AEB Parameter Calibration for Probabilistic Collision Triggering
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Solution Overview
Problem
Existing AEB functions in vehicles face issues with missed or false triggering due to estimation errors in Time to Collision (TTC), failing to meet safety and comfort requirements, and there is a need to effectively calibrate complex probabilistic parameters.
Innovation Solution
A method and apparatus for determining AEB function parameters by configuring initial parameters, testing the vehicle in various scenarios, adjusting parameters based on observed behavior, and determining adjusted parameters that meet expected conditions, ensuring compatibility with vehicle type and sensor/actuator performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If simple TTC calculation method is used, then determination process is simple, but missed or false triggering occurs due to estimation error
Solution Approach 1:
The patent transitions from a deterministic TTC threshold approach to a probabilistic risk assessment approach. Instead of using a fixed TTC threshold for triggering AEB, the system calculates collision probability as a continuous parameter ranging from 0 to 1, allowing for more nuanced decision-making that reduces both missed and false triggers while maintaining operational simplicity.
2Reliability
If probabilistic risk assessment method is used, then AEB triggering accuracy is improved, but functional parameters become complex and difficult to calibrate
Solution Approach 1:
The patent implements a self-calibration mechanism where the system automatically determines optimal probabilistic parameters through iterative testing and evaluation. Instead of requiring manual calibration of complex functional parameters, the system performs automated tests under various conditions, evaluates triggering accuracy, and adjusts parameters autonomously, significantly reducing calibration complexity while maintaining high triggering accuracy.
3Manufacturing precision
If probabilistic parameters are calibrated manually, then parameter effectiveness may be improved, but calibration time and resources increase
Solution Approach 1:
The patent replaces manual calibration processes with automated computational methods. The system uses algorithm-driven parameter determination that automatically optimizes probabilistic parameters through simulated testing and real-world data analysis, eliminating the need for time-consuming manual calibration while achieving superior parameter precision and effectiveness.
Data Source
AI summary
Embodiments of the present disclosure disclose a parameter determination method for an AEB function, a medium, and a device. The method includes: configuring current parameters of the AEB function of a vehicle; performing testing on the vehicle based on a test scenario to obtain behavior of the vehicle under the current parameters, the behavior being one of pre-collision braking to stop and collision; performing adjustment on the current parameters based on the behavior to obtain adjusted parameters; and determining the adjusted parameters as target parameters of the AEB function in response to the adjusted parameters meeting an expected condition.