Road Surface Imaging for Adaptive Driver Assistance Cascades
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Solution Overview
Problem
Conventional vehicle driver assistance systems are limited to performing optimally in perfect road conditions and often require driver intervention in adverse conditions such as rain or snow.
Innovation Solution
A vehicle system that utilizes an imaging device to generate images of the road surface, determining the vehicle trajectory condition, and adjusts driver assistance features through different cascades based on ideal or non-ideal conditions, using processor-controlled adjustments for adaptive cruise control, emergency braking, and following distance alerts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If driver assistance systems operate with fixed feature cascades optimized for perfect road conditions, then system performance is optimized for dry asphalt, but system reliability deteriorates in adverse conditions such as rain or snow requiring driver intervention
Solution Approach 1:
The system dynamically adjusts feature cascades based on detected road conditions. The processor determines the current road condition (dry, wet, snowy, icy) and selectively activates appropriate feature cascades from a plurality of available cascades, allowing the system to adapt its behavior to match current environmental conditions rather than using a fixed configuration
Solution Approach 2:
The system changes operational parameters by selecting different feature cascades with varying sensitivity thresholds and activation criteria. Each feature cascade contains pre-configured parameters optimized for specific road conditions, and the processor switches between these parameter sets based on real-time condition assessment
2Adaptability or versatility
If driver assistance systems use multiple feature cascades for different road conditions, then adaptability to various conditions improves, but device complexity increases
Solution Approach 1:
The system segments the control logic into distinct feature cascades, each dedicated to handling specific road conditions. This segmentation allows the complex task of adapting to multiple conditions to be divided into manageable, pre-configured modules that can be selectively activated without requiring complex real-time decision logic
Solution Approach 2:
The feature cascades are pre-configured and stored in memory before runtime. The processor simply needs to determine current conditions and select the appropriate pre-prepared cascade, avoiding the complexity of dynamically generating control parameters in real-time. This preliminary preparation simplifies the runtime operation significantly
Data Source
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.