Driver Steering Evaluation Using Load-Event Travel Data Exclusion
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Solution Overview
Problem
Existing driving ability determination systems require applying a load to the driver to evaluate safe driving ability, which hinders normal driving operations.
Innovation Solution
A driving ability determination system that acquires time-series travel data, calculates evaluation values for steering characteristics, and determines the occurrence of predetermined events that increase cognitive load, allowing for the evaluation of driving ability without hindering driving.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a load is applied to the driver to evaluate safe driving ability, then the evaluation accuracy is improved, but the ease of operation deteriorates because it hinders driving
Solution Approach 1:
The patent extracts and excludes travel data obtained during periods when a load is applied to the driver (such as during alarm activation or emergency events) from the evaluation calculation. This allows the system to maintain high measurement precision by using only relevant data while avoiding the hindrance caused by load application, thereby resolving the contradiction between evaluation accuracy and ease of driving.
Solution Approach 2:
The system preliminarily identifies and flags travel data obtained during load periods before performing the evaluation calculation. By pre-marking these data points for exclusion or reduced weighting, the system ensures that only appropriate data contribute to the evaluation, maintaining accuracy without requiring actual load application during evaluation, thus preserving ease of driving.
2Quantity of substance
If travel data during load periods is included in evaluation, then the quantity of evaluation data is improved, but the reliability deteriorates due to distorted evaluation results
Solution Approach 1:
The patent applies different quality treatment to different portions of travel data based on the driving condition. Travel data obtained during load periods is either excluded entirely or assigned reduced weight, while data from normal driving conditions receives full weight. This local differentiation ensures that the quantity of usable evaluation data is maximized while maintaining high reliability by preventing distortion from load-period data.
Solution Approach 2:
The system dynamically changes the weight parameter assigned to travel data based on the driving condition. During normal driving, data receives standard weighting; during load periods, the weight parameter is reduced or set to zero. This parameter adjustment allows the system to utilize maximum data quantity while ensuring reliability through conditional weighting strategies.
Data Source
AI summary
A driving ability determination system includes a processor and memory coupled to the processor. The processor is configured to perform: acquiring series travel data of a vehicle; calculating an evaluation value indicating a steering characteristic of a driver of the vehicle based on the travel data; and determining whether a predetermined event in which a predetermined load acts on the driver has occurred based on the travel data. The calculating includes specifying, as specific travel data, the travel data acquired after a time point at which it is determined that the predetermined event has occurred calculating a first evaluation value based on the travel data by excluding the specific travel data from first travel data or based on the travel data corrected, and calculating a second evaluation value when the predetermined load acts on the driver based on the first evaluation value and second travel data.