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.

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.

Abstract: The Intelligent Information Conversion System (IICS) facilitates real-time dynamic information exchange among connected and automated vehicle (CAV), roadside intelligent unit (RIU), and cloud platform. The system comprises a codebook, coding module, connector module, and supporting system. The codebook provides a standardized format for information exchange, using a sequence of integers corresponding to various categories such as vehicle automation level, vehicle type, and road category. The coding module encodes and decodes information to enable seamless communication among CAV, RIU, and cloud platform, optimizing data transmission and service levels for autonomous driving. The system supports sorting, encoding, and decoding information into a codebook string, improving real-time interaction and information flow across connected environments. It enhances vehicle automation and supports dynamic, context sensitive data exchanges between different entities in the autonomous ecosystem.

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).

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.

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.

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.

Abstract: A method of dicing a wafer includes positioning the wafer with its top side on a tape material. The wafer includes a plurality of die separated by scribe streets. A first pass being a first infrared (IR) laser beam is directed at the bottom side with a point of entry within the scribe streets. The first IR laser beam is focused with a focus point embedded within a thickness of the wafer, and has parameters selected to form an embedded crack line within the wafer. The embedded crack line does not reach the top side surface. A second pass being a second IR laser beam is directed at the bottom side having parameters selected to form a second crack line that that has a spacing relative to the embedded crack line, and the second IR laser beam causes the embedded crack line to be extended to the top side surface.

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.

Abstract: Provided herein is technology relating to automated driving and, more particularly, to an automated driving system comprising a Connected Automated Vehicle Subsystem that interacts in real-time with a Connected Automated Highway Subsystem to provide coordinated sensing; coordinated prediction and decision-making; and coordinated control for transportation management and operations and control of connected automated vehicles.

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.

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.

Abstract: The present invention relates to a functional cyclic olefin polymer obtained from hydrogenation of a cyclic olefin polymer, wherein the cyclic olefin polymer comprises at least a monomeric unit A? derived from a monomer A having a norbornene ring and a polar functional group, wherein the amount of the monomeric unit A? is in the range of from 20% to 100% by mole, 50% to 100% by mole, from 60% to 100% by mole, or from 70% to 100% by mole, based on the total amount of the monomeric units of the cyclic olefin polymer. The present invention further relates to a process for producing the functional cyclic olefin polymer, a composition comprising the functional cyclic olefin polymer, and the use of the functional cyclic olefin polymer. The functional cyclic olefin polymer of the present invention exhibits improved properties, especially in terms of mechanical properties and barrier properties.

Abstract: Provided is a remote control device based on computer vision technology, the remote control device includes a main body and a stand base connected with the main body. The main body includes a control unit, an output unit, a power supply unit, and a switch at least partially enclosed by a case. The control unit includes a visual sensor that collects image information and a microcontroller that outputs a control instruction to a controlled device via the output unit according to the image information collected by the visual sensor. The power supply unit is configured to supply power to the control unit and the output unit. The switch is configured to control the working state of the remote control device.

Abstract: Aspects of the present invention allow for real-time people monitoring method and system for estimation of the size and flow density of a given group of people located in a given area of space. The method and system may be used to monitor live or recorded camera input, foreground segmentation, human tracking, height estimation, and dwell estimation. In particular, human detection may be achieved using a spatio-temporal variance analysis calculation methodology for moving target detection.

Abstract: Method and system for objects surveillance and real-time activity recognition is based on analysis of spatio-temporal images of individuals under surveillance where a spatio-temporal volume occupied by each individual is decomposed by crossing the same at specific heights to form 2-dimensional slices, each containing representation of trajectory of the motion of corresponding portions of the individual body. The symmetry of the trajectories (Gait DNA) is analyzed and classified to generate data indicative of a type of activity of the individual based on the symmetry or asymmetry of the Gait DNA in each 2-dimensional slice. An effective occlusion handling ability is implemented which permits to restore the occluded silhouette of an individual.

Abstract: Aspects of the present invention allow for real-time people monitoring method and system for estimation of the size and flow density of a given group of people located in a given area of space. The method and system may be used to monitor live or recorded camera input, foreground segmentation, human tracking, height estimation, and dwell estimation. In particular, human detection may be achieved using a spatio-temporal variance analysis calculation methodology for moving target detection.

Abstract: Method and system for objects surveillance and real-time activity recognition is based on analysis of spatio-temporal images of individuals under surveillance where a spatio-temporal volume occupied by each individual is decomposed by crossing the same at specific heights to form 2-dimensional slices, each containing representation of trajectory of the motion of corresponding portions of the individual body. The symmetry of the trajectories (Gait DNA) is analyzed and classified to generate data indicative of a type of activity of the individual based on the symmetry or asymmetry of the Gait DNA in each 2-dimensional slice. An effective occlusion handling ability is implemented which permits to restore the occluded silhouette of an individual.