Vehicle OBU-Cloud Coordination for Long-Tail Autonomous Driving
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Solution Overview
Problem
Existing vehicle on-board units (OBU) for connected and automated vehicles (CAV) are limited in their ability to provide comprehensive control and management for CAVs, as they primarily focus on communication with other vehicles or infrastructure, lacking the capability to manage a connected automated vehicle highway system.
Innovation Solution
A vehicle control on-board unit (OBU) configured to exchange data with a vehicle infrastructure coordination transportation system, providing detailed and time-sensitive control instructions for automated vehicle driving, including vehicle following, lane changing, and route guidance, while also integrating with a connected automated vehicle highway system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing OBU systems communicate with other vehicles or infrastructure, then basic connected vehicle functionality is achieved, but comprehensive control and management capability for CAVs is insufficient
Solution Approach 1:
The OBU is designed as a multi-functional device that performs not only communication functions but also data processing, decision-making, and vehicle control functions. The system integrates multiple capabilities including environmental sensing, trajectory prediction, decision-making algorithms, and direct control of vehicle subsystems, allowing a single device to fulfill diverse roles in the CAV ecosystem.
Solution Approach 2:
The patent combines previously separate functions (communication, sensing, processing, control) into an integrated OBU system. The controller is merged with communication modules, sensing modules, and execution interfaces, creating a unified control architecture that reduces system complexity while enhancing comprehensive control capability.
2Reliability
If detailed and time-sensitive control instructions are provided to individual vehicles, then automation level and safety are improved, but data processing requirements and system complexity increase
Solution Approach 1:
The system performs preliminary data processing and decision-making in advance by collecting and analyzing environmental data, predicting trajectories of surrounding objects, and pre-computing control instructions before they are needed. This preparation work reduces the real-time processing burden and enables faster, safer response times.
Solution Approach 2:
The OBU implements continuous feedback loops where control instructions are sent to vehicle subsystems, execution results are monitored, and subsequent adjustments are made based on actual vehicle response and changing environmental conditions. This closed-loop control enhances safety while distributing processing requirements across time.
3Extent of automation
If comprehensive sensing and data collection is performed, then automation level is improved, but energy consumption and computational load increase
Solution Approach 1:
The system implements selective sensing and data collection, gathering comprehensive environmental information only when necessary for specific driving scenarios or decision-making requirements. Rather than continuously maximizing data collection, the system adjusts sensing intensity and scope based on operational context, reducing energy consumption while maintaining adequate automation capability.
Data Source
AI summary
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.