Pony Ai Inc.

Hao Song

Xiang Yu

Tiancheng Lou

Jun Peng

Sinan Xiao

Yiming Liu

Tianyi Li

Zhuo Zhang

Kai Chen

Jie Hou

Nengxiu Deng

Yubo Zhang

Bo Xiao

Tao Qin

Jianan Wang

Zichao Qi

Yin Zhong

Mengda Yang

Zhenhao Pan

Xing Xing He

Haoying Fu

Zhou Zhang

Systems, methods, and non-transitory computer-readable media are provided for implementing a tracking camera system onboard an autonomous vehicle. Coordinate data of an object can be received. The tracking camera system actuates, based on the coordinate data, to a position such that the object is in view of the tracking camera system. Vehicle operation data of the autonomous vehicle can be received. The position of the tracking camera system can be adjusted, based on the vehicle operation data, such that the object remains in view of the tracking camera system while the autonomous vehicle is in motion. A focus of the tracking camera system can be adjusted to bring the object in focus. The tracking camera system captures image data corresponding to the object.

Systems and methods for implementing a tracking camera system onboard an autonomous vehicle

A set of sensor information may include first sensor information generated based on a first sensor of a first vehicle and second sensor information generated based on a second sensor of a second vehicle. Individual sensor information may characterize positions of objects in an environment of individual sensors. Relevant sensor information for a vehicle may be determined based on the set of sensor information and a position of the vehicle. The relevant sensor information may characterize positions of objects in a maneuver environment of the vehicle. A desired navigation of the vehicle in the maneuver environment of the vehicle may be determined based on the relevant sensor information. An instruction may be provided to the vehicle based on the desired navigation of the vehicle. The instruction may characterize one or more maneuvers to be performed by the vehicle to execute the desired navigation.

Distributed sensing for vehicle navigation

A computer-implemented method and a system for training a computer-based autonomous driving model used for an autonomous driving operation by an autonomous vehicle are described. The method includes: creating time-dependent three-dimensional (3D) traffic environment data using at least one of real traffic element data and simulated traffic element data; creating simulated time-dependent 3D traffic environmental data by applying a time-dependent 3D generic adversarial network (GAN) model to the created time-dependent 3D traffic environment data; and training a computer-based autonomous driving model using the simulated time-dependent 3D traffic environmental data.

Generative adversarial network enriched driving simulation

An adaptive filter system and a method for controlling the adaptive filter system are described herein. The system can includes one or more filters to attenuate incoming light. The one or more filters can be moved by one or more actuators. The method can capture image data from an imaging device through the one or more filters. Information can be determined from the captured image data. The one or more filters can be moved to a position for capturing image data based on the information.

Adaptive filter system for self-driving vehicle

Systems, methods, and non-transitory computer readable media configured to generate enhanced training information. Training information may be obtained. The training information may characterize behaviors of moving objects. The training information may be determined based on observations of the behaviors of the moving objects. Behavior information may be obtained. The behavior information may characterize a behavior of a given object. Enhanced training information may be generated by inserting the behavior information into the training information.

Enhanced training information generation

Systems, methods, and non-transitory computer readable media may be configured to characterize optical characteristics of optical elements. An optical element mount may be configured to carry an optical element. A calibration display may be configured to display a calibration object. The calibration object may include a known visual pattern. Multiple images of the calibration object may be obtained. The multiple images may be acquired using the optical element carried by the optical element mount. The multiple images may include different perspectives of the calibration object. Optical characteristics of the optical element may be characterized based on the known visual pattern and the different perspectives of the calibration object.

Characterizing optical characteristics of optical elements

A method comprises obtaining autonomous vehicle sensor data of an autonomous vehicle. One or more autonomous vehicle actions of the autonomous vehicle are predicted based on the autonomous vehicle sensor data. Interactive content is identified from a library of interactive content. The interactive content is adjusted based on the predicted one or more autonomous vehicle actions, and the adjusted interactive content is presented within the autonomous vehicle.

Systems and methods for autonomous vehicle interactive content presentation

A system included and a computer-implemented method performed in an autonomous-driving vehicle are described. The system performs: detecting a wireless push signal transmitted from a signal transmitter accompanied by an off-vehicle passer and received by a signal receiver of the autonomous-driving vehicle, the wireless push signal including information about a motion capability level of the off-vehicle passer, determining a position and a motion capability level of the off-vehicle passer at least based on the wireless push signal, and controlling a locomotive mechanism of the autonomous-driving vehicle based on the determined position and motion capability level of the off-vehicle passer.

Active off-vehicle notification to autonomous-driving vehicle

Systems and methods are provided for segmenting a data frame to be acquired into a number of incremental data of equal data length. A first incremental data of the data frame can be acquired from one or more sensors. The first incremental data of the data frame can be processed while a next incremental data of the data frame is being acquired from the one or more sensors. The acquiring and processing of incremental data of the data frame can continue until a last incremental data of the data frame is acquired and processed. Processed incremental data can be outputted as a processed data frame.

System and method for incremental data processing

A lens mount apparatus mountable on a vehicle and a method for controlling a lens mount apparatus are described. The lens mount apparatus includes a plurality of lenses concentrically arranged around a center, and the plurality of lenses include a first lens having a first focal length and a second lens having a second focal length that is shorter than the first focal length. The method includes positioning one of the plurality of lenses, such that one of the lenses that has a focal length suitable for capturing an object is used for image capturing.

Growing community of inventors

Sunnyvale, CA, United States of America

Hao Song