Patents by Inventor Kunsong Shi

Kunsong Shi 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).

  • Publication number: 20250225871
    Abstract: This application describes a proactive sensing system for an autonomous vehicle. This system fuses vehicle sensing data and sensing data from a roadside unit, a Traffic Control Unit, and/or a cloud to provide full 360-degree coverage and birds-eye view of the driving environment. This proactive sensing system cooperatively uses vehicle-based sensor data and sensor data from external sources to provide better and more efficient sensing of longtail or corner cases, such as blind spots and blockage by surrounding objects. Specifically, this proactive sensing system effectively identifies major sensing points where vulnerable road users, such as pedestrians and bicycles, are major challenges for autonomous vehicles at intersections, roundabouts, or work zones. Accordingly, the technology significantly improves the safety of autonomous vehicles.
    Type: Application
    Filed: February 27, 2025
    Publication date: July 10, 2025
    Inventors: Bin Ran, Rui Gan, Sicheng Fu, Yang Cheng, Tianyi Chen, Yifan Yao, Keshu Wu, Kunsong Shi, Huachun Tan, Zhen Zhang, Xiaotian Li, Shuoxuan Dong
  • Patent number: 12326731
    Abstract: The technology relates to a systematic intelligent system (SIS) configured to share data and allocate computing resources among automated driving systems (ADS), e.g., using unified data specifications and interfaces. The SIS comprises systematic intelligent units (SIU) that serve components of ADS, including vehicle intelligent units (VIU) and roadside intelligent units (RIU), and is configured to perform methods to serve an entire trip.
    Type: Grant
    Filed: November 30, 2021
    Date of Patent: June 10, 2025
    Assignee: CAVH LLC
    Inventors: Tianyi Chen, Bin Ran, Shuoxuan Dong, Keshu Wu, Yang Cheng, Linheng Li, Shen Li, Xiaotian Li, Yanghui Mo, Yifan Yao, Kunsong Shi, Haotian Shi, Hanchu Li
  • Publication number: 20250159443
    Abstract: This invention presents a vehicle safety system (VSS) for autonomous vehicles (AVs) utilizing an onboard unit (OBU) capable of communicating with various entities, comprising roadside units (RSUs), other OBUs, and cloud platforms. The OBU incorporates a safety subsystem designed to implement proactive, active, and passive safety measures. The proactive safety measures comprise incident prediction and warnings. The active safety measures comprise emergency braking, and the passive safety measures comprise incident response and dynamic routing. This VSS can be further enhanced by incorporating sensing and processing capabilities of the RSU network or the cloud platform, enabling distributed and integrated safety functions and improved environmental awareness. The system aims to enhance AV safety by addressing incidents before, during, and after their occurrence through comprehensive safety measures at a system level, comprising a vehicle centric system, a vehicle-road system, or a vehicle cloud system.
    Type: Application
    Filed: January 14, 2025
    Publication date: May 15, 2025
    Inventors: Bin Ran, Weizhe Tang, Sicheng Fu, Yang Cheng, Shen Li, Zhen Zhang, Huachun Tan, Tianyi Chen, Shuoxuan Dong, Kunsong Shi, Linhui Ye, Qin Li, Zhijun Chen, Linchao Li, Linghui Xu, Xia Wan, Xiaoxuan Chen
  • Publication number: 20250150791
    Abstract: This technology provides systems and methods for a vehicle computing system (VCS) for autonomous driving. This VCS furnishes End-to-End models that provide sensing, prediction, planning, decision-making, and control functions. The VCS executes vehicle control algorithms, trains general AI models, and makes inferences from those AI models. Specifically, a computing subsystem of the VCS performs computation methods that train a tensor-centered model and/or make inferences from a tensor-centered model. Additionally, the VCS gathers data from a roadside unit network, an onboard unit, a cloud platform, a traffic control center/traffic control unit, and a traffic operations center (TOC), thereby enhancing the safety and efficiency of autonomous driving.
