Disclosed herein are an autonomous driving method for avoiding a stopped vehicle and an apparatus for the same. The autonomous driving method for avoiding a stopped vehicle is performed by an autonomous driving control apparatus provided in an autonomous vehicle, and includes obtaining taillight recognition information for a stopped vehicle identified ahead of the autonomous vehicle, determining whether the stopped vehicle is to be avoided in consideration of the taillight recognition information, when it is determined that the stopped vehicle is to be avoided, setting an avoidance method in consideration of whether lane returning is to be performed, which is determined based on an autonomous driving task, and setting an avoidance time point corresponding to the avoidance method and controlling the autonomous vehicle to avoid the stopped vehicle by traveling along an avoidance path generated in conformity with the avoidance time point.

An indication of an intention of making a lane change to an adjacent lane that is issued from a preceding vehicle that travels in the same lane as an own vehicle is sensed while causing the own vehicle to travel while following the preceding vehicle. When the indication of the intention of making the lane change is sensed, deviation of the preceding vehicle toward the adjacent lane from an occupied region that is occupied by the own vehicle in traveling in the lane is sensed. Then, when deviation of the preceding vehicle from the occupied region is sensed, acceleration suppression for causing the own vehicle to travel while following the preceding vehicle is canceled.

A motor-vehicle path-controlling module is arranged to model the path of the vehicle during a change in traffic lane by a Bezier curve relating a value of a parameter to a value of a lateral deviation of the vehicle from the center of a traffic lane and to a value of a time-dependent variable representative of the variation in the change of path; determine a setpoint state vector of a closed feedback loop of a path-controlling device, the loop being designed to control the motor vehicle so that it follows the path modelled by the Bezier curve, the vector being determined on the basis of the lateral deviation, of the time-dependent variable and of the parameter, and transmit the setpoint state vector to the input of the loop.

A method for evaluating contextual risk profiles at a computing device (110, 212, 312) in a vehicle (310), the method including obtaining information about a proximate vehicle (320, 330); utilizing the information to create a risk profile for the proximate vehicle (320, 330); and based on the risk profile, initiating an action at computing device (110, 212, 312).

A vehicle control apparatus controls movement of a vehicle in a lateral direction intersecting a direction in which the vehicle travels based on a movement trajectory of a preceding vehicle. The vehicle control apparatus includes a detection unit configured to detect a surrounding environment of the vehicle, and a preceding vehicle which travels ahead in the same lane in which the vehicle travels, a determination unit configured to determine whether or not the preceding vehicle straddles lanes or approaches within a set distance predetermined for the lanes based on lateral movement information of the preceding vehicle detected by the detection unit, and a control unit configured to control lateral movement of the vehicle based on a determination result of the determination unit and detection information of the detection unit.

A system includes a processor and a memory storing instructions executable by the processor to select a distance based on a determination of whether a lane adjacent a primary vehicle and a secondary vehicle in front of the primary vehicle is clear. The instructions include instructions to actuate a braking system of the primary vehicle when the primary vehicle is at the distance from the secondary vehicle.

Techniques for determining a vehicle action and controlling a vehicle to perform the vehicle action for navigating the vehicle in an environment can include determining a vehicle action, such as a lane change action, for a vehicle to perform in an environment. The vehicle can detect, based at least in part on sensor data, an object associated with a target lane associated with the lane change action sensor data. In some instances, the vehicle may determine attribute data associated with the object and input the attribute data to a machine-learned model that can output a yield score. Based on such a yield score, the vehicle may determine whether it is safe to perform the lane change action.

Methods and devices for generating data for controlling a Self-Driving Car (SDC) are disclosed. The method includes: (i) acquiring a predicted object trajectory for an object, (ii) acquiring a set of anchor points along the lane for the SDC, (iii) for each one of the set of anchor points, determining a series of future moments in time when the SDC is potentially located at the respective one of the set of anchor points, thereby generating a matrix structure including future position-time pairs, (iv) for each future position-time pair in the matrix structure, using the predicted object trajectory for determining a distance between a closest object to the SDC as if the SDC is located at the respective future position-time pair, and (v) storing the distance between the closest object to the SDC in association with the respective future position-time pair in the matrix structure.

A vehicle, system and method for operating the vehicle is disclose. The system includes a radar system and a processor. The radar system locates a gap between targets in a second lane adjoining a first lane, with the host vehicle residing in the first lane. The processor is configured to determine a viability value of the gap for a lane change, select the gap based on the viability value, align the host vehicle with the selected gap, and merge the host vehicle from the first lane into the selected gap in the second lane.

An example operation includes one or more of determining a transport is operating in an unsafe manner, directing a proximate transport operating in a safe manner to maneuver in front of the transport, and directing the proximate transport to control at least one function of the transport.