A method automatically controls an actuator of a control system of an automotive device. The method includes determining a reference trajectory, determining a position of the device with respect to the reference trajectory, acquiring a parameter relating to a force exerted by a driver on a manual control device of the control system, and calculating a controlling setpoint of the actuator. The controlling setpoint is calculated as a function of the parameter and of the position of the device with respect to the reference trajectory.

The present invention discloses an intelligent vehicle platoon lane change performance evaluation method. First, an intelligent vehicle platoon lane change performance test scenario is established; secondly, a three-degree of freedom nonlinear dynamics model is established according to motion characteristics of intelligent vehicles in a platoon lane change process; further, an improved adaptive unscented Kalman filter algorithm is utilized to perform filter estimation on state variables of positions and velocities of platoon vehicles; and finally, based on accurately recursive vehicle motion state parameters, evaluation indexes for platoon lane change performance are proposed and quantified, and an evaluation system for platoon lane change performance is constructed. According to the method proposed in the present invention, the problem of lacking platoon lane change performance quantitative evaluation at present is solved, vehicle motion state parameters can be measured in a high-precision and comprehensive manner, multi-dimensional platoon lane change performance evaluation indexes are quantified and output, and comprehensive, accurate, and reliable scientific quantitative evaluation for platoon lane change performance is achieved.

Systems and methods for coordinating steering controls between towing vehicles and towed vehicles provide more cohesive parking experiences during towing events, including bidirectional charging towing events. The towed vehicle may be controlled to provide assistive parking steering maneuvers to assist the towing vehicle when parking during the towing event. The assistive parking steering maneuver may include maneuvering a drive wheel of the towed vehicle either toward or away from a detected curb or detected traffic, for example.

The present disclosure relates to an unmanned lane keeping method and device, a computer device, and a storage medium. The method includes that: a vehicle road image collected by a data collector of the vehicle is received; the vehicle road image is transmitted to a preset DNN model of the vehicle for processing to obtain a steering wheel angle corresponding to the vehicle road image, wherein the DNN model of the vehicle is established by deep learning, and is used for characterizing a correspondence between the vehicle road image and the steering wheel angle; and the vehicle is controlled to keep driving in a corresponding lane according to the steering wheel angle.

A vehicular driving assistance system includes a camera viewing exterior of a vehicle and capturing image data. The system, via processing captured image data as the vehicle travels along a current traffic lane, determines a current lateral position of the vehicle within the current traffic lane and determines a target lateral position of the vehicle within the current traffic lane. The system determines a steering command to guide the vehicle from the current lateral position to the target lateral position and determines a steering angle offset required to maintain the target lateral position within the current traffic lane and stores the determined steering angle offset in nonvolatile memory. After storing the determined steering angle offset and when the vehicle is traveling during a subsequent trip, the system determines a second target lateral position of the vehicle within the current traffic lane and applies the stored steering angle offset.

Vision based guidance system and method for lawn mowing devices are disclosed. An exemplary method for operating an autonomous lawn mower includes receiving, via a receiver, a perimeter data set from a handheld computer. The perimeter data set includes a perimeter outline of at least one perimeter that is determined utilizing a GPS unit of the handheld computer. The exemplary method also includes collecting, via at least one camera, images of a set area within the perimeter outline and mowing, via a mowing blade, grass within the set area. The exemplary method also includes autonomously steering, via a controller, the autonomous lawn mower based on the perimeter outline of the at least one perimeter and the images captured by the at least one camera.

A control method is provided for controlling a lateral position of a motor vehicle. The control method includes calculating a sighting distance of a detector means embedded in the vehicle, calculating a first component of a steering angle setpoint of a steered wheels of the vehicle, and calculating a second component of the steering angle setpoint. The first component is an open loop component of a control system, while the second component is a closed loop component of the control system. The first component is weighted by a gain that is a decreasing function of the sighting distance.

Mappings of keys to actions can automate various vehicle systems. Some automations can provide lane departure warnings. Keys for lane departure mappings can specify vibration patterns expected when a vehicle drives over lane delineators. These vibration-based mappings can include keys with vibration patterns, e.g., defining vibration frequencies or vibration locations. Keys for emergency light mappings can be based on conditions such as (1) the vehicle being on the road, stopped, not in traffic, and not at a stop signal; (2) components of the vehicle having failed; or (3) weather conditions.

A computer implemented method for lateral control of a vehicle comprises the following steps carried out by computer hardware components: determining a location error of the vehicle; determining an orientation error of the vehicle; determining a cost function based on the location error and the orientation error using a circular transformation; and processing the cost function in a model predictive controller to control the vehicle laterally.

A parking assistance control device detects a parkable area, where a host vehicle can be parked, based on target information, causes the vehicle to move from the initial position, which is the vehicle's position when the parkable area is detected, to the parkable area by controlling a driving device, braking device, and steering device and, when the target information indicates that a stopper is installed in the parkable area, causes the vehicle to stop with its position and direction with respect to the stopper matching a predetermined position and direction. The parking assistance control device causes the vehicle to stop with the distance between the vehicle's predetermined first reference point and the stopper matching a first predetermined value so that the vehicle is forward-parked in the state where the front end of a part, provided on the vehicle's front side and lower than the stopper, is separated from the stopper.