Vehicle Restraint Deployment Adaptation Using 3D Occupant Sensing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current crash algorithms in vehicles are limited by the technology of sensors used to estimate occupant size and position, leading to mis-classification and inaccurate restraint deployment strategies, especially in autonomous driving scenarios where occupant positions can vary significantly.
Innovation Solution
A method and system that utilizes a 3D sensor system to directly measure occupant size and position, combining this data with traditional seat sensors to create a fused occupant classification, which is then used to adapt restraint deployment strategies based on actual occupant morphology and position, including the use of an electronic control unit to manage airbag and seatbelt deployment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional seat track and weight sensors are used for indirect occupant classification, then the device complexity is low, but the measurement precision of occupant size and position is insufficient leading to mis-classification
Solution Approach 1:
The patent combines traditional seat sensors (track and weight sensors) with a 3D sensor system to create a fused occupant classification system. This merging approach integrates the simplicity of existing sensors with the precision of 3D sensing, achieving high measurement accuracy without completely replacing the existing sensor infrastructure
Solution Approach 2:
The patent introduces a fusion module as an intermediary that processes and combines data from multiple sensor sources (seat track sensor, weight sensor, and 3D sensor system). This fusion module acts as a mediator that synthesizes information from different sensing modalities to produce accurate occupant classification while managing the complexity of multiple sensors
2Reliability
If current crash algorithms with limited sensor technology are used, then the system is simple to operate, but the restraint deployment strategy accuracy is insufficient for varied occupant positions
Solution Approach 1:
The patent implements dynamic restraint deployment strategies that adapt in real-time based on the fused occupant classification. The system dynamically adjusts airbag deployment parameters (such as deployment force, timing, and sequence) according to the actual occupant size and position, ensuring optimal protection reliability for each specific scenario
Solution Approach 2:
The system uses feedback from the 3D sensor system and seat sensors to continuously monitor occupant position and size, then feeds this information back to the crash algorithm to adjust the restraint deployment strategy. This closed-loop feedback mechanism ensures accurate and reliable deployment decisions adapted to actual occupant conditions
3Adaptability or versatility
If indirect estimation methods are used for occupant classification, then the device complexity is low, but the adaptability to different occupant morphologies is insufficient
Solution Approach 1:
The patent transitions from indirect 1D/2D estimation (seat track position and weight) to direct 3D measurement of occupant morphology. The 3D sensor system captures three-dimensional spatial information about the occupant, enabling accurate classification of different body types, sizes, and positions that cannot be determined by traditional indirect methods alone
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the accuracy of restraint deployment by adapting to the actual occupant size and position, reducing mis-classification and optimizing deployment strategies for various occupant sizes and positions, thereby minimizing injury during crashes.
Implementation Method 1
Processing resources are provided that determine depth information for an object in the scene based on a time-of-flight characteristic of the reflected light from the light source captured on the array
Data Source
Figure 1
Figure 2~3C
Figure 4
AI summary
The invention relates to a method and system for restraint deployment adaption in a vehicle (1) based on occupant sensing. A size of an occupant (3) and a position of the occupant (3) in the seat (7) are determined or measured with at least one 3D sensor system (21). In addition to the 3D sensor system (21) at least one seat track sensor (12) is connected to the fusion module (51) of the ECU (1). At least one central impact sensor (4C) and optionally one or several remote impact sensors (4R) of the vehicle (1) are connected to the event detection module (52) of the ECU (1). A deployment requests module (54) carries out an adjustment of the restraint system strategy in function of the actual classification of the occupant (3).