Vehicle Controller Area-Specific Confidence Lane Departure Prevention
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Solution Overview
Problem
Conventional lane departure prevention systems are limited by their reliance on overall confidence calculations, which degrade when drivers have difficulty seeing road markers or when lane marks are worn or obscured, leading to reduced effectiveness and potential erroneous control.
Innovation Solution
A vehicle controller that uses area-specific confidence calculations to divide images into distinct areas based on lane recognition, allowing for independent control methods to be applied to each area, incorporating vehicle speed, steering angle, and yaw rate information to enhance lane departure prevention while minimizing erroneous control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If overall confidence calculation is used for lane mark recognition, then the system maintains simplicity in control decision-making, but the availability ratio of departure prevention control degrades when partial areas have poor visibility
Solution Approach 1:
The image is divided into multiple areas (e.g., left lane area, right lane area, center area) and confidence is calculated independently for each area. This allows the system to identify which specific areas have reliable lane mark recognition and which do not, preventing poor visibility in one area from degrading the overall system reliability.
Solution Approach 2:
Different confidence thresholds and control strategies are applied to different areas of the image based on their specific visibility conditions. High-confidence areas can enable departure prevention control while low-confidence areas trigger alternative control methods, optimizing both reliability and operational appropriateness.
2Reliability
If area-specific confidence calculation is implemented, then the application range of departure prevention control is expanded, but the device complexity increases
Solution Approach 1:
The image processing is segmented into multiple areas with independent confidence calculations. This modular approach allows the system to process only relevant areas, reducing unnecessary computational complexity while expanding the application range to situations where partial lane visibility is sufficient.
Solution Approach 2:
The system performs confidence calculation only for necessary areas rather than uniformly processing the entire image. This selective processing approach reduces overall computational complexity while maintaining expanded application range for departure prevention control.
3Reliability
If area-specific confidence information is used for control decisions, then erroneous control is suppressed, but the processing time and computational load increase
Solution Approach 1:
The image is divided into areas that are processed independently and in parallel. This segmentation allows the system to identify high-confidence areas quickly and make control decisions based on those areas alone, reducing overall processing time while maintaining error suppression through multi-area verification.
Solution Approach 2:
The system performs preliminary confidence assessment for each area before making final control decisions. This preliminary filtering allows the system to quickly identify areas with sufficient confidence and proceed with control decisions without unnecessary computational overhead from reprocessing low-confidence areas.
Data Source
AI summary
A vehicle controller is provided capable of expanding an application range of departure prevention control while suppressing erroneous control. The vehicle controller includes: a vehicle-mounted camera 600 that captures an image in front of a vehicle; and an ECU 610 that decides one vehicle control method from a plurality of vehicle control methods and controls an actuator with the decided vehicle control method. The vehicle-mounted camera includes an area-specific confidence calculation section 400 that divides the image captured into a plurality of areas on a basis of an acquired image by the capturing and a recognized lane, calculates confidence for each divided area and outputs area-specific confidence information, and the ECU decides a vehicle control method in accordance with the area-specific confidence information.