Autonomous Vehicle Rescue Priority System
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Solution Overview
Problem
In scenarios where multiple autonomous vehicles experience operational suspensions, existing systems lack an effective method to determine the appropriate order of priority for rescue team responses, potentially leading to inefficient or unsafe recovery operations.
Innovation Solution
An information processing apparatus and method that acquire positional, vehicle, internal, and external image data from affected vehicles to determine a priority order for rescue teams based on factors like passenger count, road width, lane type, failure type, and repair time, ensuring timely and effective response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple autonomous vehicles experience operational suspensions simultaneously, then the rescue team must respond to multiple vehicles, but without a priority determination system, the response efficiency and resource allocation deteriorate
Solution Approach 1:
The system performs preliminary actions by automatically acquiring positional information, vehicle information, images, and determining priority orders immediately when suspensions occur, before the rescue team needs to make decisions. This preliminary data collection and analysis eliminates the time the rescue team would otherwise spend gathering information and determining response priorities manually.
Solution Approach 2:
The information processing apparatus acts as an intermediary between the multiple suspended autonomous vehicles and the rescue team. It receives data from various vehicles, processes it according to predetermined criteria, and provides a structured priority order to the rescue team, thereby mediating the complex situation of multiple simultaneous suspensions into a manageable response sequence.
2Productivity
If the rescue team responds to all suspended vehicles equally, then resource allocation becomes inefficient, but determining priority requires complex analysis of multiple factors
Solution Approach 1:
The system changes parameters by evaluating multiple factors (positional information, vehicle information, images) and converting them into a single priority order parameter. By transforming complex multi-dimensional data into a one-dimensional priority sequence, the system enables efficient resource allocation without requiring the rescue team to manually analyze complex criteria for each vehicle.
Solution Approach 2:
The priority determination process is segmented into distinct evaluation components: positional information assessment, vehicle information analysis, image evaluation, and final priority ordering. This segmentation allows the system to handle complex multi-factor analysis in a structured, modular manner that improves computational efficiency and makes the determination process more manageable.
3Measurement precision
If the system collects comprehensive data (positional information, vehicle information, images) for priority determination, then the accuracy of priority ordering improves, but the data processing time and computational load increase
Solution Approach 1:
The system applies partial action by acquiring and processing only the essential data elements needed for priority determination from each suspended vehicle. Rather than collecting all possible vehicle data, it focuses on specific positional information, key vehicle information, and relevant images, achieving sufficient accuracy for rescue prioritization without the time cost of comprehensive data collection.
Data Source
AI summary
An information processing apparatus includes a controller configured to acquire, when a suspension of operation occurs in an autonomous vehicle, positional information, vehicle information, a vehicle internal image, and a vehicle external image of the autonomous vehicle, and determine, in a case in which a suspension of operation occurs in a plurality of autonomous vehicles, an order of priority for a rescue team to go to the plurality of vehicles, based on the positional information, the vehicle information, the vehicle internal image, and the vehicle external image.