Vehicle Occupant Protection Triggering via Sensor Fusion
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Solution Overview
Problem
Existing occupant protection systems in vehicles lack precision in triggering and positioning, leading to potential injuries due to incomplete detection of collision scenarios and occupant positioning, which can result in suboptimal deployment of airbags and seatbelts.
Innovation Solution
The method utilizes interior and exterior cameras, radar, and Lidar signals to detect collisions and occupant movements, allowing for precise control and timing of occupant protection devices like airbags and seatbelts, ensuring they are deployed only when necessary and optimally positioned to minimize injury risk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If occupant protection means are triggered based on traditional collision detection, then the response speed is fast, but the precision of triggering and positioning is insufficient leading to potential injuries
Solution Approach 1:
The system segments the detection process into multiple independent components: interior cameras for occupant detection, exterior cameras for collision scenario detection, radar for distance measurement, and Lidar for spatial mapping. Each sensor type processes specific aspects of the environment, and their results are integrated to achieve high-precision triggering decisions and positioning of protection means.
Solution Approach 2:
The patent merges data from multiple sensor systems (cameras, radar, Lidar) to create a comprehensive view of the collision scenario and occupant position. This fusion of detection data enables precise determination of both when to trigger protection means and where to position them for maximum effectiveness.
2Reliability
If occupant protection means are deployed based on incomplete collision detection, then the system response is simple, but the effectiveness is reduced due to suboptimal deployment
Solution Approach 1:
The system performs preliminary detection and analysis of collision scenarios using exterior cameras and radar before the actual collision occurs. This advance detection allows the system to pre-calculate optimal deployment positions and timing for occupant protection means, ensuring they are deployed at the precise moment and location needed for maximum protective effectiveness.
Solution Approach 2:
The system continuously monitors the environment using multiple sensors and uses this feedback to dynamically adjust the triggering decisions and positioning of protection means. The real-time data from cameras, radar, and Lidar provides continuous feedback about occupant position and collision progression, enabling adaptive optimization of the protection deployment.
3Measurement precision
If traditional sensor systems are used for collision detection, then the system is simple, but the accuracy of collision scenario detection is insufficient
Solution Approach 1:
The patent implements multi-functional sensor systems where each sensor type serves multiple purposes. For example, exterior cameras not only detect collision scenarios but also track the motion of other vehicles and objects. Radar systems simultaneously measure distance, speed, and trajectory of potential collision objects. This multi-functionality allows the system to achieve high detection accuracy without proportionally increasing the total sensor count.
Solution Approach 2:
The system transitions from traditional single-dimension collision detection to multi-dimensional detection by incorporating spatial information from Lidar and radar alongside visual data from cameras. This adds depth, distance, and velocity dimensions to the collision detection, enabling much more accurate characterization of collision scenarios using a coordinated sensor array rather than excessive individual sensors.
Data Source
AI summary
A method for operating an occupant protection device of a vehicle involves triggering an occupant protection mechanism, in the event of an imminent detected collision for the vehicle or of a detected collision of the vehicle. The triggering also depends upon detected image data of at least one interior camera of the vehicle and the triggering can be suppressed based on the detected image data of the interior camera.