Driving Function Allocation Between Vehicle and Highway Intelligence
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Solution Overview
Problem
Current Connected Automated Vehicle (CAV) systems face limitations due to high costs and performance constraints related to the number of sensors and computation devices, leading to inefficiencies and safety concerns in automated driving tasks.
Innovation Solution
A function allocation system (FAS) is introduced to optimize the allocation of sensing, decision-making, and control functions between the CAV system and the Connected Automated Highway (CAH) system, utilizing a communication module, data module, and computing module to manage and distribute intelligence levels and tasks efficiently across different scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If CAV systems use numerous sensors and computation devices to improve sensing and decision-making capabilities, then measurement precision and reliability are improved, but device complexity and cost increase
Solution Approach 1:
The patent divides the CAVH system into distinct functional modules: CAV subsystem (vehicle-level sensing and control), CAH subsystem (highway-level infrastructure and communication), and FAS subsystem (function allocation and coordination). This segmentation allows each subsystem to have specialized, optimized components rather than duplicating full sensor suites in every vehicle, reducing overall system complexity while maintaining sensing precision.
Solution Approach 2:
The patent creates a multi-functional architecture where the FAS serves multiple purposes: allocating sensing functions, coordinating decision-making, managing communication protocols, and optimizing resource distribution. The CAH infrastructure provides universal support services to multiple CAVs simultaneously, reducing the need for each individual vehicle to have complete autonomous capabilities.
2Reliability
If CAV systems allocate more functions locally to improve response time and reliability, then speed and reliability are improved, but loss of information and coordination efficiency worsen due to functional overlap
Solution Approach 1:
The FAS implements continuous feedback loops that monitor the operational status, sensing data quality, and decision-making effectiveness of both CAV and CAH subsystems. This feedback mechanism allows the system to dynamically adjust function allocation, ensuring that reliability is maintained while minimizing information redundancy through optimized data sharing protocols.
Solution Approach 2:
The FAS acts as an intermediary layer between the CAV subsystem and CAH subsystem, coordinating information flow and decision-making processes. This mediator prevents direct functional overlap by managing which subsystem performs which functions based on real-time conditions, thereby reducing information redundancy while maintaining reliable automated driving operations.
3Productivity
If CAV systems perform complete automated driving functions independently to improve productivity, then productivity is improved, but device complexity and cost increase
Solution Approach 1:
The patent transitions from a single-vehicle autonomous driving model to a system-level approach by adding the highway infrastructure dimension (CAH) and the function allocation dimension (FAS). This dimensional expansion allows automated driving functions to be distributed across multiple levels (vehicle, infrastructure, coordination layer), improving overall productivity while reducing the complexity burden on individual vehicles.
Data Source
AI summary
Provided herein is technology relating to a function allocation system (FAS) that deploys artificial intelligence models for a connected automated highway (CAH) system and a connected automated vehicle (CAV) system to distribute driving intelligence between the CAV system and the CAH system. The FAS comprises a communication module, a data module, and a computing module. The computing module is configured to analyse scenes using sensing data, determine automated driving function requirements, deploy function allocation methods, and analyse CAH system and CAV system functions. The function allocation methods provide analysis, guidance, and optimization capabilities for sensing, decision-making, and control functions. The FAS allocates automated driving functions to the CAV system and the CAH system based on their respective intelligence levels. The technology aims to enhance automated driving and ensure driving safety by leveraging function allocation models and algorithms for optimal function distribution between vehicles and the infrastructure.