Driving Comfort Assessment Model Using Sensor Data
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Solution Overview
Problem
Traditional methods for assessing the comfort level of driving systems, especially autonomous ones, rely on subjective user assessments, which are inaccurate, costly, and difficult to apply universally, making it hard to identify causes for low comfort levels and suggest improvements.
Innovation Solution
A method and apparatus that generate an assessment model for comfort level by associating user feedback with objective measurements of traveling indicators, allowing for a quantitative evaluation of comfort levels in both autonomous and non-autonomous driving systems, enabling objective and comparable assessments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If subjective assessment by limited test drivers is used, then assessment can be performed, but accuracy and universality of results deteriorate
Solution Approach 1:
The patent replaces the mechanical system of subjective human assessment with an automated assessment system that uses objective vehicle data (acceleration, braking, steering inputs) processed through machine learning models. This substitution eliminates human subjectivity while maintaining assessment capability, directly resolving the contradiction between assessment accuracy and system complexity.
Solution Approach 2:
The patent introduces an intermediary assessment model that acts as a bridge between raw vehicle operating data and comfort level evaluation. This intermediary layer processes objective measurements through trained algorithms to generate comfort scores, replacing direct subjective judgment while preserving the essential assessment function.
2Productivity
If subjective assessment by limited users is used, then assessment can be performed, but time and labor costs increase
Solution Approach 1:
The assessment system performs self-service by automatically collecting vehicle operating data from onboard sensors and processing it through pre-trained models. The system evaluates comfort levels without requiring human assessors to manually observe or record data, enabling continuous automated assessment that dramatically improves productivity while reducing time investment.
Solution Approach 2:
The patent applies preliminary action by pre-training assessment models using extensive datasets before deployment. Once trained, these models can rapidly evaluate comfort levels for numerous driving scenarios without requiring repeated human assessment efforts, thereby improving long-term assessment efficiency and reducing cumulative time costs.
3Loss of information
If traditional subjective assessment is used, then comfort level can be evaluated, but ability to identify causes and suggest improvements deteriorates
Solution Approach 1:
The patent segments the comfort assessment into multiple independent dimensions by evaluating different vehicle operating parameters (acceleration comfort, braking comfort, steering comfort) separately. This segmentation allows identification of specific cause areas while maintaining manageable system complexity through modular assessment components.
Solution Approach 2:
The patent adds another dimension to traditional assessment by incorporating detailed vehicle operating data (acceleration rates, braking forces, steering angles) alongside comfort scores. This multi-dimensional approach enables cause identification through pattern analysis across multiple parameters without proportionally increasing system complexity.
Data Source
AI summary
Illustrative embodiments of the disclosure provide a method and apparatus for assessing a comfort level of a driving system. A method for generating an assessment model for comfort level in a driving system comprises acquiring a first assessment from a user on a comfort level of at least one traveling operation of the driving system, and acquiring a measurement of a traveling indicator of the driving system when performing the at least one traveling operation. The method further comprises generating the assessment model for the comfort level in the driving system based on the first assessment, the measurement of the traveling indicator, and a second assessment from the user on an overall comfort level of the driving system.