Remote Operator Queueing for Autonomous Vehicle Assistance
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating unpredictable or unfamiliar scenarios, requiring timely and effective assistance from remote operators to ensure safety and efficiency.
Innovation Solution
A remote operation system that matches available remote operators with autonomous vehicles in need of assistance based on criteria such as geographical knowledge, availability, and expertise, using a queue management system to prioritize requests and allocate operators effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple remote operators are available to assist autonomous vehicles, then the quality of assistance can be improved by selecting the most suitable operator, but the system complexity increases due to need for matching and queue management
Solution Approach 1:
The patent introduces a remote operation system as an intermediary between autonomous vehicles and remote operators. This mediator receives requests from vehicles, manages queues, and matches operators to requests based on criteria such as geographical knowledge and availability, thereby improving assistance quality while centralizing the complexity management
Solution Approach 2:
The system performs preliminary actions by pre-screening and matching remote operators to vehicle requests before actual assistance is needed. The queue management system prioritizes and prepares operator assignments in advance based on operator criteria and request characteristics, reducing response time and improving reliability
2Loss of time
If remote operators are assigned quickly to autonomous vehicles, then response time is reduced, but the precision of matching operators to appropriate requests may be compromised
Solution Approach 1:
The system performs preliminary matching and prioritization actions before actual operator assignment. By pre-evaluating operator criteria against request characteristics and establishing queue priorities in advance, the system prepares optimal matches ready for immediate assignment, achieving both speed and precision
Solution Approach 2:
The queue management system incorporates feedback mechanisms to continuously refine operator matching. By monitoring assignment outcomes and operator performance, the system adjusts matching criteria and queue prioritization to improve both response time and matching precision over time
Data Source
AI summary
A remote operations system receives a request for remote operator assistance and adds the request to a queue of additional requests. The queue may be ordered based on time of receipt, priority, criticality, and the like. The remote operations system determines a remote operator of a set of remote operators to provide a response to the request in the queue based at least in part on one or more of a status of the remote operator (e.g., indicative of availability, whether they are in training, etc.), criteria associated with the remote operator (e.g., skills in responding to various requests, preferences for a geographic area, mission types, etc.), and information associated with the request received from the vehicle (e.g., mission type, sensor data, messages, vehicle status, etc.). If the request is not accepted in a threshold period of time, the request may be rerouted to an additional remote operator.