Patent classifications
B60W10/18
Methods and apparatus for automated speed selection and retarder application in downhill driving of an autonomous tractor trailer
A method includes detecting, via a processor of an autonomous vehicle, an upcoming downhill road segment of a route on which the autonomous vehicle is currently travelling. The detection is based on map data, camera data, and/or inertial measurement unit (IMU) data. In response to detecting the upcoming downhill road segment, a descent plan is generated for the autonomous vehicle. The descent plan includes a speed profile and a brake usage plan. The brake usage plan specifies a non-zero amount of retarder usage and an amount of foundation brake usage for a predefined time period. The method also includes autonomously controlling the autonomous vehicle, based on the descent plan, while the autonomous vehicle descends the downhill road segment.
CONTROL SYSTEM, CONTROLLER, AND CONTROL METHOD
The present invention obtains a control system, a controller, and a control method capable of appropriately controlling body behavior of plural motorcycles that travel in group.
In a control system (1), a controller (12), and a control method according to the present invention, in plural motorcycles (10) to each of which an environment sensor (11) and the controller (12) are mounted and in each of which a control mode for controlling body behavior is executed by the controller (12) on the basis of output of the environment sensor (11), a first controller that is mounted to a first motorcycle of the plural motorcycles (10) transmits acquired information that is acquired during execution of the control mode to a second controller that is mounted to a second motorcycle other than the first motorcycle of the plural motorcycles (10), and the second controller receives the acquired information and executes the control mode on the basis of the acquired information.
CONTROL SYSTEM, CONTROLLER, AND CONTROL METHOD
The present invention obtains a control system, a controller, and a control method capable of appropriately controlling body behavior of plural motorcycles that travel in group.
In a control system (1), a controller (12), and a control method according to the present invention, in plural motorcycles (10) to each of which an environment sensor (11) and the controller (12) are mounted and in each of which a control mode for controlling body behavior is executed by the controller (12) on the basis of output of the environment sensor (11), a first controller that is mounted to a first motorcycle of the plural motorcycles (10) transmits acquired information that is acquired during execution of the control mode to a second controller that is mounted to a second motorcycle other than the first motorcycle of the plural motorcycles (10), and the second controller receives the acquired information and executes the control mode on the basis of the acquired information.
SYSTEM AND METHOD FOR EVALUATING THE BEHAVIOR OF A VEHICLE COMPONENT
A method for evaluating the behavior of a vehicle component, including: issuing a control signal by a control unit of a motor vehicle to a vehicle component; detecting a response of the motor vehicle to the control signal; determining the behavior of the vehicle component; classifying the behavior of the vehicle component; and adapting the actuation of the motor vehicle component by the control unit. Also described is a related system.
SYSTEM AND METHOD FOR EVALUATING THE BEHAVIOR OF A VEHICLE COMPONENT
A method for evaluating the behavior of a vehicle component, including: issuing a control signal by a control unit of a motor vehicle to a vehicle component; detecting a response of the motor vehicle to the control signal; determining the behavior of the vehicle component; classifying the behavior of the vehicle component; and adapting the actuation of the motor vehicle component by the control unit. Also described is a related system.
VEHICLE CONTROL DEVICE, AND VEHICLE CONTROL SYSTEM
A vehicle control device that autonomously controls a vehicle so as not to cause rapid deceleration that leads to a deterioration in ride quality. The vehicle control device controls first and second deceleration, means that reduce a speed at a deceleration rate large than a deceleration rate of the first deceleration means. The vehicle control device includes a blind spot area detecting unit that detects a blind spot area of a sensor that recognizes an external environment, and a blind spot object estimating unit that estimates a blind spot object that is a virtual moving body hidden in the blind spot area. When a vehicle approaches the blind spot area at a speed reduced by the first deceleration means, the vehicle is decelerated by the second deceleration means when a type of a moving body detected by the sensor is different from a type of the blind spot object.
VEHICLE CONTROL DEVICE, AND VEHICLE CONTROL SYSTEM
A vehicle control device that autonomously controls a vehicle so as not to cause rapid deceleration that leads to a deterioration in ride quality. The vehicle control device controls first and second deceleration, means that reduce a speed at a deceleration rate large than a deceleration rate of the first deceleration means. The vehicle control device includes a blind spot area detecting unit that detects a blind spot area of a sensor that recognizes an external environment, and a blind spot object estimating unit that estimates a blind spot object that is a virtual moving body hidden in the blind spot area. When a vehicle approaches the blind spot area at a speed reduced by the first deceleration means, the vehicle is decelerated by the second deceleration means when a type of a moving body detected by the sensor is different from a type of the blind spot object.
Vehicle Motion Control Apparatus, Vehicle Motion Control Method, and Vehicle Motion Control System
A vehicle motion control apparatus includes a control unit which controls a steering apparatus and a brake apparatus provided in a vehicle. The control unit acquires a normative motion state amount necessary for the vehicle to trace a target traveling path, acquires a target motion state amount necessary for generating a yaw moment to cancel unstable behavior of the vehicle, and acquires a target steering angle for generating a steering angle moment and a target brake force for generating a brake moment, to obtain a necessary yaw moment generated by the vehicle. The control unit outputs a first control command for obtaining the target steering angle to the steering apparatus and outputs a second control command for obtaining the target brake force to the brake apparatus.
Vehicle Motion Control Apparatus, Vehicle Motion Control Method, and Vehicle Motion Control System
A vehicle motion control apparatus includes a control unit which controls a steering apparatus and a brake apparatus provided in a vehicle. The control unit acquires a normative motion state amount necessary for the vehicle to trace a target traveling path, acquires a target motion state amount necessary for generating a yaw moment to cancel unstable behavior of the vehicle, and acquires a target steering angle for generating a steering angle moment and a target brake force for generating a brake moment, to obtain a necessary yaw moment generated by the vehicle. The control unit outputs a first control command for obtaining the target steering angle to the steering apparatus and outputs a second control command for obtaining the target brake force to the brake apparatus.
OBJECT POSE ESTIMATION
A depth image of an object can be input to a deep neural network to determine a first four degree-of-freedom pose of the object. The first four degree-of-freedom pose and a three-dimensional model of the object can be input to a silhouette rendering program to determine a first two-dimensional silhouette of the object. A second two-dimensional silhouette of the object can be determined based on thresholding the depth image. A loss function can be determined based on comparing the first two-dimensional silhouette of the object to the second two-dimensional silhouette of the object. Deep neural network parameters can be optimized based on the loss function and the deep neural network can be output.