B60W40/10

Teleoperations for collaborative vehicle guidance
11584389 · 2023-02-21 · ·

Techniques to provide guidance to a vehicle operating in an environment are discussed herein. For example, such techniques may include sending a request for assistance, receiving a reference trajectory, and causing the vehicle to determine a trajectory based on the reference trajectory. Data such as sensor data and vehicle state data may be sent from the vehicle to a remote computing device. The computing device outputs a user interface using the data and determines the reference trajectory based on receiving an input in the user interface. The techniques can send an indication of the reference trajectory to the vehicle for use in planning a trajectory for the vehicle. A vehicle, such as an autonomous vehicle, can be controlled to traverse an environment based on the trajectory.

Image segmention via efficient semidefinate-programming based inference for binary and multi-class Markov Random Fields

A system for controlling a physical system via segmentation of an image includes a controller. The controller may be configured to receive an image of n pixels from a first sensor, and an annotation of the image from a second sensor, form a coupling matrix, k class vectors each of length n, and a bias coefficient based on the image and the annotation, generate n pixel vectors each of length n based on the coupling matrix, class vectors, and bias coefficient create a single segmentation vector of length n from the pixel vectors wherein each entry in the segmentation vector identifies one of the k class vectors, output the single segmentation vector; and operate the physical system based on the single segmentation vector.

Image segmention via efficient semidefinate-programming based inference for binary and multi-class Markov Random Fields

A system for controlling a physical system via segmentation of an image includes a controller. The controller may be configured to receive an image of n pixels from a first sensor, and an annotation of the image from a second sensor, form a coupling matrix, k class vectors each of length n, and a bias coefficient based on the image and the annotation, generate n pixel vectors each of length n based on the coupling matrix, class vectors, and bias coefficient create a single segmentation vector of length n from the pixel vectors wherein each entry in the segmentation vector identifies one of the k class vectors, output the single segmentation vector; and operate the physical system based on the single segmentation vector.

Controlling damper friction effects in a suspension
11498382 · 2022-11-15 · ·

In some examples, a vehicle suspension for supporting, at least in part, a sprung mass, includes a damper connected to the sprung mass, the damper including a movable piston. The vehicle suspension further includes an actuator and a controller. The controller may be configured to determine a frequency of motion associated with the sprung mass. When the frequency of motion is below a first frequency threshold, the controller may send a control signal to cause the actuator to apply a deceleration force to the sprung mass. Further, when the frequency of motion associated with the sprung mass exceeds the first frequency threshold, the controller may send a control signal to cause the actuator to apply a compensatory force to the sprung mass. For instance, a magnitude of the compensatory force may be based on a friction force determined for the damper.

Controlling damper friction effects in a suspension
11498382 · 2022-11-15 · ·

In some examples, a vehicle suspension for supporting, at least in part, a sprung mass, includes a damper connected to the sprung mass, the damper including a movable piston. The vehicle suspension further includes an actuator and a controller. The controller may be configured to determine a frequency of motion associated with the sprung mass. When the frequency of motion is below a first frequency threshold, the controller may send a control signal to cause the actuator to apply a deceleration force to the sprung mass. Further, when the frequency of motion associated with the sprung mass exceeds the first frequency threshold, the controller may send a control signal to cause the actuator to apply a compensatory force to the sprung mass. For instance, a magnitude of the compensatory force may be based on a friction force determined for the damper.

Human-powered vehicle control device, suspension system, and human-powered vehicle
11498641 · 2022-11-15 · ·

A human-powered vehicle control device is provided for suitably controlling a rotation state of a wheel of a human-powered vehicle. The human-powered vehicle control device includes a first detector and an electronic controller. The first detector is configured to detect information related to a driving force of the wheel of the human-powered vehicle on a road surface. The electronic controller is configured to change an operation state of a suspension device of the human-powered vehicle in response to a detection result of the first detector.

Human-powered vehicle control device, suspension system, and human-powered vehicle
11498641 · 2022-11-15 · ·

A human-powered vehicle control device is provided for suitably controlling a rotation state of a wheel of a human-powered vehicle. The human-powered vehicle control device includes a first detector and an electronic controller. The first detector is configured to detect information related to a driving force of the wheel of the human-powered vehicle on a road surface. The electronic controller is configured to change an operation state of a suspension device of the human-powered vehicle in response to a detection result of the first detector.

METHOD AND DEVICE FOR CONTROLLING PEDALS OF A VEHICLE

The present invention relates to a method for operating a driver model for controlling a vehicle. The driver model comprises a vehicle module (203) which determines an accelerator pedal position to be set on the vehicle. In addition, the vehicle module (203) determines a required power as a component of a total power, which total power can be generated by a drive system of the vehicle, wherein the required power corresponds to a power that is necessary for moving the vehicle at a required speed and/or a required acceleration (311) along a predefined road course. The method according to the invention further provides for a value (313) of a permissible pedal position to be assigned to the required power and for the value (313) of the permissible pedal position to be transmitted to the driver model in order to control the vehicle.

METHOD AND DEVICE FOR CONTROLLING PEDALS OF A VEHICLE

The present invention relates to a method for operating a driver model for controlling a vehicle. The driver model comprises a vehicle module (203) which determines an accelerator pedal position to be set on the vehicle. In addition, the vehicle module (203) determines a required power as a component of a total power, which total power can be generated by a drive system of the vehicle, wherein the required power corresponds to a power that is necessary for moving the vehicle at a required speed and/or a required acceleration (311) along a predefined road course. The method according to the invention further provides for a value (313) of a permissible pedal position to be assigned to the required power and for the value (313) of the permissible pedal position to be transmitted to the driver model in order to control the vehicle.

VEHICLE POSITION CORRECTION APPARATUS AND METHOD THEREOF
20220355805 · 2022-11-10 · ·

A vehicle position correction apparatus and a method thereof may include a learner that deep learns a model which predicts a position of a probe vehicle based on driving information of the probe vehicle traveling on a road, a communication device that receives driving information of a target vehicle from the target vehicle, and a controller that obtains a predicted position of the target vehicle based on the model on which the deep learning is completed and corrects an actually measured position of the target vehicle to the predicted position of the target vehicle.