Driving Mode Detection via Sensor Fusion and Threshold Adjustment
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Solution Overview
Problem
Existing systems for determining whether a user is driving a vehicle to limit mobile device access often result in false positives and false negatives, as they rely solely on Bluetooth detection or motion sensors, leading to inaccurate mode switching.
Innovation Solution
The system employs sensor fusion by correlating Bluetooth device proximity with motion attributes to improve the determination of driving mode, adjusting thresholds based on the confidence level of these correlations to reduce false positives and negatives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Bluetooth detection or motion sensors are used alone to determine driving mode, then the system complexity is low, but the measurement precision and reliability are poor due to false positives and false negatives
Solution Approach 1:
The patent combines multiple detection methods (Bluetooth proximity detection, motion sensor detection, location detection) into a unified driving mode determination system. By merging these different sensing approaches, the system achieves higher measurement precision through cross-validation, where multiple indicators must align to confirm driving mode, thereby reducing false positives and false negatives that occur with single-sensor approaches.
Solution Approach 2:
The system dynamically adjusts detection thresholds and confidence levels based on the combination of sensor inputs. When multiple sensors indicate driving conditions, the system increases confidence in the determination and may lower additional thresholds for mode switching. This parameter adjustment allows the system to maintain high accuracy while adapting to different detection scenarios.
2Reliability
If multiple sensors and detection methods are combined to improve accuracy, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent segments the driving mode determination process into distinct detection modules (Bluetooth detection module, motion sensor module, location detection module) that operate independently but contribute to the overall determination. Each module processes specific sensor data and provides confidence scores, allowing the system to maintain reliability through modular design while managing complexity through clear separation of detection functions.
Solution Approach 2:
The system introduces a confidence level calculation mechanism that acts as an intermediary between multiple sensors and the final driving mode determination. This mediator aggregates inputs from various sensors, weighs their reliability, and produces a unified confidence score that drives mode switching decisions, thereby simplifying the integration of multiple complex sensors into a coherent decision-making process.
Data Source
AI summary
A system and method of determining whether a device user is driving provide an improved ability to switch between a normal mode and a driving mode with fewer false positives and false negatives. Bluetooth connectivity and motion sensor readings are fused to make the drive mode determination and to set the timing of nay switch. In an embodiment, Bluetooth devices correlated with driving are used to modify the confidence level and the decision threshold associated with sensor input. When a node having a driving correlation higher than a particular threshold is connected to a device, a lower threshold is applied to the motion sensor input for entering drive mode and a higher threshold is applied for exiting drive mode. Similarly, when a user device is not connected to any highly correlated node, default thresholds may be used for entering and exiting the drive mode.