Driver Assistance Feature Cascades for Poor Road Conditions
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Solution Overview
Problem
Conventional vehicle driver assistance systems are ineffective in poor road conditions such as rain or snow, requiring driver intervention as they are designed for ideal conditions only.
Innovation Solution
A vehicle system that uses an imaging device to generate images of the road trajectory, determining conditions and adjusting driver assistance feature cascades accordingly to compensate for non-ideal conditions, such as using different sets of feature cascades for normal and imperfect road conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If driver assistance systems are designed to operate only in perfect road conditions, then the system operation is simple and reliable in ideal conditions, but the system becomes ineffective and requires driver intervention in poor road conditions
Solution Approach 1:
The driver assistance system dynamically adjusts its operation based on detected road conditions. The system transitions from static operation (designed for perfect conditions only) to dynamic operation where parameters such as feature cascades are modified in real-time based on environmental feedback from imaging devices detecting rain, snow, or other poor conditions.
Solution Approach 2:
The system changes operational parameters based on road conditions. When poor conditions are detected, the system modifies feature cascades and other operational parameters to maintain effectiveness. This allows the same hardware system to adapt its behavior across different environmental conditions without requiring separate systems for each condition.
2Device complexity
If the driver assistance system uses a fixed set of feature cascades for perfect conditions, then the system design and operation is simple, but the system cannot compensate for non-ideal road conditions
Solution Approach 1:
The system employs dynamic parameter adjustment where feature cascades are modified based on detected road conditions. This maintains reasonable design complexity while significantly improving reliability in poor conditions through real-time adaptation of operational parameters.
Solution Approach 2:
The system uses feedback from imaging devices that detect road conditions to adjust feature cascades. This closed-loop approach allows the system to automatically compensate for non-ideal conditions without requiring complex manual reconfiguration, maintaining ease of operation while improving performance.
3Extent of automation
If the system requires driver intervention in poor road conditions, then the system design remains simple, but the automation level decreases and driver workload increases
Solution Approach 1:
The driver assistance system performs self-adjustment by automatically detecting road conditions through integrated imaging devices and modifying its own feature cascades accordingly. This eliminates the need for driver intervention in poor conditions while maintaining automation, as the system serves itself by adapting to environmental changes without external input.
Solution Approach 2:
The system achieves multi-functionality by using the same driver assistance infrastructure to operate across multiple road conditions (perfect, rainy, snowy, etc.). Rather than requiring separate systems or manual mode switching, the universal design allows automatic adaptation to various conditions, maintaining high automation levels.
Data Source
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AI summary
The present disclosure is directed to systems and methods for controlling driver assistance features of a vehicle based on images of a vehicle trajectory condition. In one form, the present disclosure provides a system comprising a memory, an imaging device positioned in a vehicle that is configured to generate images of a surface in front of the vehicle, and at least one processor configured to determine a vehicle trajectory condition based on images generated by the imaging device; when the vehicle trajectory condition is determined to be a first condition based on the images, operate a driver assistance system of the vehicle with a first set of feature cascades; and when the vehicle trajectory condition is determined to be a second condition based on the images, operate the driver assistance system of the vehicle with a second set of feature cascades.