Safety Operation Index Calculation for Defensive Driving Classification
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Solution Overview
Problem
Conventional methods for calculating a safety operation index in usage-based and behavior-based insurance struggle to accurately reflect a driver's driving intentions, leading to potential misclassification of safe driving habits as dangerous, especially in unavoidable situations.
Innovation Solution
A safety operation index calculator that extracts and classifies driving data using processors and memory to differentiate between defensive and dangerous driving by grouping data points based on coordinate values and adjusting thresholds for more accurate scoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional numerical driving data is used to calculate the safety operation index, then the calculation process is simple, but the accuracy and reliability of the safety operation index deteriorates because driving intentions cannot be reflected
Solution Approach 1:
The patent segments driving data into multiple dimensions including spatial coordinates, temporal information, and behavioral patterns. By dividing the analysis into distinct components (location data, time data, driving maneuvers), the system achieves more accurate assessment of driving intentions while maintaining a structured calculation process that manages complexity through organized data categorization.
Solution Approach 2:
The patent transitions from conventional one-dimensional numerical driving data to multi-dimensional analysis by incorporating spatial coordinates (latitude, longitude, altitude), temporal dimensions, and contextual information. This dimensional expansion enables the system to capture driving intentions and patterns that cannot be represented by simple numerical metrics alone.
2Reliability
If only numerical driving data is used for safety operation index calculation, then the data processing is straightforward, but the reliability deteriorates because defensive driving maneuvers are misclassified as dangerous driving
Solution Approach 1:
The patent applies preliminary classification rules that identify defensive driving scenarios before final safety assessment. By pre-defining contexts such as emergency evasion maneuvers, restricted zone entries, and unavoidable dangerous driving situations, the system prevents misclassification of defensive driving as dangerous, thereby improving reliability while managing complexity through predetermined classification frameworks.
Solution Approach 2:
The system incorporates feedback mechanisms that compare calculated safety operation indexes with actual driving outcomes and contextual information. This feedback loop allows the system to learn from misclassifications and adjust its assessment criteria, improving reliability over time while using the feedback information to refine the analysis process rather than adding unnecessary complexity.
3Measurement precision
If conventional driving data classification is used, then the processing speed is fast, but the accuracy deteriorates because it cannot differentiate between intentional dangerous driving and unavoidable dangerous situations
Solution Approach 1:
The patent segments driving data into hierarchical categories, processing high-level patterns first (such as overall driving route and context) before analyzing detailed maneuvers. This segmented approach enables accurate differentiation between intentional dangerous driving and unavoidable situations by examining multiple levels of data organization, achieving precision without requiring complete analysis of every single data point simultaneously.
Solution Approach 2:
The system performs preliminary filtering and contextual assessment before detailed classification of driving maneuvers. By pre-identifying defensive driving contexts and unavoidable dangerous situations based on spatial, temporal, and environmental data, the system reduces the computational burden on detailed maneuver analysis, thereby achieving high classification precision while minimizing processing time losses.
Data Source
AI summary
A safety operation index calculation device and a method are disclosed. An apparatus may in close one or more processors and memory. The memory may store instructions that, when executed by the one or more processors, cause the apparatus to extract, from driving data collected for drivers whose safety operation indexes are higher than a threshold value, driving data that may be determined as dangerous driving; classify, based on predetermined criteria, the extracted driving data into a plurality of groups; designate a group, of the plurality of groups, having a size larger than remaining groups of the plurality of groups, as a defensive driving group; and update the safety operation indexes for the drivers based on at least a portion, of the extracted driving data, corresponding to the remaining group.