    Type: Application
    Filed: January 6, 2025
    Publication date: May 8, 2025
    Inventors: Bin Ran, Bingjie Liang, Yan Zhao, Zhiyu Wang, Yang Cheng, Shen Li, Zhen Zhang, Huachun Tan, Tianyi Chen, Shuoxuan Dong, Kunsong Shi, Linhui Ye, Qin Li, Zhijun Chen, Linchao Li, Linghui Xu, Xia Wan, Xiaoxuan Chen
  • Publication number: 20250150792
    Abstract: The invention provides systems and methods for a vehicle-based cloud computing system (VCCS) for autonomous driving. This VCCS builds world models based on a series of complex scenario data to optimize sensing, prediction, planning, decision making, and control for autonomous driving. The VCCS can execute vehicle control algorithms, train general AI models, and make inferences to optimize autonomous driving. Specifically, it dynamically adjusts driving strategies based on long tail scenarios including but not limited to weather, work zone information, and traffic status, ensuring safe and efficient vehicle operation. Additionally, the VCCS can gather supplementary data from (a) a roadside unit (RSU) network, (b) another OBU, (c) a cloud platform, (d) a traffic control center/traffic control unit (TCC/TCU), and (e) a traffic operations center (TOC), thereby further improving control and efficiency in complex driving environments.
    Type: Application
    Filed: January 13, 2025
    Publication date: May 8, 2025
    Inventors: Bin Ran, Bingjie Liang, Renfei Wu, Yan Zhao, Yang Cheng, Shen Li, Zhen Zhang, Huachun Tan, Tianyi Chen, Shuoxuan Dong, Kunsong Shi, Linhui Ye, Qin Li, Zhijun Chen, Linchao Li, Linghui Xu, Xia Wan, Xiaoxuan Chen
  • Patent number: 12279191
    Abstract: Provided herein is technology relating to aspects of a Distributed Driving System (DDS) for managing Connected and Automated Vehicles (CAV) and particularly, but not exclusively, to systems, designs, and methods for a Device Allocation System (DAS) configured to allocate and distribute resources to devices of a Distributed Driving Systems (DDS).
    Type: Grant
    Filed: March 4, 2021
    Date of Patent: April 15, 2025
    Assignee: CAVH LLC
    Inventors: Bin Ran, Shuoxuan Dong, Yang Cheng, Tianyi Chen, Shen Li, Xiaotian Li, Kunsong Shi, Haotian Shi, Keshu Wu, Yifan Yao, Ran Yi
  • Patent number: 12266262
    Abstract: Provided herein is a technology for an Autonomous Vehicle Cloud System (AVCS). This AVCS provides sensing, data fusion, prediction, decision-making, and/or control instructions for specific vehicles at a microscopic level based on data from one or more of other vehicles, roadside unit (RSU), cloud-based platform, and traffic control center/traffic control unit (TCC/TCU). Specifically, the AVs can be effectively and efficiently operated and controlled by the AVCS. The AVCS provides individual vehicles with detailed time-sensitive control instructions for fulfilling driving tasks, including car following, lane changing, route guidance, and other related information. The AVCS is configured to predict individual vehicle behavior and provide planning and decision-making at a microscopic level. In addition, the AVCS is configured to provide one or more of virtual traffic light management, travel demand assignment, traffic state estimation, and platoon control.
    Type: Grant
    Filed: July 28, 2023
    Date of Patent: April 1, 2025
    Assignee: CAVH LLC
    Inventors: Bin Ran, Yuan Zheng, Can Wang, Yang Cheng, Yifan Yao, Keshu Wu, Tianyi Chen, Haotian Shi, Shen Li, Kunsong Shi, Zhen Zhang, Fan Ding, Huachun Tan, Yuankai Wu, Shuoxuan Dong, Linhui Ye, Xiaotian Li
  • Patent number: 12260746
    Abstract: Provided herein is a technology for an Autonomous Vehicle Intelligent System (AVIS), which facilitates vehicle operations and control for autonomous driving. The AVIS and related methods provide vehicles with vehicle-specific information for a vehicle to perform driving tasks such as car following, lane changing, and route guidance. The AVIS comprises an onboard unit (OBU), wherein the OBU comprises a communication module communicating with one or more of other autonomous vehicles (AV), a roadside unit (RSU), a cloud platform, and a traffic control center/traffic control unit (TCC/TCU). The AVIS implements one or more of the following functions: sensing, prediction, decision-making, and vehicle control using onboard information and vehicle-specific information received from other AVs, the RSU, the cloud platform, and/or the TCC/TCU.
