CAVH LLC

The present technology relates to systems and methods that allocate, arrange, and distribute certain types of functions and intelligence for autonomous driving systems (ADS) to facilitate vehicle operations and controls; to improve the safety of an autonomous vehicle (AV); and to ensure the efficiency, intelligence, reliability, and resilience of ADS. The present technology also provides methods to define ADS system intelligence and its levels, which are based on two dimensions: the vehicle intelligence and the cloud intelligence. The cloud intelligence supports and complements the vehicle intelligence when a vehicle is impaired or handicapped for certain functions (sensing, prediction, decision, and/or control) during operations in abnormal conditions. Distribution of driving intelligence between the AV and the cloud facilitates safe operations of the AV for long-tail corner cases.

An Enterprise-Oriented Cloud Control System is disclosed for providing time-sensitive, vehicle-specific guidance and control instructions to autonomous vehicles (AVs) in long-tail corner cases. The system operates through an enterprise-oriented cloud intelligent unit (E-CIU) that integrates service, management, communication, sensing, prediction, planning, control, and support subsystems. Automated driving scenarios are classified by a traffic fence based on demand and supply characteristics. The E-CIU receives multi-source event and non-event data from vehicles, roads, clouds, and centers, offers various “as-a-service” functions, and employs event models to convert macroscopic event data into microscopic operational data. These models generate cooperative sensing, prediction, planning, and control solutions and produce customized, real-time instructions for longitudinal/lateral motion and operational decisions. An onboard unit exchanges information with the E-CIU and executes cloud-generated commands, providing effective management of AVs in rare and complex scenarios.

This technology provides several methods for operating an Autonomous Vehicle Intelligent Control System that integrates a sensing module for collecting 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/Traffic Control Units (TCC/TCU). The system receives targeted guidance instructions and information, such as vehicle maneuvering, safety maintenance, traffic control, and special conditions, to enhance driving tasks. The system also incorporates weather or special information in vehicle operation or control. The OBU receives vehicle-specific targeted weather information and/or special information from the TCC/TCU. The special information comprises activity, accidents, and hazards/obstacles information. The vehicle control module enhances driving safety by integrating vehicle-specific weather, pavement condition, activity, accidents, and hazards/obstacles information.

Provided herein is technology relating to a distributed driving system with the support of an intelligent roadside toolbox (IRT) to address long-tail cases. The IRT comprises a cloud and provides fused data from multiple sensors and data sources. A connected automated vehicle (CAV) uses the fused data to supplement its sensing data and maintain its automation level when its components have failure. Moreover, the IRT predicts the movement and behavior of surrounding objects, pedestrians, and bicycles; and provides such vulnerable road user information to the CAV to help the CAV maintain its safe driving and desired autonomous driving level in complex urban environments. For emergency situations or function failure, the IRT provides emergency services and failure safety measures for the CAV.

This technology relates to autonomous vehicle (AV) control systems tailored for critical points with information support from a cloud platform or other vehicles. A first system integrates an onboard unit (OBU) and communication modules to interact with a cloud platform, delivering time-sensitive instructions to vehicles at critical points. The OBUs execute these instructions for driving tasks. A second system enables an AV to operate through critical points with information from other vehicles, leveraging integrated information services for enhanced functionality and safety. A third system combines an OBU with a cloud platform, leveraging cloud services for enhanced functionality, such as computing. The technology adapts to diverse critical point scenarios, employing proactive incident prediction and rapid detection methods for optimized performance.

This technology provides an Autonomous Vehicle (AV) Control System that includes a sensing module for gathering driving environment data and an onboard unit (OBU) for vehicle control. The OBU fuses data from the vehicle and data from a Traffic Control Center/Traffic Control Unit (TCC/TCU), a Roadside Unit (RSU), or another vehicle. The OBU comprises a vehicle control module and communication modules for information exchange with TCC/TCU, RSU, or another vehicle. The AV control system receives targeted guidance instructions and information, such as vehicle maneuvering, safety maintenance, traffic control, and special conditions, to enhance driving tasks. The AV control system collaborates with TCC/TCU, RSU, or another AV, which provides 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 autonomous vehicles (AVs).

Provided herein is technology relating to automated driving, particularly, but not exclusively, to an enterprise active safety system (EASS) that is configured to improve safety or minimize losses from safety events. More specifically, the EASS is configured to provide system-based safety functions by integrating one or more of the vehicle components, road components, cloud components, pedestrian components, and map components. These safety functions include one or more of crash detection, crash prediction, crash warning, crash avoidance, crash impact reduction, and emergency response functions.

The technology provides designs and methods for the transit management system, which facilitates transit vehicle operations and control for connected automated transit vehicles (CATVs) systems. The transit management system provides transit vehicles with customized/non-customized information and time-sensitive control instructions for transit vehicle to fulfill the driving tasks such as vehicle routing, lane changing, turning. The transit management system also realizes transit vehicle lane design, transportation operations and management services for transit vehicle. The transit management system consists of one of more of the following physical subsystems: (1) Roadside Unit (RSU) network, (2) Traffic Control Unit (TCU) and Traffic Control Center (TCC) network, (3) Vehicle Onboard Unit (OBU), (4) Traffic Operations Centers (TOCs), (5) Cloud platform. The transit management system realizes one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. The transit management system is supported by road infrastructure, real-time wired and/or wireless communication, the power supply networks, and cyber safety and security services.

This invention provides an Autonomous Vehicle (AV) Control System comprising a sensing module for gathering driving environment data and an onboard unit (OBU) for vehicle control. The OBU comprises a vehicle control module and communication modules for information exchange with a Traffic Control Center/Traffic Control Unit (TCC/TCU) or Roadside Units (RSUs). The AV Control System receives targeted guidance instructions and information, such as vehicle maneuvering, safety maintenance, traffic control, and special conditions, to enhance driving tasks. The AV Control System collaborates with a TCC/TCU or 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 autonomous vehicles (AVs).

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.