A vehicular vision system includes a camera disposed at a vehicle and viewing exterior of the vehicle. The system, responsive to processing by an image processor of image data captured by the camera, determines presence of a leading vehicle ahead of the equipped vehicle and travelling in the same lane as the equipped vehicle. The system, via processing by the image processor of image data captured by the camera, determines an indication at the leading vehicle indicative of a safeness of a passing maneuver by the equipped vehicle. The indication is representative of a determination by the leading vehicle that the safeness of the passing maneuver exceeds a threshold safeness level. The system, based on the determined indication, at least in part controls operation of the equipped vehicle to overtake and pass the determined leading vehicle.

In response to perceiving a moving object, one or more possible object paths of the moving object are determined based on the prior movement predictions of the moving object, for example, using a machine-learning model, which may be created based on a large amount of driving statistics of different vehicles. For each of the possible object paths, a set of trajectory candidates is generated based on a set of predetermined accelerations. Each of the trajectory candidates corresponds to one of the predetermined accelerations. A trajectory cost is calculated for each of the trajectory candidates using a predetermined cost function. One of the trajectory candidates having the lowest trajectory cost amongst the trajectory candidates is selected. An ADV path is planned to navigate the ADV to avoid collision with the moving object based on the lowest costs of the possible object paths of the moving object.

A vehicle control apparatus includes a processor. Before the vehicle passes through an inflection point of a curvature of a target trajectory, the processor sets a first reference point before the inflection point. After the vehicle passes through the inflection point, the processor sets a second reference point at a position where a second distance from a current position of the vehicle after the vehicle passes through the inflection point to the second reference point is longer than a first distance from a current position of the vehicle before the vehicle passes through the inflection point to the first reference point when compared under travel conditions identical in a vehicle speed, an acceleration rate, a deceleration rate, or a steering angle. The processor sets a target steering angle based on the curvature of an arc passing through the current position and the first reference point or the second reference point.

A method for controlling a U-turn using a high-definition map may include recognizing a U-turn section in front of a vehicle on the basis of sensor information, detecting a first point in the U-turn section using a high-definition map, determining at least one candidate lane link on the high-definition map and selecting a target lane link from the at least one candidate lane link, determining a second point on the target lane link on the basis of the first point, and generating a dynamic curvature route based on the first point and the second point.

A vehicle control device includes a recognition part, a driving control part, and an output control part. When determining there is a section where a current driving mode cannot be continued in a first lane and the vehicle changes to a second lane, the output control part outputs predetermined information, including first and second information, before reaching the section. When detecting an intention to change lanes after outputting the first information, and a lane change to the second lane is completed before outputting the second information, the driving control part continues a first driving mode executed during traveling in the first lane even after the lane change is completed, and when detecting the intention to change lanes after outputting the first information, and the lane change to the second lane is completed after outputting the second information, the driving control part changes to a driving mode imposing a larger task.

When a subject vehicle arrives at a destination while traveling, or when a driver of the subject vehicle becomes unable to drive during travel or when a failure occurs that interferes with the travel of the subject vehicle during the travel, a control plan for autonomous stop control is generated, the control plan comprising deceleration control for decreasing a speed of the subject vehicle; pulling over control for moving the subject vehicle from a lane in which the subject vehicle travels to the shoulder of the road; and stop control for stopping the subject vehicle at the shoulder of the road, and on a basis of this control plan, the autonomous stop control is performed to decelerate the subject vehicle and then move it to the shoulder of the road by individually and sequentially performing each of the deceleration control, the pulling over control, and the stop control.

Command determination for controlling a vehicle, such as an autonomous vehicle, is described. In an example, individual requests for controlling the vehicle relative to each of multiple objects or conditions in an environment are received (substantially simultaneously) and based on the request type and/or additional information associated with a request, command controllers can determine control commands (e.g., different accelerations, steering angles, steering rates, and the like) associated with each of the one or more requests. The command controllers may have different controller gains (which may be based on functions of distance, distance ratios, time to estimated collisions, etc.) for determining the controls and a control command may be determined based on the all such determined controls.

The present application relates to a method and apparatus for controlling an ADAS equipped vehicle including an input for receiving a lane change request, a global positioning sensor for detecting a vehicle location, a memory for storing a map data, a vehicle controller for performing a lane change in response to a lane change navigational route, and a processor configured for generating the lane change navigational route in response to the map data and the lane change request, for calculating a predicted lateral acceleration within the lane change navigational route in response to the map data and the lane change request and for coupling the lane change navigational route to the vehicle controller in response to the predicted lateral acceleration being less than a lateral acceleration threshold.

A vehicle for transporting passengers include a floor board on which the passengers ride. The vehicle further includes a passenger distribution detection device that detects a passenger distribution that is a distribution of the passengers on the floor board. The vehicle further includes a control device that executes a passenger guidance control that guides the passengers on the floor board such that the passenger distribution approaches a target passenger distribution to increase a stability of the vehicle.

A vehicle occupant assistance apparatus predicts acceleration occurring when a vehicle is traveling. When a make-up mode is activated, assistance information is notified before a predetermined value of the acceleration occurs, based on predicted values of the acceleration. Thus, since the assistance information is notified to an occupant before the vehicle shakes due to the predetermined value of the acceleration, assistance taking a shake of the vehicle into consideration can be rendered to the occupant who applies make-up when the vehicle is traveling.