    Type: Grant
    Filed: July 28, 2023
    Date of Patent: March 25, 2025
    Assignee: CAVH LLC
    Inventors: Bin Ran, Bingjie Liang, Yan Zhao, Yang Cheng, Yifan Yao, Keshu Wu, Tianyi Chen, Haotian Shi, Shen Li, Kunsong Shi, Zhen Zhang, Fan Ding, Huachun Tan, Yuankai Wu, Shuoxuan Dong, Linhui Ye, Xiaotian Li
  • Publication number: 20250095480
    Abstract: The invention provides systems and methods for a computing power allocation system for autonomous driving (CPAS-AD), which is a component of an Intelligent Road Infrastructure System (IRIS). The CPAS-AD incorporates advanced computing capabilities that effectively allocate computational power for sensing, prediction, planning, decision-making, and control functions to enable end-to-end driving functions. In addition to the vehicle, the CPAS-AD can acquire additional computation resources from one or more of: (a) a roadside unit (RSU) network, (b) a cloud platform, (c) a traffic control center/traffic control unit (TCC/TCU), and (d) a traffic operations center (TOC). Additionally, tailored to different traffic scenarios, the CPAS-AD can allocate data and computation resources (including but not limited to CPU and GPU) for vehicle sensing, prediction, planning, decision-making, and control functions, thereby enabling safe and efficient autonomous driving.
    Type: Application
    Filed: November 26, 2024
    Publication date: March 20, 2025
    Inventors: Bin Ran, Bingjie Liang, Yan Zhao, Haozhan Ma, Renfei Wu, Yang Cheng, Yifan Yao, Keshu Wu, Tianyi Chen, Haotian Shi, Shen Li, Kunsong Shi, Zhen Zhang, Fan Ding, Huachun Tan, Yuankai Wu, Shuoxuan Dong, Linhui Ye, Xiaotian Li
  • Publication number: 20250087081
    Abstract: The invention provides systems and methods for a function-based computing power allocation system (FCPAS), which is a component of an Intelligent Road Infrastructure System (IRIS). The FCPAS incorporates advanced computing capabilities that effectively allocate computational power for prediction, planning, and decision making functions. Specifically, through the FCPAS, an AV can acquire additional computational resources for vehicle prediction, planning, and decision-making functions, thereby enabling safe and efficient autonomous driving. Additionally, tailored to different traffic scenarios, the FCPAS can allocate data and computational resources (including but not limited to CPU and GPU) for vehicle automation.
    Type: Application
    Filed: November 26, 2024
    Publication date: March 13, 2025
    Inventors: Bin Ran, Bingjie Liang, Yan Zhao, Zhiyu Wang, Junfeng Jiang, Yang Cheng, Yifan Yao, Keshu Wu, Tianyi Chen, Haotian Shi, Shen Li, Kunsong Shi, Zhen Zhang, Fan Ding, Huachun Tan, Yuankai Wu, Shuoxuan Dong, Linhui Ye, Xiaotian Li
  • Patent number: 12243423
    Abstract: The technology provided herein relates to a roadside infrastructure sensing system for Intelligent Road Infrastructure Systems (IRIS) and, in particular, to devices, systems, and methods for data fusion and communication that provide proactive sensing support to connected and automated vehicle highway (CAVH) systems.
    Type: Grant
    Filed: August 2, 2022
    Date of Patent: March 4, 2025
    Assignee: CAVH LLC
    Inventors: Bin Ran, Huachun Tan, Zhen Zhang, Yang Cheng, Xiaotian Li, Tianyi Chen, Shuoxuan Dong, Kunsong Shi
  • Patent number: 12219445
    Abstract: This technology provides designs and methods for the vehicle on-board unit (OBU), which facilitates vehicle operations and control for connected automated vehicle highway (CAVH) systems. OBU systems provide vehicles with individually customized information and real-time control instructions for vehicle to fulfill the driving tasks such as car following, lane changing, route guidance. OBU systems also realize transportation operations and management services for both freeways and urban arterials. The OBU composed of the following devices: 1) a vehicle motion state parameter and environment parameter collection unit; 2) a multi-mode communication unit; 3) a location unit; 4) an intelligent gateway unit, and 5) a vehicle motion control unit. The OBU systems realize one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control.
