Automatic Driving Evaluation via Passenger Facial Expression Analysis
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Solution Overview
Problem
In automatic driving vehicles, it is challenging to evaluate ride comfort without passenger input, as traditional methods rely on human feedback, which can be burdensome and inaccurate.
Innovation Solution
A driving evaluation apparatus that uses facial expression and behavior analysis, via cameras and microphones, to determine passenger feelings during vehicle operations, estimating ride comfort and evaluating the driving experience automatically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional passenger feedback methods are used to evaluate ride comfort, then evaluation accuracy can be improved, but passenger burden increases and automation level decreases
Solution Approach 1:
The system uses facial expression recognition technology to automatically detect and analyze passenger emotions without requiring any active participation from the passenger. The camera captures facial images, the processor analyzes expressions to determine comfort levels, and the evaluation is completed entirely autonomously, making the passenger unaware of the evaluation process while maintaining high measurement precision
Solution Approach 2:
The patent replaces traditional mechanical feedback methods (such as questionnaires, buttons, or verbal feedback requiring passenger action) with an optical detection system using cameras and image processing algorithms to automatically capture and analyze passenger facial expressions, thereby eliminating the need for manual passenger involvement while preserving evaluation accuracy
2Productivity
If automatic driving control performance is continuously updated based on evaluations, then ride comfort improvement can be accelerated, but system complexity increases
Solution Approach 1:
The system establishes a closed-loop feedback mechanism where facial expression data from passengers is continuously collected, processed to generate ride comfort evaluations, and fed back to update the automatic driving control algorithms. This automated feedback loop enables continuous improvement of control performance without manual intervention, accelerating productivity while the modular architecture manages system complexity
Solution Approach 2:
The system pre-processes and stores facial expression data and evaluation results in structured formats, preparing evaluation datasets in advance for efficient algorithm training and updates. This preliminary organization of data enables faster subsequent updates of the automatic driving control system without creating excessive complexity during the update process itself
Data Source
AI summary
A driving evaluation apparatus includes a processor configured to determine, based on information about facial expressions or behaviors of one or more passengers riding in a vehicle that is under automatic driving control, whether or not the passenger has displayed a facial expression or behavior indicating a specific feeling, and estimate ride comfort of the vehicle felt by the passenger in accordance with a determination result; and evaluate the driving of the vehicle that is under the automatic driving control, based on an estimation result of the ride comfort.