Patents by Inventor Sinan Xiao
Sinan Xiao has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11899455Abstract: A method comprises obtaining smart seat sensor data, the smart seat sensor data being detected by a tactile-sensitive surface material of a seat of an autonomous vehicle in response to a user interacting with the tactile-sensitive surface material. Other sensor data is obtained from one or more other sensors disposed within the autonomous vehicle. The smart seat sensor data and the other sensor data are integrated. A behavior of the user is estimated based on the integrated data, and the autonomous vehicle is controlled based on the estimated behavior of the user.Type: GrantFiled: June 6, 2022Date of Patent: February 13, 2024Assignee: Pony AI Inc.Inventor: Sinan Xiao
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Patent number: 11774978Abstract: 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.Type: GrantFiled: July 18, 2022Date of Patent: October 3, 2023Assignee: Pony AI Inc.Inventors: Hao Song, Jun Peng, Nengxiu Deng, Sinan Xiao, Tao Qin, Tiancheng Lou, Tianyi Li, Xiang Yu, Yubo Zhang
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Patent number: 11716542Abstract: 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.Type: GrantFiled: April 25, 2022Date of Patent: August 1, 2023Assignee: Pony AI Inc.Inventors: Kai Chen, Jun Peng, Tiancheng Lou, Xiang Yu, Zhuo Zhang, Hao Song, Sinan Xiao, Yiming Liu, Tianyi Li
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Patent number: 11535274Abstract: Provided herein is a system of a vehicle that comprises one or more sensors, one or more processors, and memory storing instructions that, when executed by the one or more processors, causes the system to perform: selecting a trajectory along a route of the vehicle; predicting a trajectory of another object along the route; adjusting the selected trajectory based on a predicted change, in response to adjusting the selected trajectory, to the predicted trajectory of the another object, the predicted change to the predicted trajectory of the another object being stored in a model; determining an actual change, in response to adjusting the selected trajectory, to a trajectory of the another object, in response to an interaction between the vehicle and the another object; updating the model based on the determined actual change to the trajectory of the another object; and selecting a future trajectory based on the updated model.Type: GrantFiled: March 26, 2020Date of Patent: December 27, 2022Assignee: Pony AI Inc.Inventors: Robert Dingli, Peter G. Diehl, Sinan Xiao
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Patent number: 11529950Abstract: 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.Type: GrantFiled: September 8, 2020Date of Patent: December 20, 2022Assignee: Pony AI Inc.Inventors: Bo Xiao, Yiming Liu, Sinan Xiao, Xiang Yu, Tiancheng Lou, Jun Peng, Jie Hou, Zhuo Zhang, Hao Song
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Publication number: 20220350339Abstract: 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.Type: ApplicationFiled: July 18, 2022Publication date: November 3, 2022Inventors: Hao Song, Jun Peng, Nengxiu Deng, Sinan Xiao, Tao Qin, Tiancheng Lou, Tianyi Li, Xiang Yu, Yubo Zhang
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Patent number: 11474125Abstract: Systems, methods, and non-transitory computer readable media may be configured to calibrate sensor measurements based on detection of brake light. Acceleration information of a first vehicle may be obtained. The acceleration information may define an acceleration probability distribution of the first vehicle. Image information may be obtained. The image information may define an image of the first vehicle. Whether a brake light of the first vehicle is on or off may be determined based on the image of the first vehicle. Based on a determination that the brake light of the first vehicle is on, a calibrated acceleration probability distribution of the first vehicle may be generated based on the acceleration probability distribution of the first vehicle and a braking-calibration curve.Type: GrantFiled: November 16, 2018Date of Patent: October 18, 2022Assignee: Pony AI Inc.Inventors: Zixuan Zhou, Sinan Xiao, Xiang Yu, Tiancheng Lou, Jun Peng
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Publication number: 20220308582Abstract: A method comprises obtaining smart seat sensor data, the smart seat sensor data being detected by a tactile-sensitive surface material of a seat of an autonomous vehicle in response to a user interacting with the tactile-sensitive surface material. Other sensor data is obtained from one or more other sensors disposed within the autonomous vehicle. The smart seat sensor data and the other sensor data are integrated. A behavior of the user is estimated based on the integrated data, and the autonomous vehicle is controlled based on the estimated behavior of the user.Type: ApplicationFiled: June 6, 2022Publication date: September 29, 2022Inventor: Sinan Xiao
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Patent number: 11438492Abstract: 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.Type: GrantFiled: June 2, 2020Date of Patent: September 6, 2022Assignee: Pony AI Inc.Inventors: Yubo Zhang, Xiang Yu, Tiancheng Lou, Jun Peng, Kai Chen, Yiming Liu, Sinan Xiao, Tianyi Li, Yin Zhong, Hao Song
