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.

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: 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: 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: Provided herein is technology relating to automated driving and particularly, but not exclusively, to an intelligent information conversion system and related methods for providing collaborative automatic driving to intelligent transportation systems, vehicle networking systems, collaborative management control systems, vehicle-road collaborative systems, automated driving systems, and the like.

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.

Abstract: This technology provides an Autonomous Vehicle (AV) Intelligent Control System (ICS) that integrates a sensing module for collecting driving environment data and an onboard unit (OBU) for vehicle control. The OBU includes a vehicle control module and communication modules for interacting with Traffic Control Centers (TCC/TCU) and Roadside Units (RSUs). These modules exchange information at the control level, such as vehicle positioning, speed, and environmental conditions, enabling the AV to operate safely and efficiently. The system also features redundancy through dual-security mechanisms, enhancing safety and reliability. The AV ICS is designed to distribute driving tasks and functions, utilizing both TCC/TCU and RSU data for vehicle control and monitoring, with wireless communication capabilities for seamless information exchange.

Abstract: This technology provides an Autonomous Vehicle (AV) Intelligent Driving System (IDS) that includes a sensing module for gathering driving environment data and an onboard unit (OBU) for vehicle control. The OBU features a vehicle control module and communication modules for guidance-level interaction with Traffic Control Centers (TCC/TCU) and Roadside Units (RSUs). The system receives targeted guidance instructions and information, such as vehicle maneuvering, safety maintenance, traffic control, and special conditions, to enhance driving tasks. The IDS collaborates with TCC/TCU and RSUs, providing redundancy and a fail-safe mechanism for increased safety and reliability. The system is designed with wireless communication capabilities for efficient information exchange and is applicable to connected and automated vehicles (CAVs).

Abstract: Provided herein is technology relating to automated driving and particularly, but not exclusively, to an intelligent information conversion system and related methods for providing collaborative automatic driving to intelligent transportation systems, vehicle networking systems, collaborative management control systems, vehicle-road collaborative systems, automated driving systems, and the like.

Abstract: A webpage generating method includes: obtaining a size of an original design file and layer information of a layer included in the original design file; obtaining a material included in the layer; and generating a webpage according to the size of the original design file, the layer information of the layer, and the material included in the layer.

Abstract: A webpage generating method includes: obtaining a size of an original design file and layer information of a layer included in the original design file; obtaining a material included in the layer; and generating a webpage according to the size of the original design file, the layer information of the layer, and the material included in the layer.