High-performance road vehicle having: a plurality of replaceable or removable components; a control unit, which controls the operation of the road vehicle; at least one electronic identification device, which is fitted on a corresponding component, has a memory designed to contain at least one unique identifying code of the component and has a first transmission organ designed to send the data contained in the memory; and a second transmission organ, designed to communicate with the first transmission organ and connected to the control unit to allow the control unit to read the univocal identifying code of the component.

A system, method, and device for operations of an electrically motorized vehicle. The vehicle can utilize an electrically motorized wheel to convert a non-motorized wheeled vehicle to an electrically motorized wheeled vehicle. One system includes a server in communication with the device of each of a plurality of electrically motorized wheels, the server operable to track a position of each of the electrically motorized wheels and communicate the position thereof to a transportation network.

A system for control of a mobility device comprising a controller for analyzing data from at least one sensor on the mobility device, wherein the data is used to determine the gait of user. The gait data is then used to provide motion command to an electric motor on the mobility device.

A control system controls a vehicle using a probabilistic motion planner and an adaptive predictive controller. The probabilistic motion planner produces a sequence of parametric probability distributions over a sequence of target states for the vehicle with parameters defining a first and higher order moments. The adaptive predictive controller optimizes a cost function over a prediction horizon to produce a sequence of control commands to one or multiple actuators of the vehicle. The cost function balances a cost of tracking of different state variables in the sequence of the target states defined by the first moments. The balancing is performed by weighting different state variables using one or multiple of the higher order moments of the probability distribution.

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.

Aspects of the subject technology relate to systems and methods for adaptively controlling acceleration of a vehicle employing one pedal driving functionality. A full release of an accelerator pedal of a vehicle is detected while the vehicle travels at a first non-zero speed according to a default accelerator pedal map. When the full release of the accelerator pedal is detected, the vehicle decelerates, and the first accelerator pedal map is switched to an adaptive accelerator pedal map. While the vehicle decelerates, the adaptive accelerator pedal map is adjusted according to reduction of a speed of the vehicle. When a depression of the accelerator pedal to reaccelerate the vehicle pedal is detected while the vehicle decelerates and before the speed of the vehicle reaches zero, the vehicle is controlled to reaccelerate the vehicle according to the adjusted adaptive accelerator pedal map without further decelerating the vehicle.

A method of navigating an autonomous driving vehicle (ADV) includes determining a target function for an open space model based on one or more obstacles and map information within a proximity of the ADV, then iteratively performing first and second quadratic programming (QP) optimizations on the target function. Then, generating a second trajectory based on results of the first and second QP optimizations to control the ADV autonomously using the second trajectory. The first QP optimization is based on fixing a first set of variables of the target function. The second QP optimization is based on maximizing a sum of the distances from the ADV to each of the obstacles over a plurality of points of the first trajectory, and minimizing a difference between a target end-state of the ADV and a determined final state of the ADV using the first trajectory.

A working vehicle includes a steering device including a steering handle, a vehicle body to travel with either manual steering by the steering handle or automatic steering of the steering handle based on a traveling reference traveling line, and a controller to permit automatic steering based on steering angles of the steering device obtained when the vehicle body travels a predetermined distance while being steered by the manual steering.

A system for control of a mobility device comprising a controller for analyzing data from at least one sensor on the mobility device, wherein the data is used to determine the gait of user. The gait data is then used to provide motion command to an electric motor on the mobility device.

Provided is an Artificial Intelligence (AI) system for simulating a human brain's functions, such as recognition, decision, etc., by using a machine learning algorithm such as deep learning, etc. and applications of the AI system. Provided is an electronic device including: a camera configured to capture an outside image of a vehicle, and a processor configured to execute one or more instructions stored in a memory, wherein the processor executes the one or more instructions to: determine, from the captured image, at least one object for estimating lane information; estimate, from the image, lane information of a road on which the vehicle is traveling, based on a distance between the determined at least one object and the vehicle and a vanishing point of the image; and output guide information for guiding driving of the vehicle based on the estimated lane information.