Automated Driving Map Analysis Using Operator Sound Evaluation
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Solution Overview
Problem
Existing automated driving technologies rely solely on acceleration data for map generation, which is insufficient for comprehensive evaluation of automated driving vehicles, leading to inadequate identification of issues during automated driving.
Innovation Solution
A processing method that extracts automated driving data and sound evaluation data from dynamic data associated with traveling points on a digital map, generating factor analysis data to analyze and identify issues in the automated driving state by correlating the two types of data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If only acceleration data is used for map generation, then the data processing is simple, but the evaluation comprehensiveness is insufficient
Solution Approach 1:
The patent combines multiple data sources (acceleration data from sensors and sound evaluation data from operators) into a unified evaluation system. The map generation process integrates both automated driving data and human operator assessments, merging objective sensor measurements with subjective human evaluations to achieve comprehensive evaluation while maintaining manageable processing complexity through structured data integration.
2Reliability
If multiple data sources are integrated for comprehensive evaluation, then the evaluation reliability improves, but the data processing complexity increases
Solution Approach 1:
The patent segments the evaluation process into distinct components: automated driving data extraction from sensors, sound evaluation data collection from operators, and integrated analysis. By dividing the comprehensive evaluation into modular segments that can be processed independently and then combined, the system achieves thorough evaluation coverage while keeping processing complexity manageable through structured segmentation of data sources and analysis steps.
3Measurement precision
If sound evaluation data from operators is collected, then the problem identification accuracy improves, but the data collection complexity increases
Solution Approach 1:
The patent implements a self-service approach where operators naturally provide sound evaluation data through their normal driving interactions and feedback mechanisms. The system captures operator evaluations during regular operation without requiring separate dedicated data collection sessions or complex intervention protocols. This allows accurate problem identification through genuine operator insights while minimizing the complexity of data collection infrastructure.
Data Source
AI summary
A processing method, which is executed by a processor to execute a process associated with automated driving of a moving body, includes: extracting, from dynamic data embedded in association with traveling points of the moving body on a digital map, automated driving data representing an automated driving state of the moving body at an analysis traveling point and sound evaluation data representing evaluation by a sound from an operator regarding the automated driving state at the analysis traveling point; and generating, based on the automated driving data, factor analysis data correlated with the sound evaluation data as a result of analyzing a factor of the automated driving state at the analysis traveling point. The generating of the factor analysis data includes: selecting the automated driving data correlated with the sound evaluation data; and generating the factor analysis data based on the selected automated driving data.