A vehicle driving assist device includes a processor that functions as a receiver, an emergency collision avoidance controller, and a preliminary collision avoidance controller. The receiver receives, in relation to an oncoming moving body moving in an oncoming lane adjacent to a traveling lane of a vehicle and having a velocity component in a direction opposite to a traveling direction of the vehicle, a risk degree calculated based on a history of a distance from a lane marker defining the oncoming lane to the oncoming moving body, by communication with a device outside the vehicle. Upon determination that the vehicle is highly likely to collide with an obstacle, the emergency collision avoidance controller performs emergency collision avoidance control. The preliminary collision avoidance controller recognizes the oncoming moving body as the obstacle in accordance with the risk degree, and performs preliminary control prior to the emergency collision avoidance control.

A vehicular sensing system includes a camera and a radar sensor disposed at a vehicle. The system, responsive to processing of radar data captured by the radar sensor, determines an edge of a road the vehicle is traveling along. Responsive to processing of image data captured by the camera, location of a lane marking of the road is determined. As the vehicle travels along the road, the system, responsive to failing to determine the location of the lane marking of the road via processing of the image data captured by the camera, predicts the location of the lane marking of the road based on the radar data. The vehicle is controlled based in part on the predicted location of the lane marking of the road.

Techniques for determining a location and type of traffic-related features and using such features in route planning are discussed herein. The techniques may include determining that sensor data represents a feature such as a traffic light, road segment, building type, and the like. The techniques further include determining a cost of a feature, whereby the cost is associated with the effect of a feature on a vehicle traversing an environment. A feature database can be updated based on features in the environment. A cost of the feature can be used to update costs of routes associated with the location of the feature.

In one or more embodiments, a method comprises receiving, at a processor, an input signal from an input device in response to a first actuation of the input device by a driver of an autonomous vehicle. The input device is a device disposed with the autonomous vehicle and has a second actuation of the input device associated with a standard operation of the input device. The second actuation has an actuation pattern different from an actuation pattern of the first actuation. In response to the input signal, a determination is made by the processor to determine whether the autonomous vehicle can perform a maneuver safely. In response to determining that the autonomous vehicle can perform the maneuver safely, a signal is sent by the processor to cause the autonomous vehicle to perform the maneuver.

This application relates to the automated driving field, and discloses a method for identifying abnormal driving behavior, a system, and a vehicle including the system. The method for identifying abnormal driving behavior includes: obtaining vehicle driving behavior data, and determining, based on the vehicle driving behavior data, whether a vehicle is in a state of suspicious abnormal driving behavior; obtaining current vehicle driving scenario data if the vehicle is in the state of suspicious abnormal driving behavior; and determining, based on the vehicle driving behavior data and the current vehicle driving scenario data, whether the suspicious abnormal driving behavior is abnormal driving behavior. In the technical solutions of this application, current driving scenario information is introduced to an identification process of abnormal driving behavior of the vehicle, so that accuracy of identifying the abnormal driving behavior is improved.

A vehicle display device, includes: a curve information acquisition section configured to acquire information relating to a degree of curvature of a travel lane; a deceleration determination section configured to determine whether or not deceleration of a vehicle is required based on the degree of curvature of the travel lane and a vehicle speed; and a marking display section configured to, in a case in which deceleration is required, cause a display device to display a predetermined first marking superimposed along the travel lane at a display region inside a vehicle cabin.

An apparatus includes at least one camera configured to capture an image of a traffic lane in front of a vehicle. The apparatus also includes a path tracking controller configured to detect lane boundaries and a path curvature for the traffic lane from the image, determine a lateral offset of the vehicle from a reference path for the traffic lane and a heading offset for the vehicle from the path curvature, determine a yaw rate maintaining the vehicle within the traffic lane using a kinematics control, determine a steering angle maintaining the vehicle within the traffic lane using a dynamics control and the yaw rate determined by the kinematics control, and activate a steering control based on the determined steering angle.

There is provided a method for preventing car collision, the method comprising: obtaining information about a vehicle stopped in front of a preceding vehicle acquired by the preceding vehicle; calculating a deceleration amount for preventing a collision with the stopped vehicle based on the information about the stopped vehicle; predicting a preset event related to the preceding vehicle based on a change in the position of the preceding vehicle; and controlling an autonomous driving vehicle based on the deceleration amount according to a prediction result.

A lane departure avoidance device includes a control unit that executes a lane departure prevention control by at least one of automatically turning a turning wheel and issuing an alarm, when it is determined that there is a possibility that a vehicle crosses a lane border and a driver has no intention of performing a lane departure, and that suspends executing the lane departure prevention control, when it is determined that there is a possibility that the vehicle crosses the lane border and the driver intentions to perform the lane departure. The control unit continues to suspend executing the lane departure prevention control, when it is determined that there is another lane border on a side that the vehicle approaches and that a distance from the vehicle to the other lane border is a reference distance or more, in a situation where executing the lane departure prevention control is suspended.

Systems and methods are provided for vehicle navigation. In one implementation, a system may comprise at least one processor. The processor may be programmed to receive images representative of an environment of the host vehicle and analyze the images to identify a first object and a second object. The processor may determine a first predefined navigational constraint implicated by the first object and a second predefined navigational constraint implicated by the second object, wherein the first and second predefined navigational constraints cannot both be satisfied, and the second predefined navigational constraint has a priority higher than the first predefined navigational constraint. The processor may determine a navigational action for the host vehicle satisfying the second predefined navigational constraint, but not satisfying the first predefined navigational constraint and, cause an adjustment of a navigational actuator of the host vehicle in response to the determined navigational action.