Driver Estimation Using Routine Pre-Driving Operation Data
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Solution Overview
Problem
Existing driver identification systems require operations on specific biometric devices, leading to delayed and inaccurate identification.
Innovation Solution
A driver estimation system that acquires and analyzes operation data from routine pre-driving actions using machine learning to estimate the driver with high accuracy in a short time, incorporating a learned model and operation proposal mechanism.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If biometric information acquisition means is used for driver identification, then identification accuracy is improved, but identification time is delayed because the driver must operate a specific operation unit
Solution Approach 1:
The system performs driver identification by analyzing operation data from routine pre-driving operations (such as door locking, seat adjustment, mirror adjustment) that the driver performs before starting the vehicle. This preliminary action of collecting and analyzing operation data during natural pre-driving routines enables identification without requiring the driver to specifically interact with biometric acquisition devices, thereby reducing identification time while maintaining accuracy
Solution Approach 2:
The driver performs routine operations (door locking, seat adjustment, mirror adjustment) for their own convenience and comfort, and the system simultaneously uses these self-service operations for driver identification. The driver's natural behaviors serve dual purposes: their own operational needs and the system's identification function, eliminating the need for separate biometric authentication actions
2Measurement precision
If operation data from multiple preset operation items is collected and analyzed, then driver estimation accuracy is improved, but device complexity increases
Solution Approach 1:
The system uses a single data acquisition unit that collects operation data from multiple operation units (door locking unit, seat adjustment unit, mirror adjustment unit, etc.). These operation units serve their primary functions for vehicle operation while simultaneously providing data for driver identification. This multi-functionality approach improves estimation accuracy through multiple data sources without significantly increasing overall system complexity
Solution Approach 2:
The data acquisition unit acts as an intermediary that collects operation data from various operation units and transfers it to the driver estimation unit. This intermediary component simplifies the system architecture by centralizing data collection and processing, avoiding the need for complex direct connections between multiple operation units and the estimation algorithm
Data Source
AI summary
A driver estimation device includes a data acquisition unit. The data acquisition unit acquires operation data related to an operation performed by a driver before driving a vehicle for a plurality of preset operation items. The driver estimation device also includes a driver estimation unit. The driver estimation unit estimates the driver based on the operation data acquired by the data acquisition unit.