Remote Autonomous Vehicle Assistance With Operator Attribute Matching
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Solution Overview
Problem
Autonomous vehicles face challenges in efficiently providing remote assistance due to the variability in operator characteristics and the need for precise matching of operator attributes with request parameters, leading to suboptimal resource utilization and service disruptions.
Innovation Solution
A computer-implemented method that tracks assisted autonomy tasks, generates operator attributes, and selects operators based on request parameters to facilitate remote autonomous vehicle assistance, reducing computational resources and bandwidth by matching operator expertise with task requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If operators with varying characteristics are assigned to handle remote assistance requests, then the system can accommodate diverse task requirements, but the effectiveness of remote assistance decreases due to mismatched operator-task pairing
Solution Approach 1:
The system performs preliminary actions by tracking assisted autonomy tasks and generating operator attributes in advance, before actual assistance requests are handled. This allows the computing system to pre-establish operator profiles with relevant characteristics, enabling efficient matching when requests occur and ensuring both adaptability and reliability.
Solution Approach 2:
The system implements feedback mechanisms by continuously tracking operator performance on assisted autonomy tasks and updating operator attributes accordingly. This feedback loop ensures that operator profiles remain current and accurate, improving the effectiveness of future task assignments while maintaining system reliability.
2Measurement precision
If comprehensive tracking of assisted autonomy tasks is performed to generate operator attributes, then operator selection accuracy improves, but computational resources and bandwidth consumption increase
Solution Approach 1:
The system extracts only the essential and relevant attributes from comprehensive task tracking data, rather than processing all available information. By identifying and extracting key operator characteristics needed for effective matching, the system achieves high measurement precision while reducing computational resource consumption and bandwidth usage.
3Adaptability or versatility
If multiple operators are maintained in the remote assistance system to handle diverse requests, then service coverage improves, but resource utilization becomes suboptimal due to difficulty in precise matching
Solution Approach 1:
The system performs preliminary matching computations by generating and storing operator attributes in advance, so that when assistance requests occur, the system can quickly identify the most suitable operator from the pool. This preliminary preparation enables maintaining multiple operators for diverse service coverage while achieving optimal resource utilization through efficient matching.
Data Source
AI summary
Systems and methods for controlling autonomous vehicles are provided. Assisted autonomy tasks facilitated by operators for a plurality of autonomous vehicles can be tracked in order to generate operator attributes for each of a plurality of operators. The attributes for an operator can be based on tracking one or more respective assisted autonomy tasks facilitated by the operator. The operator attributes can be used to facilitate enhanced remote operations for autonomous vehicles. For example, request parameters can be obtained in response to a request for remote assistance associated with an autonomous vehicle. An operator can be selected to assist with autonomy tasks for the autonomous vehicle based at least in part on the operator attributes for the operator and the request parameters associated with the request. Remote assistance for the first autonomous vehicle can be initiated, facilitated by the first operator in response to the request for remote assistance.