The present invention provides a shift control method implemented in a vehicle equipped with an automatic transmission for controlling an input shaft rotation speed to a target input shaft rotation speed during a shift. The method includes setting of a basic target synchronization rotation speed that is a basic target value of the input shaft rotation speed during the shift, and setting of a corrected target input shaft rotation speed as the target input shaft rotation speed when the shift is a downshift without a requirement for a driving force of the vehicle, The corrected target input shaft rotation speed is obtained by decreasingly correcting the basic target synchronization rotation speed. Further, a decreasing correction amount of the basic target synchronization rotation speed is set so as to become larger as a deceleration of the vehicle becomes larger.

An autonomous vehicle system removes ephemeral points from lidar samples. The system receives a plurality of light detection and ranging (lidar) samples captured by a lidar sensor. Along with the lidar samples, the system receives an aligned pose and an unwinding transform for each of the lidar samples. The system determines one or more occupied voxel cells in a three-dimensional (3D) space using the lidar samples, their aligned poses, and their unwinding transforms. The system identifies occupied voxel cells representative of noise associated with motion of an object relative to the lidar sensor. The system filters the occupied voxel cells by removing the cells representative of noise. The system inputs the filtered occupied voxel cells in a 3D map comprising voxel cells, e.g., during the map generation and/or a map update.

A device for determining hands off of a driver includes a torque sensor for sensing a torque caused by turning of a steering wheel and generating a torque signal, a first frequency filter and a second frequency filter for filtering the torque signal, a representative value generating device for generating a first representative value based on a frequency component of a first filtered signal output by the first frequency filter, and generating a second representative value based on a frequency component of a second filtered signal output by the second frequency filter, and a control module that determines the hands off of the driver based on a ratio of the first representative value and the second representative value.

A hybrid electric vehicle (HEV) includes an internal combustion engine, a traction motor, a generator, and a traction battery. Available electric power in the HEV is based upon the available power in the traction battery. The engine and the motor may both work simultaneously to propel the HEV. While the engine is powering the HEV, a controller is configured to increase a power output of the engine based upon a difference between available battery power and a combination of desired motor power and desired generator power.

A system control a vehicle using a friction function describing a friction between a type of surface of the road and a tire of the vehicle as a function of a slip of a wheel of the vehicle. The parameters of each friction function include an initial slope of the friction function defining a stiffness of the tire and one or combination of a peak friction, a shape factor and a curvature factor of the friction function. Upon estimating a slip and a stiffness of the tire, the system selects from the memory parameters of the friction function corresponding to the current stiffness of the tire, determines a control command using a value of the friction corresponding to the slip of the tire according to the friction function defined by the selected parameters, and submits the control command to an actuator of the vehicle.

Aspects of the disclosure provide for generation of trajectories for a vehicle driving in an autonomous driving mode. In one instance, a default number of trajectories to be generated may be identified. A set of maneuvering options may be selected from a set of predetermined maneuvering options based on the number of trajectories. The set of maneuvering options may be filtered based on the default number of trajectories. A set of trajectories may be generated based on the filtered set of maneuvering option such that each trajectory of the set corresponds to a different maneuvering behavior. A cost for each trajectory of the set of trajectories may be determined, and one of the trajectories of the set of trajectories may be selected based on the determined costs. The vehicle may be maneuvered in the autonomous driving mode according to the selected one of the trajectories.

A control system 9 according to the present invention is mounted on a moving object. The control system 9 includes: an observing device 92 which transmits observation result data indicating an observation result of surroundings of the moving object; a first control instruction device 91 which transmits first control data indicating the control contents determined based on the observation result data; a movement control device 93 which controls movement of the moving object; and a relay device 95 which relays the first control data transmitted from the first control instruction device 91, to the movement control device 93. When a second control instruction device 94 which transmits second control data indicating the control contents determined based on the observation result data is provided to the control system 9, the relay device 95 transmits the second control data instead of the first control data, to the movement control device 93.

Herein, a “perception statistical performance model” (PSPM) for modelling a perception slice of a runtime stack for an autonomous vehicle or other robotic system may be used e.g. for safety/performance testing. A PSPM is configured to receive a computed perception ground truth, and determine from the perception ground truth, based on a set of learned parameters, a probabilistic perception uncertainty distribution, the parameters learned from a set of actual perception outputs generated using the perception slice to be modelled. A simulated scenario is run based on a time series of such perception outputs (with modelled perception errors), but can also be re-run based on perception ground truths directly (without perception errors). This can, for example, be way to ascertain whether perception error was the cause of some unexpected decision within the planner, by determining whether such a decision is also taken in the simulated scenario when perception error is “switched off”.

A vehicle control device includes a memory configured to store relationship definition data that defines a relationship between a state of a vehicle and an action variable, which is a variable relating to an operation of electronic equipment in the vehicle, and a processor. The processor is configured to execute acquisition processing of acquiring a detection value of a sensor, operation processing of operating the electronic equipment, reward calculation processing, update processing of updating the relationship definition data, detection processing, and switching processing of switching the relationship definition data to post-treatment data. The processor is configured to, based on the update mapping, output the relationship definition data updated to increase an expected return on the reward when the electronic equipment is operated in compliance with the relationship definition data.

A vehicle controller, a vehicle control system, a vehicle learning device, a vehicle control method, and a memory medium are provided. A switching process switches relationship defining data used in an operation process to post-measure data, when a detection process detects that a functional recovery measure has been taken. The switching process includes a process that uses, as the post-measure data, initial data that is the relationship defining data of a state before an update process is executed as the vehicle travels.