    Type: Grant
    Filed: July 8, 2019
    Date of Patent: February 4, 2025
    Assignee: CAVH LLC
    Inventors: Shen Li, Bin Ran, Zhen Zhang, Yang Cheng, Huachun Tan, Tianyi Chen, Shuoxuan Dong, Kunsong Shi, Linhui Ye, Qin Li, Zhijun Chen, Linchao Li, Linghui Xu, Xia Wan, Xiaoxuan Chen
  • Publication number: 20240386793
    Abstract: The invention provides a roadside computing system (RCS), or an edge computing system, for an autonomous vehicle. The RCS comprises a hierarchy of roadside unit (RSU) and an onboard unit (OBU) in an individual vehicle. The RSU comprises a data processing module and a communication module, and is capable of generating guidance information and targeted instructions for individual vehicle. The data processing module of the RSU comprises two processors: an External Object Calculating Module (EOCM) and an AI processing unit. Thus, the RCS utilizes roadside edge computing power and AI models to support autonomous driving for the vehicle. The OBU comprises a data processing module, a communication module, and a vehicle control module, and is capable of generating vehicle-specific targeted instruction for the vehicle based on guidance information and targeted instructions received from RSUs, and controlling the vehicle based on vehicle-specific targeted instruction.
    Type: Application
    Filed: June 4, 2024
    Publication date: November 21, 2024
    Inventors: Bin Ran, Bocheng An, Zhi Zhou, Min Li, Keshu Wu, Yang Cheng, Yifan Yao, Haotian Shi, Tianyi Chen, Shen Li, Kunsong Shi, Zhen Zhang, Fan Ding, Huachun Tan, Yuankai Wu, Shuoxuan Dong, Linhui Ye, Xiaotian Li
  • Publication number: 20240359708
    Abstract: Provided herein is an artificial intelligence-based mobile roadside intelligent unit (MRIU) for providing, supplementing, and/or enhancing the control and operation of autonomous vehicles in normal and long-tail scenarios. The MRIU comprises a computing module configured to provide supplemental computation capability for autonomous driving. The MRIU comprises a communication module to communicate and exchange data with a vehicle or a cloud. The MRIU provides prediction, decision-making, and/or control functions for autonomous driving. The MRIU provides edge computing capability for autonomous vehicles to train and operate artificial intelligence-based intelligent driving models in a distributed fashion. Specifically, an edge computing unit conducts data fusion and data feature extraction, provides prediction, formulates control strategies, generates vehicle control instructions, and/or distributes vehicle control information and/or instructions for an autonomous vehicle.
    Type: Application
    Filed: July 10, 2024
    Publication date: October 31, 2024
    Inventors: Bin Ran, Wenqi Lu, Bingjie Liang, Linheng Li, Ziwei Yi, Tianyi Chen, Yang Cheng, Yifan Yao, Keshu Wu, Kunsong Shi
  • Publication number: 20240355203
    Abstract: This invention presents an automated driving system with distributed computing (ADS-DC). During the operation of a connected automated vehicle (CAV), some or all of its automated driving capabilities for sensing, prediction, planning, decision-making, or control may be downgraded due to long-tail events or malfunctions. The intelligent roadside toolbox (IRT) functions as an edge server or a cloud, and can supplement CAV's sensing functions, prediction and management functions, planning and decision-making functions, and vehicle control functions by providing customized, on-demand, and dynamic computing resources and functions to the CAV. In addition, the IRT computing functions provide the computation support for sensing, prediction, planning, decision-making, and/or control functions of said CAV. Namely, the IRT functions as an edge server or a cloud to provide processing, training or optimization of CAV driving models as well as facilitate the implementation of the driving models in the CAV.
    Type: Application
    Filed: July 3, 2024
    Publication date: October 24, 2024
    Inventors: Bin Ran, Sicheng Fu, Rui Gan, Yang Cheng, Shen Li, Kexin Tian, Tianyi Chen, Shuoxuan Dong, Kunsong Shi, Haotian Shi, Xiaotian Li
  • Publication number: 20240351616
    Abstract: This invention presents a function allocation system for an autonomous vehicle (AV). During the operations of the AV, some or all of its automated driving capabilities or functions could be downgraded due to long-tail events or malfunctioning. The roadside intelligent infrastructure, or the cloud platform, could supplement some or all of AV's automated driving functions, including sensing, prediction and decision-making, and/or control functions. The function allocation system dynamically allocates these functions between AV and intelligent infrastructure, achieving a higher system intelligence level S than the downgraded vehicle intelligence level V. In addition, a function allocation system could dynamically allocate sensing, prediction and decision-making, and/or control functions between AV and a cloud platform. This invention also presents a function integration system or a fusion system for an AV.
