Pony Ai Inc.

Yiming Liu

Xiang Yu

Tiancheng Lou

Jun Peng

Hao Song

Sinan Xiao

Zhuo Zhang

Tianyi Li

Jie Hou

Kai Chen

Bo Xiao

Yubo Zhang

Zichao Qi

Yin Zhong

Zhenhao Pan

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

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 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

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.

Camera multi-lens mount for assisted-driving vehicle

Systems, methods, and non-transitory computer readable media configured to generate enhanced three-dimensional information. Three-dimensional information of a scene may be obtained. The three-dimensional information may define a three-dimensional point cloud model of the scene. The three-dimensional information may be determined based on distances of the scene from a location. Image information may be obtained. The image information may define one or more images of an object. The object may be identified based on the image information. A three-dimensional point cloud model of the object may be obtained. Enhanced three-dimensional information of the scene may be generated by inserting the three-dimensional point cloud model of the object into the three-dimensional point cloud model of the scene.

Enhanced three-dimensional training data generation

A system included and a computer-implemented method performed in an autonomous-driving vehicle are described. The system performs: detecting one or more movable objects; determining a target movable object from the one or more detected objects; determining a manner of generating a directed alert notification selectively toward the target movable object; and causing a directed alert notification of the determined manner to be generated toward the target movable object.

Directed alert notification by autonomous-driving vehicle

Systems and methods directed to projecting a current trajectory path of the autonomous vehicle on a surface of road is disclosed. In some embodiments, an autonomous vehicle with a light projector is disclosed, where the light projector is on a top surface of an autonomous vehicle. Additionally, in some embodiments, the autonomous vehicle may include an electronic control unit for controlling an operation of the light projector, where the electronic control unit detects whether the autonomous vehicle is turned on. In further embodiments, the electronic control unit receives data of an environmental condition surrounding the autonomous vehicle and receives an upcoming trajectory path of the autonomous vehicle. The electronic control unit may also project a light from the light projector onto a surface of a road indicating the upcoming trajectory path of the autonomous vehicle.

Growing community of inventors

San Jose, CA, United States of America

Yiming Liu