Crash Discrimination Algorithm for Vehicle Safety Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current vehicle safety systems struggle to accurately discriminate between various types of crash events, such as oblique moving deformable barrier, full frontal, offset, oblique/angular, and small overlap crashes, which affects the timely and appropriate deployment of occupant protection devices, and these systems are often platform-dependent, leading to inconsistent performance across different vehicle configurations.
Innovation Solution
A vehicle safety system equipped with front and side impact sensors, including crush zone and multi-axis sensors, that implement a discrimination algorithm to classify crash events by comparing sensor data from left-hand, right-hand, and central sensors, allowing for the identification of oblique moving deformable barrier crashes and other types, and controlling the deployment timing of actuatable restraining devices accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If simple accelerometer-based crash detection is used, then the system is easy to operate and low cost, but the measurement precision and ability to discriminate between different crash types is insufficient
Solution Approach 1:
The patent segments the crash detection function into multiple specialized sensors positioned at different locations (frontal, side, rear impact sensors and crush zone sensors). Each sensor monitors specific crash parameters, and the controller integrates these segmented measurements to achieve accurate discrimination between different crash types without requiring a single overly complex sensor system.
Solution Approach 2:
The patent transitions from single-axis acceleration measurement to multi-dimensional crash parameter monitoring by incorporating sensors that measure acceleration in multiple directions (frontal, lateral, longitudinal) and at multiple locations throughout the vehicle. This dimensional expansion enables the system to distinguish between various crash types based on the unique signature of acceleration vectors and patterns.
2Adaptability or versatility
If platform-dependent discrimination schemes are implemented, then the system can be optimized for specific vehicle configurations, but the adaptability to different vehicle platforms is reduced
Solution Approach 1:
The patent implements a universal discrimination system where the controller uses the same multi-sensor configuration and discrimination algorithm across different vehicle platforms. The system is designed to function reliably whether the vehicle is equipped with two-wheel drive or four-wheel drive, front-engine or mid-engine layouts, by focusing on universal crash physics rather than platform-specific characteristics.
Solution Approach 2:
The patent adjusts discrimination thresholds and parameters based on vehicle-specific characteristics such as weight distribution, sensor locations, and crash test data for each platform. The controller modifies operational parameters like acceleration thresholds and timing windows to account for differences in vehicle mass, suspension characteristics, and structural response, thereby maintaining reliable crash identification across diverse platforms.
3Measurement precision
If multiple sensors and complex discrimination algorithms are deployed, then crash event discrimination accuracy improves, but the processing time and system response delay increase
Solution Approach 1:
The patent pre-programs the controller with discrimination algorithms and threshold values determined through extensive crash testing and simulation. During a crash event, the controller immediately compares sensor inputs against pre-established criteria and deployment maps, eliminating the need for complex real-time calculations. This preliminary preparation enables rapid discrimination and deployment decisions within milliseconds of crash initiation.
Solution Approach 2:
The patent implements a streamlined discrimination process that skips unnecessary intermediate analysis steps by using direct threshold comparisons and pattern recognition based on pre-characterized crash signatures. The system rapidly evaluates key parameters (acceleration magnitude, direction, duration, and sensor correlation) against stored reference patterns, enabling quick classification of crash type and immediate activation of appropriate restraint systems without prolonged processing delays.
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
The system effectively discriminates between different crash types, enabling precise and timely activation of occupant protection devices, improving safety by ensuring appropriate responses to varying crash scenarios and adapting to different vehicle platforms.
Implementation Method 1
front impact sensors configured to measure acceleration in the longitudinal direction of the vehicle
Implementation Method 2
side impact sensors configured to measure acceleration in the longitudinal direction of the vehicle and lateral direction of the vehicle
Data Source
AI summary
A method for controlling an actuatable restraining device includes sensing a plurality of crash event indications in response to a crash event. The method also includes classifying the crash event in response to comparing the sensed crash event indications against one another to identify an oblique moving deformable barrier crash event. The method further includes controlling deployment timing of the actuatable restraining device in response to the classification of the crash event.