LKAS Path Biasing to Avoid Rough Road Surfaces
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Solution Overview
Problem
Lane-keep assist systems (LKAS) center vehicles over localized patterns of rough road surfaces, leading to poor ride quality, cabin noise, and safety issues, particularly in highways with heavy truck traffic.
Innovation Solution
A system using vehicle sensors to detect rough road surfaces and bias the LKAS to avoid these surfaces by adjusting the vehicle's path to alternative areas with lower roughness, utilizing sensors like LiDAR, radar, and cameras to evaluate road conditions and adjust the LKAS offset.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the LKAS centers the vehicle in the lane, then the vehicle positioning accuracy is improved, but the ride quality deteriorates due to traveling over rough road surfaces
Solution Approach 1:
The system evaluates different lateral positions within the lane to identify local areas with better road surface conditions. Instead of uniformly centering the vehicle, it selectively positions the vehicle in specific lateral zones that minimize exposure to rough road surfaces while maintaining lane discipline.
Solution Approach 2:
The system performs preliminary evaluation of road surface conditions ahead of the vehicle using sensors (cameras, LiDAR, radar) to predict and identify rough patches before the vehicle reaches them. This allows the LKAS to proactively adjust the vehicle's lateral position to avoid anticipated rough areas.
2Ease of operation
If the LKAS centers the vehicle in the lane, then the lane-keeping function is improved, but the noise and vibration levels increase due to rough road surfaces
Solution Approach 1:
The system continuously monitors noise and vibration levels from sensors and uses this feedback to dynamically adjust the LKAS bias offset. When rough road surfaces are detected through increased noise and vibration signals, the system automatically shifts the vehicle's lateral position to reduce exposure to these harmful conditions.
3Device complexity
If the LKAS centers the vehicle in the lane, then the system simplicity is maintained, but the ride safety deteriorates due to rough road surfaces
Solution Approach 1:
The system uses existing multi-functional sensors (cameras, LiDAR, radar, microphones, accelerometers) already present in modern vehicles for other purposes (environmental perception, collision avoidance). These same sensors are leveraged to detect road surface conditions, allowing the LKAS enhancement without adding dedicated hardware.
Data Source
AI summary
Systems and methods for detecting rough road surfaces and using lane-keep assist system (LKAS) biasing to avoid rough road surfaces are provided. The system may comprise a vehicle, one or more sensors configured to image an environment of a vehicle, and a computing device, comprising a processor and a memory. The memory may be configured to store instructions that, when executed by the processor, are configured to cause the processor to receive input from the one or more sensors, determine one or more vehicle path areas on a road surface using the input from the one or more sensors, evaluate one or more vehicle path areas for one or more rough road surfaces, and bias an LKAS to avoid one or more rough road surfaces. The one or more vehicle path areas may comprise a current vehicle path area and one or more alternative vehicle path areas.