A vehicle driving behavior monitoring and warning system that includes a host vehicle having a communication device that receives operating information of remote vehicles that are located within a predetermined zone of interest, a warning device and an electronic controller. The electronic controller is connected to the communication device and the warning device. The electronic controller evaluates operating information received by the communication device and determine whether or not one of the remote vehicles is operating with questionable driving behavior and determines whether or not the remote vehicle poses a potential threat to the host vehicle. In response to determining that the remote vehicle is operating with questionable driving behavior and poses a potential threat to the host vehicle, the electronic controller operates the warning device warning the operator of the host vehicle of the remote vehicle.

A method for determining a distance between a camera positioned on a rear portion of a tow vehicle and a trailer coupler supported by a trailer positioned behind the tow vehicle as the tow vehicle approaches the trailer. The method includes identifying the trailer coupler of the trailer within one or more images of a rearward environment of the tow vehicle. The method also includes receiving sensor data from an inertial measurement unit supported by the tow vehicle. The method includes determining a pixel-wise intensity difference between a current received image from the one or more images and a previously received image from the one or more images. The method includes determining the distance based on the identified trailer coupler, the sensor data, and the pixel-wise intensity difference, the distance includes a longitudinal distance, a lateral distance, and a vertical distance.

A motion planner performs motion planning with collision assessment, using a motion planning lattice that represents configuration states of a primary agent (e.g., autonomous vehicle) as nodes and transitions between states as edges. The system may assign cost values to edges, the cost values representing probability or likelihood of collision for the corresponding transition. The cost values may additionally or alternatively represent a severity of collision, for example generated via a parametric function with two or more parameters and one or more weights. A primary agent and/or dynamic obstacles may be represented as respective oriented bounding boxes. Some obstacles (e.g., road markings, edge of road) may be represented as curves. A trajectory of a primary agent and/or dynamic obstacle may be represented by respective sets of fitted polynomial functions, edges on the planning graph, which represent transitions in states of the primary agent, the system sets value representing a probability of collision, and optionally representing a severity of the collision. The system then causes the actuator system of the primary agent to implement a motion plan with the applicable identified path based at least in part on the optimization.

A vehicle exterior environment recognition apparatus includes a travel path derivation unit, a speed derivation unit, and a follow-up controller. The travel path derivation unit estimates an own-vehicle travel path and derives a target-vehicle travel path that contains a point on a target vehicle and forms a parallel curve to the own-vehicle travel path. The speed derivation unit derives a target-vehicle speed vector. The follow-up controller makes a follow-up control based on the target-vehicle speed vector on the condition that an angle formed by the target-vehicle speed vector and a tangential line to the target-vehicle travel path at the point on the target vehicle falls within a predetermined angular range, and makes the follow-up control based on a tangential speed component of the target-vehicle speed vector on the condition that the angle falls out of the angular range.

A self-localization estimation unit of a self-localization estimation device determines, based on mutual relationships between the in-lane position and the absolute position including the error, whether there is lane-relevant candidate information, the lane-relevant candidate information representing that one or more in-vehicle positions are each estimated to be in which of lanes identified by the lane information; and estimates, based on a result of the determination of whether there is lane-relevant candidate information, a localization of the own vehicle corresponding to the map information.

A method for matching a reference object and a test object includes providing a test object in a field of sensing of at least one sensor disposed at a vehicle. A volume match is determined based on a volume of the reference object and a volume of the test object. A distance match is determined based on a center and orientation of the reference object and a center and orientation of the test object. An angle match is determined based on a yaw angle of the reference object and a yaw angle of the test object. A superposition of the volume match, the distance match, and the angle match is determined based on a multiplication of the volume match, the distance match, and the angle match. A degree of matching of the reference object and the test object is determined based on the superposition.

A hazard prediction and a hazard avoidance procedure are performed based on a predetermined hazard avoidance condition during an autonomous driving operation of a vehicle. User-input information about a driving operation of the vehicle; is received, and area or object information is checked to determine the area or the object as a monitoring target. The monitoring target is tracked. At least one additional hazard avoidance procedure for the monitoring target is set, and the at least one additional hazard avoidance procedure is performed in addition to the hazard avoidance procedure when the monitoring target approaches the vehicle.

Disclosed are a short cut-in target identification apparatus and an identification method thereof. The short cut-in target identification apparatus includes an occupancy distance map (ODM) information calculator configured to calculate ODM information based on subject vehicle and surrounding object information, a track information calculator configured to calculate track information based on the subject vehicle and surrounding object information, and a short cut-in target selector configured to select a short cut-in target based on the ODM information and the track information.

A vehicle driving behavior monitoring and warning system that includes a host vehicle having a communication device that receives operating information of remote vehicles that are located within a predetermined zone of interest, a warning device and an electronic controller. The electronic controller is connected to the communication device and the warning device. The electronic controller evaluates operating information received by the communication device and determine whether or not one of the remote vehicles is operating with questionable driving behavior and determines whether or not the remote vehicle poses a potential threat to the host vehicle. In response to determining that the remote vehicle is operating with questionable driving behavior and poses a potential threat to the host vehicle, the electronic controller operates the warning device warning the operator of the host vehicle of the remote vehicle.

A cruise control apparatus controls travel of an own vehicle based on a predicted course which is a future travel course of the own vehicle. The cruise control apparatus includes a first predicted course calculating unit and a second predicted course calculating unit, as a plurality of course prediction means for calculating a predicted course, and is provided with a course change determination unit for determining whether a change in the course is to be performed and a prediction switching unit which performs switching to enable one of a first predicted course calculated by the first predicted course calculating unit and a second predicted course calculated by the second predicted course calculation unit, the switching being based on a result of determination made by the course change determination unit as to whether a change in the course is to be performed.