A vehicle driving assist apparatus acquires a longitudinal distance between an own vehicle and an oncoming vehicle, and a lateral distance between the own vehicle and the oncoming vehicle. The vehicle driving assist apparatus acquires a collision index value which decreases as a ratio of the longitudinal distance to the lateral distance decreases and determine that the own vehicle potentially collides with the oncoming vehicle when a turning condition is satisfied, and a collision condition is satisfied. The turning condition is a condition that the own vehicle turns, crossing an oncoming traffic lane. The collision condition is a condition that the collision index value is within a predetermined index value range. The predetermined index value range at least includes the collision index value acquired when the longitudinal distance is equal to the lateral distance.

In a target identification device, an acquisition unit is configured to acquire trajectory information including information on a movement trajectory of a moving object in the surroundings of a vehicle. A calculation unit is configured to calculate a likelihood for each type of moving object from the trajectory information by using a plurality of models predefined for each type of moving object. A target identification unit is configured to identify the type of the moving object according to the likelihood calculated by the calculation unit.

A collision avoidance assistance device includes a first determination section that determines a probability that a vehicle changes course, by using a recognition result of a road structure and a detection result by internal field sensors, a second determination section that determines a probability that the vehicle changes course, by using information related to a traveling situation output, a decision section that decides an operation mode of collision avoidance assistance using a collision avoidance assistance mechanism, by using a combination of a determination result of the first determination section and a determination result of the second determination section, and an assistance section that performs a process for controlling the collision avoidance assistance mechanism in the operation mode that has been decided by the decision section, upon detection of a collision probability with an obstacle using the information output by information output devices.

A method for the automatic control of the longitudinal dynamics of a vehicle is provided by which vehicles traveling ahead are detected. If an upcoming traffic jam is detected, the vehicle is decelerated until a predefined distance behind the tail end of the traffic jam is reached. When the predefined distance from the traffic jam tail end has been reached, the vehicle automatically controlled in its longitudinal dynamics is able to close the remaining, predefined distance to the traffic jam tail end at a low differential velocity in comparison to the velocity of the traffic jam tail end. Using an additional rear sensor system that senses trailing vehicles, the controlled vehicle is made to close the distance to the traffic jam tail end only if a trailing vehicle was detected.

Aspects of the technology relate to exception handling for a vehicle. For instance, a current trajectory for the vehicle and sensor data corresponding to one or more objects may be received. Based on the received sensor data, projected trajectories of the one or more objects may be determined. Potential collisions with the one or more objects may be determined based on the projected trajectories and the current trajectory. One of the potential collisions that is earliest in time may be identified. Based on the one of the potential collisions, a safety-time-horizon (STH) may be identified. When a runtime exception occurs, before performing a precautionary maneuver to avoid a collision, waiting no longer than the STH for the runtime exception to resolve.

A lane keeping assistance system including position means for determining a first position of the vehicle in a network with a first accuracy; first interface for providing trajectory of the vehicle in the network; second interface for providing position data of right boundary objects and position data of left boundary objects, and radar signatures of these boundary objects; radar system to scan right and left lateral environments of the vehicle and determine distances to objects on a right of the vehicle and radar signatures thereof, and distances to objects on a left of the vehicle and radar signatures thereof; evaluation unit to perform identification of acquired objects based on the first position, the provided data, and the determined data, and to determine a second position of the vehicle with a second position accuracy; and control device to control the vehicle taking into consideration the target trajectory and the second position.

In a vehicle control apparatus, a gradient calculator calculates a gradient difference between a reference gradient of a reference road section of an own vehicle and a target gradient of an objective road section of an image-detected object. A corrector corrects, based on the calculated gradient difference, second location information about the image-detected object measured by an imaging device to thereby correct a second distance of the image-detected object relative to the own vehicle. A determiner determines whether a radar-based object is identical with the image-detected object in accordance with first location information about the image-detected object measured by a radar device and the corrected second location information about the image-detected object.

A vehicle situation determination device includes an input unit and a controller. The input unit receives information about a recognition result of recognizing one or a plurality of moving objects existing in a sidewalk region ahead of a vehicle in an advancing direction. The controller determines, based on the recognition result, that the vehicle is allowed to enter a passing scheduled region in a time period of a sparse state when a transition is made from the sparse state into a dense state. The sparse state is a state where density of the one or plurality of moving objects existing in the passing scheduled region is lower than or equal to a predetermined value. The dense state is a state where the density is higher than the predetermined value.

A vehicle control system includes: an automated driving controller that is configured to execute automated driving of automatedly controlling at least one of speed control and steering control of a vehicle; an estimator that is configured to estimate a degree of wakefulness of a vehicle occupant of the vehicle; and an output controller that is configured to cause an outputter to output a first content requiring the vehicle occupant of the vehicle engage in active behavior in a case in which the degree of wakefulness is estimated as being equal to or lower than a criterion by the estimator when the automated driving is executed by the automated driving controller, whereby the degree of wakefulness of the vehicle occupant of the vehicle can be maintained at a necessary level or higher in automated driving.

A sensing system for a vehicle includes at least one radar sensor disposed at the vehicle and having a field of sensing exterior of the vehicle. The at least one radar sensor includes an array of multiple transmitting antennas and multiple receiving antennas. A control is responsive to the outputs of the at least one radar sensor and determines the presence of one or more other vehicles exterior the vehicle and within the field of sensing of the at least one radar sensor. Lane markers may be determined via a vision system of the equipped vehicle. The control determines range and relative lane position of a detected other vehicle relative to the equipped vehicle and determined lane markers, and the sensing system may anticipate a lane change, cut-in or merge intent of the detected other vehicle.