle turning angle which is an angle which the own vehicle has turned about a turning center from when the own vehicle starts turning and change the predetermined condition, depending on the own vehicle turning angle.

Systems and methods for identifying objects in an environment of a host vehicle are disclosed. In one implementation, a system includes a processor configured to receive images representative of the environment of the host vehicle; assign first pixel descriptor values to a plurality of pixels associated with a first image and second pixel descriptor values to a plurality of pixels associated with a second image; identify object representations in the first image and the second image based on at the first pixel descriptor values and the second pixel descriptor values, respectively; determine a first object descriptor and a second object descriptor based on the first pixel descriptor values and the second pixel descriptor values, respectively; and based on a comparison of the first object descriptor and the second object descriptor, output an indication that the object representations in the first image and the second image represent a common object.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that determine yield behavior for an autonomous vehicle. An agent that is in a vicinity of an autonomous vehicle can be identified. An obtained crossing intent prediction characterizes a predicted likelihood that the agent intends to cross a roadway during a future time period. First features of the agent and of the autonomous vehicle are obtained. An input that includes the first features and the crossing intent prediction is processed using a machine learning model to generate an intent yielding score that represents a likelihood that the autonomous vehicle should perform a yielding behavior due to the intent of the agent to cross the roadway. From at least the intent yielding score, an intent yield behavior signal is determined and indicates whether the autonomous vehicle should perform the yielding behavior prior to reaching the first crossing region.

A vehicle driving assistance device includes a processor. The processor is configured to execute acceleration suppression control for suppressing acceleration of a driver's vehicle in a case where a predetermined prohibition condition is not satisfied when an erroneous acceleration operation precondition is satisfied while a traveling condition is satisfied. The traveling condition is a condition for determining that the driver's vehicle is traveling. The erroneous acceleration operation precondition is a precondition for determining that an acceleration operation is erroneously performed. The acceleration operation is an operation performed by a driver of the driver's vehicle to request the acceleration of the driver's vehicle. The predetermined prohibition condition is based on a relationship between the driver's vehicle and an external environment of the driver's vehicle.

A system for controlling operation of a vehicle during a turning maneuver includes an object detection sensor, a vehicle turning angle sensor, and a processor. A memory is communicably coupled to the processor and stores a turning alert zone module configured to determine if a speed of the vehicle is within a predetermined range of speeds and, if the speed of the vehicle is within the predetermined range of speeds, determine if a vehicle turning angle is above a predetermined threshold value. If the turning angle is above the predetermined threshold value, and using the turning angle, a turning alert zone is determined. The system may then determine if at least a portion of an object resides in the turning alert zone and, if at least a portion of an object resides in the turning alert zone, control an operation of the vehicle (for example, a braking operation).

A driving assistance system for a vehicle, comprising: a detection unit configured to detect information regarding surroundings of the vehicle; and a control unit configured to perform driving assistance control based on information detected by the detection unit, wherein, when the control unit performs an operation of stopping movement due to an object detected by the detection unit during the driving assistance control, the control unit restarts the movement after a predetermined time elapses from when the stop operation is started.

Method and systems for generating vehicle motion planning model simulation scenarios are disclosed. The method receives a base simulation scenario with features of a scene through which a vehicle may travel, defines an interaction zone in the scene, generates an augmentation element that includes an object and a behavior for the object, and adds the augmentation element to the base simulation scenario at the interaction zone to yield an augmented simulation scenario. The augmented simulation scenario is applied to a vehicle motion planning model to train the model.

A motion detection device includes a plurality of sensor electrodes configured to detect static capacitance, and a sensor bracket to which the plurality of sensor electrodes are attached. The sensor bracket is provided with an engagement portion to be engaged with an engaged portion of each of the sensor electrodes. The engagement portion of the sensor bracket and the engaged portion of the sensor electrode are formed in a shape that allows mutual engagement between regular combinations and regulates mutual engagement other than the regular combinations.

A pedestrian protection apparatus may include: an active sensor configured to sense a forward obstacle of a vehicle; a passive sensor configured to sense a collision of the vehicle; a storage unit configured to store a collision threshold value which is set according to the passive sensor and a protection subject; a protection module driving unit configured to drive a protection module for protecting the protection subject in case of a collision with the vehicle; and a control unit configured to identify the protection subject based on the sensing result of the active sensor, adjust the collision threshold value according to the protection subject, compare the sensing result of the passive sensor to the collision threshold value, and operate the protection module driving unit.