Remote Assistance Evaluation Using Timing and Trajectory Gaps
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Solution Overview
Problem
Current remote assistance technologies for automated driving of mobile objects face reliability issues in evaluating operator performance, as short response times and processing times do not guarantee adequate performance, and reliance on oncoming vehicle and occupant states rather than direct mobile object states complicates evaluation accuracy.
Innovation Solution
A remote assistance system that acquires assistance requests from mobile objects, generates instruction information based on operator inputs, transmits it, collects determination information, and outputs evaluation information based on time gaps between instruction and determination timings, as well as trajectory gaps between planned and actual trajectories, to provide a reliable performance assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If operator performance is evaluated based on response time and processing time overrun, then evaluation speed is improved, but evaluation reliability deteriorates because short response times do not guarantee adequate performance
Solution Approach 1:
The evaluation process is segmented into multiple independent metrics: response time, processing time overrun, and determination accuracy. Each metric is calculated separately based on different data (instruction timing, determination timing, and determination information), allowing comprehensive assessment without relying solely on time-based measures that may be misleading.
Solution Approach 2:
The system implements feedback by collecting determination information from the mobile object and comparing it with instruction information. This feedback loop enables the evaluation of determination accuracy, providing reliable performance assessment that goes beyond simple time measurements and accounts for the actual quality of operator decisions.
2Adaptability or versatility
If evaluation is based on oncoming vehicle state and occupant state, then assessment scope is expanded, but measurement precision deteriorates due to indirect representation of mobile object state
Solution Approach 1:
The system uses determination information as an intermediary that directly represents the mobile object's state and response. Instead of relying on indirect indicators like oncoming vehicle state, the evaluation is based on the mobile object's own determination data, which serves as a direct mediator between the operator's instructions and the actual system response, thereby improving measurement precision.
Data Source
AI summary
By a remote assistance system, a remote assistance method, or a non-transitory tangible storage medium storing a remote assistance program, an assistance request is acquired from a mobile object, instruction information is generated according to an instruction from an operator, the instruction information is transmitted to the mobile object, and evaluation information that has evaluated the operator is output.