    Type: Application
    Filed: July 2, 2024
    Publication date: October 24, 2024
    Inventors: Bin Ran, Junwei You, Keshu Wu, Weizhe Tang, Yang Cheng, Yifan Yao, Tianyi Chen, Shuoxuan Dong, Mingheng Zhang, Xiaotian Li, Shen Li, Kunsong Shi, Haotian Shi, Yanghui Mo, Hongjie Liu, Ran Yi
  • Publication number: 20240343269
    Abstract: This technology relates to autonomous vehicle (AV) control systems tailored for critical points of a partially instrumented infrastructure. The first system integrates an onboard unit (OBU) and communication modules to interact with roadside units (RSUs) or a cloud platform, delivering time-sensitive control instructions to vehicles at critical points. The OBUs execute these instructions for driving tasks. The second system combines an OBU with a cloud platform, leveraging cloud services for enhanced functionality like storage and computing. It adapts to diverse critical point scenarios, employing proactive incident prediction and rapid detection methods for optimized performance.
    Type: Application
    Filed: April 8, 2024
    Publication date: October 17, 2024
    Inventors: Bin Ran, Peipei Mao, Linheng Li, Yang Cheng, Tianyi Chen, Yang Zhou, Zhen Zhang, Xiaotian Li, Shen Li, Shuoxuan Dong, Kunsong Shi
  • Publication number: 20240331529
    Abstract: The invention provides a vehicle AI computing system (VACS) that supports autonomous driving through an Onboard Unit (OBU) for vehicle-based computing and distributed computing based on vehicle road-cloud. The vehicle-based computing can effectively complete various computational tasks by using onboard computing resources. The distributed computing allows the vehicle to work in collaboration with roadside units (RSUs) and/or the cloud to effectively complete various computational tasks. The VACS features an OBU with a sensing module, a communication module, and a data processing module that integrates data from vehicle sensors, RSUs, and the cloud. The OBU also includes a vehicle control module that helps control the vehicle based on the data of RSU and cloud. The VACS leverages high performance computation resources to implement end to end driving tasks including sensing, prediction, planning and decision making, and control.
    Type: Application
    Filed: June 13, 2024
    Publication date: October 3, 2024
    Inventors: Bin Ran, Zhiyu Wang, Renfei Wu, Junfeng Jiang, Yang Cheng, Keshu Wu, Yifan Yao, Tianyi Chen, Haotian Shi, Shen Li, Kunsong Shi, Zhen Zhang, Fan Ding, Huachun Tan, Yuankai Wu, Shuoxuan Dong, Linhui Ye, Xiaotian Li
  • Patent number: 12043288
    Abstract: Provided herein is technology relating to automated driving and particularly, but not exclusively, to a mobile intelligent road infrastructure technology configured to serve automated driving systems by providing, supplementing, and/or enhancing autonomous driving functions for connected automated vehicles under common and unusual driving scenarios.
    Type: Grant
    Filed: February 18, 2022
    Date of Patent: July 23, 2024
    Assignee: CAVH LLC
    Inventors: Bin Ran, Wenqi Lu, Tianyi Chen, Yang Cheng, Linheng Li, Bingjie Liang, Yifan Yao, Kunsong Shi, Keshu Wu
  • Patent number: 12046136
    Abstract: Provided herein is technology related to a distributed driving system (DDS) by using flexible, on-demand, and customized resources and functions from an intelligent roadside toolbox (IRT). These resources comprise computational resources, cloud resources, system security resources, backup and redundancy resources. The functions comprise sensing, transportation behavior prediction and management, planning and decision-making, and vehicle control functions. The DDS and IRT technologies described herein are vehicle oriented, modular, and customizable for each vehicle to meet the specific needs of each individual vehicle as an on-demand and dynamic service. The DDS is configured to provide customized, on-demand, and dynamic IRT resources and functions to individual CAVs to supplement the CAV's sensing, transportation behavior prediction and management, planning and decision-making, and/or vehicle control.
    Type: Grant
    Filed: July 13, 2023
    Date of Patent: July 23, 2024
    Assignee: CAVH LLC
    Inventors: Bin Ran, Yang Cheng, Shen Li, Kexin Tian, Tianyi Chen, Shuoxuan Dong, Kunsong Shi, Haotian Shi, Xiaotian Li