Embodiments of the present disclosure disclose forward collision control methods and apparatuses, electronic devices, programs, and media, where the forward collision control method includes: detecting a forward suspected collision object on a road where a current traveling object is located on the basis of a neural network; predicting the collision time between the current traveling object and the suspected collision object; and performing forward collision control on the current traveling object according to the collision time, where the forward collision control includes forward collision warning and/or driving control.

A method and a system for lane change prediction. The method includes collecting raw driving data, extracting a plurality of feature sets from the collected raw driving data, and obtaining corresponding lane change information. The lane change information indicates a status of lane change of a vehicle under each of the extracted feature sets. The method further includes automatically labeling each of the extracted plurality sets of features with the obtained corresponding lane change information. The method further includes training a lane change prediction model with the labeled plurality sets of features. Examples of the present disclosure further describe methods, systems, and vehicles for applying the lane change prediction model.

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.

A method of managing operator take-over of autonomous vehicle. The method includes gathering information on an external surrounding of the autonomous vehicle; analyzing the gathered information on the external surrounding of the autonomous vehicle to determine an upcoming traffic pattern; gathering information on an operator of the autonomous vehicle; analyzing the gathered information on the operator of the autonomous vehicle to determine an operator behavior; predicting an operator action based on the determined upcoming traffic pattern and the determined operator behavior; and initiating a predetermined vehicle response based on the predicted operator action. The predicting the operator action includes comparing the determined upcoming traffic pattern with a similar historic traffic pattern and retrieving a historical operator action in response to the similar historical pattern.

A method of determining a trajectory for an autonomous vehicle is disclosed. An ego-vehicle may detect a moving actor in an environment. To choose between candidate trajectories for the ego-vehicle, the system will consider the cost of each candidate trajectory to the moving actor. The system will use the candidate trajectory costs for the candidate trajectories to select one of the candidate trajectories via which to move the ego-vehicle. An autonomous vehicle system of the ego-vehicle may then move the ego-vehicle in the environment along the selected trajectory.

A method of operating an autonomous vehicle includes detecting, based on an input received from a sensor of an autonomous vehicle that is being navigated by an on-board computer system, an occurrence of a driving event, making a determination by the on-board computer system, upon the detecting the occurrence of the driving event, whether or how to alter the path planned by the on-board computer system according to a set of rules, and performing further navigation of the autonomous vehicle based on the determination until the driving event is resolved. The driving event may include a presence of an object in a shoulder area of the road. The driving event may include accumulation of more than a certain number of vehicles behind the autonomous vehicle. The driving event may include a slow vehicle ahead of the autonomous vehicle. The driving event may include a do-not-change-lane zone is within a threshold.

A vehicular trailer sway management system includes at least one rearward-sensing radar sensor disposed at a vehicle and an electronic control unit (ECU). Radar data captured by the at least one rearward-sensing radar sensor is provided to the ECU. With a trailer hitched to the vehicle, the trailer sway management system, via processing at the ECU of the provided captured radar data, determines oblique angles of the trailer relative to the vehicle. As the vehicle tows the trailer, and responsive to monitoring of determined oblique angles of the trailer relative to the longitudinal axis of the vehicle, the trailer sway management system determines sway of the trailer relative to the vehicle. Responsive to the determined sway of the trailer relative to the vehicle, the trailer sway management system at least in part controls operation of the vehicle to manage sway of the trailer relative to the vehicle.

A parking assistance system executes a process to measure the parking space by a sensor prior to carrying out an automated parking maneuver and to detect the parking space type from a plurality of detectable parking space types using specific criteria on the basis of the measurement of the parking space. The plurality of parking space types includes a longitudinal parking space type, in which a vehicle can park longitudinally, a transverse parking space type, in which a vehicle can park transversely, and a universal parking space type in which the vehicle can park both longitudinally as well as transversely. In the event that the parking space has been detected as a universal parking space type, the parking assistance system provides the driver with the choice to select a parking direction, namely whether the parking assistance system is to park longitudinally or transversely into the parking space. The parking assistance system parks the vehicle into the parking space longitudinally or transversely according to the selection of the driver, wherein the parking trajectory depends on the selection of the driver.

Some embodiments are directed to methods and apparatus for predicting traffic conditions and controlling a host vehicle based on the predicted conditions for travel along a path. The methods and apparatus can perform the following: accessing current path data relevant to a location and speed the host vehicle; detecting data, from a vehicular communications network, from a merging vehicle intending to merge into the path of the host vehicle; detecting data, from the vehicular communications network, of preceding traffic in the path of the host vehicle; determining a speed and location of the merging vehicle from the data transmitted over the vehicle communications network; determining a speed and location of preceding traffic on the path of the host vehicle from the data transmitted over the vehicular communications network; and predicting whether the speed of the preceding traffic or the speed of the merging vehicle will slow down during the merge.

A computer-implemented method for controlling a host vehicle having a vehicle control system that controls motion of the host vehicle relative to a preceding vehicle that is immediately ahead of the host vehicle. The method includes determining a relative headway distance and a relative velocity between the host vehicle and the preceding vehicle, and an acceleration rate of the preceding vehicle. The method includes receiving message packets transmitted from a leading vehicle and the message packets contain parameters of the leading vehicle including an acceleration rate of the leading vehicle. Further, the method includes calculating an acceleration control rate for the host vehicle to maintain the headway reference distance between the host vehicle and the preceding vehicle, based on the relative headway distance, the relative velocity, the acceleration rate of the preceding vehicle, and the acceleration rate of the leading vehicle. The acceleration rate is output to a vehicle controller to control motion of the host vehicle.