Autonomous Mobile Body Response Prioritization Using Necessity Levels
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Solution Overview
Problem
Existing systems for managing autonomous mobile bodies do not efficiently handle situations where multiple mobile bodies are experiencing difficulties in moving autonomously, leading to inefficiencies in responder dispatch and situation improvement.
Innovation Solution
An information processing method that obtains service information from autonomous mobile bodies, calculates a response necessity level indicating the degree of need for responder intervention, and outputs this information to facilitate efficient responder decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a management system monitors multiple automated driving vehicles periodically, then communication status can be detected, but the system cannot efficiently prioritize which vehicles need responder intervention when multiple vehicles experience communication interruptions simultaneously
Solution Approach 1:
The system introduces a response necessity level parameter that quantifies the urgency of responder intervention. This parameter is calculated based on multiple factors including communication interruption status, vehicle position, and service execution state. By transforming multiple qualitative factors into a single quantitative parameter (response necessity level), the system enables efficient prioritization and sorting of multiple vehicles needing attention, directly resolving the contradiction between detection capability and dispatch efficiency.
2Ease of operation
If the system determines whether to contact support workers based on simple communication conditions, then the decision process is simple, but it cannot handle complex situations where multiple vehicles require different levels of intervention
Solution Approach 1:
The system uses parameter transformation to convert multiple complex conditions (communication status, vehicle position, service state) into a single response necessity level parameter. This allows the system to maintain simple operation (comparing numerical values) while achieving high adaptability (handling diverse situations through flexible parameter calculation). The calculator unit can adjust which factors influence the response necessity level based on different scenarios, providing both simplicity and versatility.
Solution Approach 2:
The response necessity level acts as an intermediary parameter between the complex input conditions and the simple output decision. Instead of directly comparing multiple complex conditions, the system first transforms them into the intermediate response necessity level, which then guides the responder dispatch decision. This intermediary approach simplifies the decision-making process while maintaining the ability to handle complex multi-situation scenarios.
Data Source
AI summary
An information processing method is an information processing method executed by a computer, and includes: obtaining first information related to a service executed by each of at least one mobile body, among a plurality of mobile bodies that move autonomously, when an event to which a responder is to respond by traveling to a position of the at least one mobile body is occurring in the at least one mobile body; calculating, based on the first information obtained, a response necessity level indicating a degree of a necessity to respond to the event, for each of the at least one mobile body; and outputting second information related to the response necessity level calculated.