Nio Usa, Inc.

Nio Technology (anhui) Co., Ltd.

Zhongkui Wang

Albert Wu

Arek V Sredzki

Keja S A Rowe

Xu Chen

Tong Lin

Omid Ghasemalizadeh

Hiu Hong Yu

Zhenxiang Jian

Waylon Y Chen

Antonio Antonellis Rufo

A calibration system for multi-sensor extrinsic calibration in a vehicle includes one or more calibration targets provided around an external environment within a threshold distance of the vehicle. Each of the one or more calibration targets includes a combination of sensor targets configured to be measured by and used for calibrating a pair of sensors selected from the group consisting of a first sensor, a second sensor or a third sensor. The system also includes a vehicle placement section configured to accommodate the vehicle on the vehicle placement section for detection of the one or more calibration targets.

High precision multi-sensor extrinsic calibration via production line and mobile station

Systems and methods for controlling a vehicle are described. A processor of a longitudinal planning system determines a state of the vehicle. The processor determines a state of a leader vehicle. The processor, based on the determined state of the vehicle and the determined state of the leader vehicle, determines a critical distance for the vehicle. The processor compares a distance between the vehicle and the leader vehicle with the critical distance. The processor, based on the comparison, determines whether the vehicle is too close to or too far from the leader vehicle. The processor, based on the determination, applies one or more of overshoot constraints, undershoot constraints, and critical constraints. After applying the one or more of overshoot constraints, undershoot constraints, and critical constraints, the processor determines a target acceleration for the vehicle. The processor controls the vehicle to track the target acceleration for the vehicle.

Systems and methods of autonomously controlling vehicle states

Methods and systems for autonomously steering a moving vehicle are disclosed. A processor determines a longitudinal velocity, a longitudinal acceleration, a lateral acceleration, and a yaw rate of the vehicle. The processor estimates, based on the longitudinal velocity, lateral acceleration, and yaw rate of the vehicle, a change in lateral velocity over time. The processor estimates, based on the change in the lateral velocity over time, the yaw rate, a distance between the front axle of the vehicle and a center of gravity of the vehicle, and a distance between the rear axle of the vehicle and the center of gravity of the vehicle, a lateral front velocity of the vehicle and a lateral rear velocity of the vehicle. Using calculations, a state estimation model for the vehicle is updated by the processor using a lateral acceleration bias. The updated state estimation model is used to autonomously steer the vehicle.

Vehicle control system using nonlinear dynamic model states and steering offset estimation

A communication system controller having an input for receiving output signals of a sending device. The communication system controller further has a clock signal. The communication system controller further has an output for transmitting input signals to a target device. The communication system controller further has a signal processing element capable of determining if the received output signals of the sending device are synchronous with the clock signal. The signal processing element is further capable of determining if the received output signals of the sending device are asynchronous with the clock signal. The communication system controller is capable of transmitting the received output signals of the sending device as input signals to the target device if the received output signals of the sending device are determined to be synchronous with the clock signal.

Systems and methods of controlling synchronicity of communication within a network of devices

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San Jose, CA, United States of America

Zhongkui Wang