The present disclosure is directed to performing one or more validity checks on potential trajectories for a device, such as an autonomous vehicle, to navigate. In some examples, a potential trajectory may be validated based on whether it is consistent with a current trajectory the vehicle is navigating such that the potential and current trajectories are not too different, whether the vehicle can feasibly or kinematically navigate to the potential trajectory from a current state, whether the potential trajectory was punctual or received within a time period of a prior trajectory, and/or whether the potential trajectory passes a staleness check, such that it was created within a certain time period. In some examples, determining whether a potential trajectory is feasibly may include updating a set of feasibility limits based on one or more operational characteristics of statuses of subsystems of the vehicle.

A method for driving a vehicle on a curved road includes: detecting, by a processor, a curved road which is ahead of a vehicle and has a curvature equal to or greater than a threshold value; calculating, by a processor, a target acceleration to enter into the curved road; generating, by a processor, a driving pattern using a magnitude of the target acceleration; and calculating, by a processor, an acceleration profile based on the driving pattern; outputting, by a processor, a control torque based on the acceleration profile, and controlling the vehicle.

A vehicle control apparatus is provided. The vehicle control apparatus comprises a load unit for loading a load; a weight sensor for estimating a position of a center of mass of the load; a drive unit; and a control unit for controlling autonomous travelling of a vehicle by controlling the drive unit, wherein the control unit estimates a position of the center of mass of the load based on a weight measured by the weight sensor, and controls an acceleration rate of the vehicle in accordance with the position of the center of mass.

In one embodiment, a method, apparatus, and system for planning a trajectory for an autonomous driving vehicle (ADV) is disclosed. The operations comprise: receiving a plurality of optimization inputs, the plurality of optimization inputs comprising a trajectory time length, a time discretization resolution, an autonomous driving vehicle (ADV) starting state, a road shape function, a maximal jerk, and a maximal lateral acceleration; receiving a plurality of optimization constraints, the plurality of optimization constraints comprising constraints relating to the maximal jerk and the maximal lateral acceleration; receiving a cost function associated with an optimization objective, the cost function comprising a first term relating to cumulative jerk, a second term relating to an end longitudinal position, a third term relating to an end longitudinal speed, and a fourth term relating to an end longitudinal acceleration; generating a plurality of planned ADV states as optimization results with nonlinear optimization, wherein the optimization results minimize a value of the cost function; and generating control signals to control the ADV based on the plurality of planned ADV states.

Provided is a vehicle control device capable of improving the riding comfort of a vehicle during parking control. A vehicle control device 10 includes: a distance measuring unit 14 that measures a distance between a position of a vehicle and a target stop position of the vehicle; and an acceleration setting unit 15 that sets an acceleration profile, which is a time change of a target value of acceleration during deceleration of the vehicle, according to the distance based on a jerk profile 15a, which is a time change of a target value of jerk during deceleration of the vehicle.

The technology provides a sign detection and classification methodology. A unified pipeline approach incorporates generic sign detection with a robust parallel classification strategy. Sensor information such as camera imagery and lidar depth, intensity and height (elevation) information are applied to a sign detector module. This enables the system to detect the presence of a sign in a vehicle's externa environment. A modular classification approach is applied to the detected sign. This includes selective application of one or more trained machine learning classifiers, as well as a text and symbol detector. Annotations help to tie the classification information together and to address any conflicts with different the outputs from different classifiers. Identification of where the sign is in the vehicle's surrounding environment can provide contextual details. Identified signage can be associated with other objects in the vehicle's driving environment, which can be used to aid the vehicle in autonomous driving.

A behavior control apparatus for a vehicle having a control unit for controlling a braking device and controlling a behavior of a vehicle by controlling braking forces of wheels. When the vehicle is in the non-braking state, the control unit acquires information on a lateral acceleration of the vehicle; calculates, based on the lateral acceleration of the vehicle, a target yaw moment of a feedforward control for reducing a rate of decrease of the vehicle's yaw gain accompanying with an increase in an absolute value of a lateral acceleration of the vehicle, and controls braking forces of the wheels by controlling the braking device so that at least a yaw moment corresponding to the target yaw moment is applied to the vehicle.

A control apparatus of a vehicle includes: a steering apparatus (6) including a steering wheel (11) operated in order to turn a vehicle (1) and a steering angle sensor (8) that detects a steering angle of the steering wheel (11), the steering apparatus (6) steering a front wheel (steered wheel) (2) of the vehicle (1) in accordance with operation of the steering wheel (11); and a controller (14) that sets a steering angle acceleration based on the steering angle detected by the steering angle sensor (8) and controls vehicle motion when the steering wheel (11) is operated to be turned. In particular, the controller (14) suppresses a rise of lateral acceleration of the vehicle (1) based on the steering angle acceleration in order to control the vehicle motion.

An apparatus configured for determining an intention to cut in in a vehicle may include a navigation module, a camera, a radar configured to obtain data about an external vehicle, a sensor configured to obtain data about behavior of the vehicle, and a processor configured to be electrically connected to the navigation module, the camera, the radar, and the sensor, wherein the processor is configured to obtain information associated with at least a portion of a road environment, traffic, or road curvature based on data obtained using at least a portion of the navigation module, the camera, the radar, or the sensor and adjust a parameter for determining an intention for a surrounding vehicle which is traveling in a second lane adjacent to a first lane where the vehicle is traveling to cut in, based on the obtained information.

The present application relates to a method and apparatus including a sensor for detecting a first vehicle speed, a camera operative to capture an image, a processor operative to determine a road curvature in response to the image, the processor further operative to determine a first predicted lateral acceleration in response to the road curvature and the first vehicle speed, the processor further operative to determine a second vehicle speed in response to the first predicted lateral acceleration exceeding a threshold value wherein the second vehicle speed results in a second predicted lateral acceleration being less than the threshold value, and to generate a control signal indicative of the second vehicle speed, and a vehicle controller operative to reduce a vehicle velocity to the second vehicle speed in response to the control signal.