A vehicle and method for controlling the same may include a speed detector configured to detect driving speed of the vehicle, a detection sensor configured to detect a target vehicle around the vehicle and obtain information about at least one of position and speed of the target vehicle, and a controller configured to determine a steering-based avoidance path for the vehicle to avoid the target vehicle by being steered, determine a maximum lateral acceleration of the vehicle for the vehicle to avoid the target vehicle in the steering-based avoidance path, and send a control signal for steering-based avoidance of the vehicle to avoid a collision with the target vehicle based on the determined maximum lateral acceleration.

Solar power generation panels added on a transportation vehicle have a layout wherein power output of the panels varies according to an azimuth orientation of the vehicle. A controller includes a database of calibration curves relating an expected power output to a respective range of the azimuth orientation according to different solar altitude angles. A self-learning sequence is performed which (a) collects a magnitude of power output while the vehicle traverses the respective range of the azimuth orientation, (b) identifies a current solar altitude angle, and (c) stores a resulting calibration curve. A parking sequence comprises (a) selecting a calibration curve according to solar altitude angle, (b) determining a target vehicle azimuth angle which optimizes a cumulative power output based on the calibration curve and solar azimuth, and (d) initiating a movement of the vehicle to orient it at the target vehicle azimuth angle.

A vehicle recognition device includes: an acquisition section acquiring image information based on an image captured by a vehicle-mounted camera; a boundary line detection section detecting, based on the image information, boundary lines on both left and right sides demarcating vehicle traveling lanes; a vehicle detection section detecting position information on an object vehicle; and a recognition section recognizing lane-to-lane movement of the object vehicle between an own lane in which the subject vehicle is traveling and an adjacent lane. The recognition section recognizes the lane-to-lane movement based on a second boundary line of the boundary lines, a lane width between a first boundary line of the boundary lines and the second boundary line, and the position information on the object vehicle, the first boundary line dividing the own lane and the adjacent lane, the second boundary line being different from the first boundary line.

An off-road dump truck includes a vehicle body, a peripheral recognition device, and an obstacle discrimination device. The peripheral recognition device detects obstacle candidates in front of the vehicle body. The obstacle discrimination device classifies the obstacle candidates, which were detected by the peripheral recognition device, into obstacles and non-obstacles and outputs, as obstacles, the obstacle candidates classified as obstacles. The obstacle discrimination device includes a travel state determination section, a distance filter section, and a reflection intensity filter section. The travel state determination section determines whether each obstacle candidate is a moving object or a stationary object. The distance filter section compares a distance, where the stationary object was first detected, with a distance threshold. The reflection intensity filter section calculates statistical information based on reflection intensity information on the obstacle candidate, and based on a comparison result of the statistical information with a threshold, classifies the obstacle candidate.

A computer-implemented method for controlling a vehicle system of a host vehicle merging into a lane. The method includes determining an actual distance between the host vehicle and the one or more remote vehicles. The actual distance is a longitudinal distance between the host vehicle and the one or more remote vehicles. The method includes determining a safe distance for merging into the lane based on a relative position of the host vehicle to the one or more remote vehicles, a speed of the host vehicle, and a speed of the one or more remote vehicles. The safe distance is a second longitudinal distance between the host vehicle and the one or more remote vehicles. The method includes controlling the vehicle system of the host vehicle to assist a merge maneuver by the host vehicle according to the actual distance and the safe distance.

An ECU performs collision avoidance control for an avoiding collision with an object based on at least one of first information, which is a detection result of the object based on a reflected wave corresponding to a transmission wave, and second information, which is a detection result of the object based on a captured image of an area in front of a vehicle captured by an image capturing means. When the state changes from a state where the object is detected by the first information and the second information to a state where the object is detected only by the first information, the ECU determines whether or not the object is located in a near area predetermined as an area in front of the vehicle in which the second information is not be able be acquired. When it is determined that the object is located in the near area, the ECU maintains an activation condition of the collision avoidance control to that in the state where the object is detected by the first information and the second information.

An autonomous driving system acquires information concerning an empty space situation in an adjacent lane, and information concerning an entry frequency with which other vehicles enter into an own lane from the adjacent lane, when an own vehicle travels on a road having a plurality of lanes. The autonomous driving system determines whether or not to select the adjacent lane as an own vehicle travel lane in accordance with the empty space situation in the adjacent lane and the entry frequency. However, when the entry frequency is a threshold value or more, determination not to select the adjacent lane as the own vehicle travel lane is kept irrespective of the empty space situation in the adjacent lane. The autonomous driving system performs lane change to the adjacent lane autonomously when the adjacent lane is selected as the own vehicle travel lane.

A system for creating a driving route of a vehicle includes: a vehicle selecting device to select a surrounding vehicle that is adjacent to a host vehicle; an intention determining device to determine an intention of the surrounding vehicle by using information including a location and a speed of the surrounding vehicle; a driving route predicting device to predict a driving route of the surrounding vehicle based on the determined intention of the surrounding vehicle; a map creating device to create a map by using the predicted driving route of the surrounding vehicle; and a driving route creating device to create a driving route of the host vehicle.

A vehicle environment detection system in an ego vehicle, including a sensor arrangement and a main control unit is arranged to detect and track at least one oncoming vehicle, and to determine whether the ego vehicle has entered a curve. The main control unit is arranged to determine a common curve with a radius, along which common curve the ego vehicle is assumed to travel, determine a measured oncome direction of the oncoming vehicle on the common curve, corresponding to an oncome angle, determine a difference angle between the measured oncome direction and an oncome direction corresponding to if the oncoming vehicle would be moving along the common curve, compare the difference angle with a threshold angle, and to determine that the oncoming vehicle is crossing if the difference angle exceeds the threshold angle.

A method and system for target detection of a vehicle is proposed. In the method and system, when the vehicle is turning, a warning signal according to a risk level of collision is generated at the right timing as a risk level of collision between the host vehicle and the other vehicle behind the host vehicle may be accurately identified by correcting a driving path of the host vehicle and position of the other vehicle on the basis of a driving state of the host vehicle.