Centralized Scenario Control for Shared Autonomous Vehicle Fleets

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Solution Overview

Problem

Autonomous vehicles face challenges in identifying and managing distinct vehicle operational scenarios due to limited resource availability for scenario identification and policy generation, necessitating a centralized system for shared scenario-specific operational control management.

Innovation Solution

A centralized shared scenario-specific operational control management system that receives and validates input data from autonomous vehicles, identifies current operational scenarios, generates and transmits corresponding control management output data, and distributes policy data to optimize vehicle operations across the transportation network.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If autonomous vehicles independently identify and manage distinct vehicle operational scenarios using local resources, then each vehicle can respond autonomously to scenarios, but the system experiences resource limitations and inefficiency in scenario identification and policy generation

Engineering Contradiction:

Improvescenario identification efficiencyVSAvoidcomputational resource consumption

Core Design Contradiction:

ProductivityVSUse of energy by moving object

Solution Approach 1:

A centralized server acts as an intermediary between autonomous vehicles and the scenario management system. The server receives operational data from vehicles, performs comprehensive scenario identification and policy generation centrally, then distributes policies back to vehicles. This mediator approach allows complex computational tasks to be performed in a centralized location with greater resources, while vehicles maintain autonomous operation with reduced local computational burden.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system transitions from distributed scenario management across multiple vehicles to centralized management in a separate dimensional space (the server). By moving the computational workload to a different spatial dimension (centralized server infrastructure), the system can handle scenario identification and policy generation more efficiently without overloading individual vehicle resources.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

2Adaptability or versatility

If each autonomous vehicle maintains its own scenario-specific policies and operational data, then vehicles can operate independently, but the system lacks centralized coordination and shared learning across the vehicle fleet

Engineering Contradiction:

Improvescenario-specific policy optimizationVSAvoiddistributed system complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system merges scenario identification, policy generation, and validation functions into a centralized server that serves the entire vehicle fleet. Instead of each vehicle maintaining separate policy systems, the centralized server consolidates these functions, enabling shared learning across vehicles while reducing individual vehicle complexity. The server aggregates operational data from multiple vehicles to generate and refine policies that benefit the entire fleet.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The centralized server performs multiple functions: receiving operational data from vehicles, identifying scenarios, generating policies, validating policies, and distributing them back to vehicles. This universal system handles the complete operational management lifecycle centrally, allowing each vehicle to focus on execution while the server manages the complexity of scenario-specific policy optimization for the entire fleet.

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Reliability

If autonomous vehicles process and validate scenario-specific operational data locally, then real-time response is possible, but computational resources are insufficient for comprehensive scenario analysis

Engineering Contradiction:

Improveoperational control accuracyVSAvoidlocal computational capacity

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The system extracts the computationally intensive functions of scenario identification, policy generation, and validation from individual vehicles and relocates them to a centralized server. Vehicles only need to perform lightweight data collection and policy execution, while the server handles the heavy computational lifting required for reliable and accurate operational control across diverse scenarios.

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentEP3759563B1Centralized shared autonomous vehicle operational management

Publication Date: 2023.11.22 NISSAN NORTH AMERICA INC

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AI summary

Centralized shared scenario- specific operational control management includes receiving, at a centralized shared scenario-specific operational control management device, shared scenario-specific operational control management input data, from an autonomous vehicle, validating the shared scenario- specific operational control management input data, identifying a current distinct vehicle operational scenario based on the shared scenario-specific operational control management input data, generating shared scenario-specific operational control management output data based on the current distinct vehicle operational scenario, and transmitting the shared scenario- specific operational control management output data.