Seat Occupancy Detection Using Sequential Probability Checks
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Solution Overview
Problem
Conventional methods for recognizing seat occupancy in motor vehicles require significant computing effort and costly sensor systems, making them inefficient and expensive.
Innovation Solution
A method that efficiently checks seat occupancy by prioritizing seats based on probability and importance, using a sequential checking sequence and a combination of sensors like infrared cameras, weight sensors, and depth measurement tools, to differentiate between occupants and objects, and adapt the checking sequence dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional sensor systems and methods are used to recognize seat occupancy, then measurement precision and reliability are improved, but computing effort and system cost increase significantly
Solution Approach 1:
The patent divides the seat into multiple evaluation zones (e.g., first, second, and third evaluation zones) with different weightings. Each zone contributes differently to the overall occupancy determination, allowing the system to achieve accurate detection without requiring complex sensor arrays throughout the entire seat structure.
Solution Approach 2:
The patent uses a single weight sensor to perform multiple functions: detecting occupancy presence, determining occupancy type (adult/child), and triggering appropriate safety systems. This multi-functional approach eliminates the need for separate sensors for each detection task, reducing system complexity while maintaining measurement precision.
2Measurement precision
If comprehensive seat occupancy analysis is performed for all seats simultaneously, then measurement precision is improved, but computing time and processing speed worsen
Solution Approach 1:
The patent pre-calculates and stores weighting factors for different evaluation zones and occupancy scenarios before actual occupancy detection is needed. These pre-computed weights are then applied during real-time operation, eliminating the need for complex calculations during critical detection moments and significantly reducing computing time while maintaining accuracy.
Solution Approach 2:
The patent implements a hierarchical evaluation process where seats are checked in sequence rather than all simultaneously. The system performs partial evaluations first (checking if any occupancy is present) before proceeding to more detailed assessments, allowing quick decisions when occupancy is clearly present or absent without requiring full computational analysis of all parameters.
3Device complexity
If simple sensor systems are used to reduce complexity, then device complexity is reduced, but measurement precision and occupancy differentiation capability deteriorate
Solution Approach 1:
The patent applies different weighting factors to different evaluation zones within the seat based on their local characteristics and occupancy detection importance. For example, zones more likely to contact occupants receive higher weights, while less critical zones receive lower weights. This localized quality approach allows accurate differentiation using a single sensor.
Solution Approach 2:
The patent changes the evaluation parameters dynamically based on detected conditions. When occupancy is detected in certain zones, the system adjusts which parameters are evaluated and how they are weighted, allowing a simple sensor system to achieve sophisticated differentiation capabilities through intelligent parameter adjustment rather than hardware complexity.
Data Source
AI summary
A method for recognizing a seat occupancy of seats in a motor vehicle including a) preparing a checking sequence of the seats at least using a probability of occupancy of the seats, and b) sequentially checking the occupancy of the seats using the checking sequence prepared in step a).