Adaptive Roadway Surface Estimation Threshold
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Solution Overview
Problem
Existing vehicle controller systems fail to update roadway surface estimates frequently enough, leading to outdated estimates even when the surface condition changes, such as from dry to wet, as the error value may not exceed a constant threshold, causing the system to neglect current conditions.
Innovation Solution
A method and system that determine when to update the surface estimation value by calculating yaw rate errors, predicted front axle cornering forces, and wheel slip values, using sensors and a vehicle dynamics model to adjust the threshold values and indicate updates based on these calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a constant threshold value is used to determine when to update the roadway surface estimate, then the system is simple to implement, but the surface estimation value is not updated regularly enough to reflect current roadway conditions
Solution Approach 1:
The patent transforms the static constant threshold into a dynamic adaptive threshold that automatically adjusts based on vehicle operating conditions. The threshold is no longer fixed but varies according to factors like vehicle speed, steering angle, and braking status, allowing the system to remain simple to implement while accurately detecting surface condition changes under diverse driving scenarios.
Solution Approach 2:
The patent changes the parameter of the threshold from a constant value to a variable value that depends on multiple vehicle operational parameters. By introducing dependencies on speed, steering angle, and braking status, the threshold adapts to different driving conditions, enabling reliable surface estimation updates without complicating the overall system architecture.
2Stability of the object's composition
If the error value threshold is set high to avoid false updates, then false updates are reduced, but legitimate surface condition changes are missed
Solution Approach 1:
The patent makes the threshold dynamic by linking it to vehicle operating conditions. During steady-state driving, the threshold can be higher to prevent false updates, while during transient maneuvers like braking or sharp steering, the threshold adjusts to be more sensitive, capturing legitimate surface condition changes that would otherwise be missed.
Solution Approach 2:
The patent introduces multiple parameters (vehicle speed, steering angle, braking status) that influence the threshold value. This multi-parameter approach allows the system to differentiate between normal variations and genuine surface condition changes, maintaining stability while improving detection accuracy across different driving scenarios.
3Measurement precision
If the system updates the surface estimation frequently, then current roadway conditions are reflected accurately, but false updates increase due to normal vehicle dynamics variations
Solution Approach 1:
The patent implements a dynamic threshold that adapts to vehicle operating conditions, allowing frequent updates when conditions warrant (such as during braking or cornering) while maintaining stability during normal driving. This dynamic approach reduces false updates by contextualizing yaw rate errors within the current driving scenario.
Solution Approach 2:
The patent uses multiple vehicle parameters (speed, steering angle, braking status) to modulate the update frequency and threshold. By considering these additional parameters, the system can distinguish between yaw rate variations caused by normal vehicle dynamics and those indicating genuine surface condition changes, thereby reducing false updates while maintaining accuracy.
4Measurement precision
If a dynamic threshold based on multiple parameters is used, then surface estimation accuracy improves, but system complexity increases
Solution Approach 1:
The patent leverages existing vehicle sensors and controllers that are already present in modern vehicles. By utilizing data from existing yaw rate sensors, speed sensors, steering angle sensors, and brake systems, the patent avoids adding dedicated hardware, thus improving surface estimation accuracy without significantly increasing overall system complexity.
Solution Approach 2:
The patent enables the existing vehicle control system to serve multiple functions. The same sensors and controllers used for basic vehicle stability and control are also utilized for surface condition estimation, allowing the system to improve accuracy through multi-parameter analysis without requiring separate dedicated systems for each function.
Data Source
AI summary
A system and a method for determining when to update a surface estimation value indicative of a condition of a roadway surface are provided. The method includes determining a front axle cornering force error value based on a predicted front axle cornering force value and a first front axle cornering force value. The method further includes determining a threshold yaw rate error value based on the front axle cornering force error value. The method further includes indicating that the surface estimation value is to be updated when a yaw rate error value is greater than the threshold yaw rate error value.