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Publication number: 20220247913Abstract: 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.Type: ApplicationFiled: April 25, 2022Publication date: August 4, 2022Inventors: Kai Chen, Jun Peng, Tiancheng Lou, Xiang Yu, Zhuo Zhang, Hao Song, Sinan Xiao, Yiming Liu, Tianyi Li
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Patent number: 11392132Abstract: 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.Type: GrantFiled: September 8, 2020Date of Patent: July 19, 2022Assignee: Pony AI Inc.Inventors: Hao Song, Jun Peng, Nengxiu Deng, Sinan Xiao, Tao Qin, Tiancheng Lou, Tianyi Li, Xiang Yu, Yubo Zhang
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Patent number: 11353872Abstract: A method comprises obtaining one or more parameters of an autonomous vehicle, the parameters including any of a position, path, and/or speed of the autonomous vehicle. The method further includes identifying, based on the one or more parameters of the autonomous vehicle, a region of interest from a plurality of regions surrounding the autonomous vehicle. The method further includes controlling, based on the region of interest, one or more sensors mounted on a surface of the autonomous vehicle to capture sensor data of the region of interest and not capture sensor data from the one or more other regions of the plurality of regions surrounding the autonomous vehicle. The method further includes providing the captured sensor data to a processor, the processor being capable of facilitating, based on the captured sensor data of the region of interest, one or more autonomous vehicle driving actions.Type: GrantFiled: July 26, 2019Date of Patent: June 7, 2022Assignee: Pony AI Inc.Inventor: Sinan Xiao
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Patent number: 11353871Abstract: A method comprises obtaining smart seat sensor data, the smart seat sensor data being detected by a tactile-sensitive surface material of a seat of an autonomous vehicle in response to a user interacting with the tactile-sensitive surface material. Other sensor data is obtained from one or more other sensors disposed within the autonomous vehicle. The smart seat sensor data and the other sensor data are integrated. A behavior of the user is estimated based on the integrated data, and the autonomous vehicle is controlled based on the estimated behavior of the user.Type: GrantFiled: July 26, 2019Date of Patent: June 7, 2022Assignee: Pony AI Inc.Inventor: Sinan Xiao
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Patent number: 11317033Abstract: 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.Type: GrantFiled: July 14, 2020Date of Patent: April 26, 2022Assignee: Pony AI Inc.Inventors: Kai Chen, Jun Peng, Tiancheng Lou, Xiang Yu, Zhuo Zhang, Hao Song, Sinan Xiao, Yiming Liu, Tianyi Li
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Publication number: 20210300412Abstract: Provided herein is a system of a vehicle that comprises one or more sensors, one or more processors, and memory storing instructions that, when executed by the one or more processors, causes the system to perform: selecting a trajectory along a route of the vehicle; predicting a trajectory of another object along the route; adjusting the selected trajectory based on a predicted change, in response to adjusting the selected trajectory, to the predicted trajectory of the another object, the predicted change to the predicted trajectory of the another object being stored in a model; determining an actual change, in response to adjusting the selected trajectory, to a trajectory of the another object, in response to an interaction between the vehicle and the another object; updating the model based on the determined actual change to the trajectory of the another object; and selecting a future trajectory based on the updated model.Type: ApplicationFiled: March 26, 2020Publication date: September 30, 2021Inventors: Robert Dingli, Peter G. Diehl, Sinan Xiao
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Patent number: 11126189Abstract: 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.Type: GrantFiled: March 31, 2020Date of Patent: September 21, 2021Assignee: Pony AI Inc.Inventors: Hao Song, Xiang Yu, Tiancheng Lou, Jun Peng, Yiming Liu, Sinan Xiao
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Patent number: 10887433Abstract: 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.Type: GrantFiled: April 3, 2018Date of Patent: January 5, 2021Assignee: Pony AI Inc.Inventors: Haoying Fu, Mengda Yang, Xiang Yu, Tiancheng Lou, Jun Peng, Sinan Xiao, Tianyi Li, Hao Song
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Publication number: 20200409380Abstract: 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.Type: ApplicationFiled: September 8, 2020Publication date: December 31, 2020Inventors: Hao Song, Jun Peng, Nengxiu Deng, Sinan Xiao, Tao Qin, Tiancheng Lou, Tianyi Li, Xiang Yu, Yubo Zhang
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Publication number: 20200398831Abstract: 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.Type: ApplicationFiled: September 8, 2020Publication date: December 24, 2020Inventors: Bo Xiao, Yiming Liu, Sinan Xiao, Xiang Yu, Tiancheng Lou, Jun Peng, Jie Hou, Zhuo Zhang, Hao Song
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Patent number: 10871628Abstract: 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.Type: GrantFiled: October 31, 2017Date of Patent: December 22, 2020Assignee: Pony AI Inc.Inventors: Kai Chen, Zhenhao Pan, Xiang Yu, Tiancheng Lou, Jun Peng, Yiming Liu, Hao Song, Jie Hou, Zichao Qi, Sinan Xiao