Neural Lane Departure Warning for Intent-Aware Driver Alerts
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing driving warning systems are unable to account for various combinations of factors that may indicate unintentional lane line crossing, leading to inadequate or inappropriate warning issuance.
Innovation Solution
A device comprising an input unit, a processing unit with an artificial neural network, and an output unit, which processes driving relevant data to generate driving awareness data and output timely and appropriate driving warning information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional distance-to-line-crossing and time-to-line-crossing methods are used for lane departure warning, then the system structure is simple, but the system cannot account for various combination of factors indicating unintentional lane crossing
Solution Approach 1:
The system segments the complex driving scenario analysis into multiple independent factors including distance to line crossing, time to line crossing, steering angle, lane width, and driver behavior patterns. Each factor is processed separately by dedicated sensors and algorithms, then integrated to form comprehensive lane departure warnings. This segmentation allows the system to consider various combinations of factors without creating an unmanageably complex monolithic structure.
Solution Approach 2:
The patent introduces an intermediary processing layer that receives data from multiple sensors (cameras, GPS, steering angle sensors) and combines them with map data and driver profile information. This intermediary layer acts as a mediator that integrates diverse data sources and applies complex decision logic, shielding the simplicity of individual sensor components while enabling sophisticated multi-factor analysis for lane departure warnings.
2Reliability
If lane departure warning threshold is set to be sensitive to detect all potential lane crossings, then detection coverage is improved, but unwanted warnings increase
Solution Approach 1:
The system performs preliminary analysis of driver behavior patterns and contextual factors before issuing lane departure warnings. By pre-processing steering angle data, acceleration patterns, and driver intent indicators, the system can predict whether a detected lane crossing is intentional or unintentional. This preliminary action allows the system to maintain high detection coverage while filtering out false alarms caused by intentional lane changes or driver corrections.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors driver responses to warnings and adjusts warning thresholds accordingly. When drivers intentionally change lanes, the system learns from these patterns and adjusts future warning behavior. This feedback loop enables the system to maintain high reliability in detecting unintentional lane crossings while reducing unwanted warnings by adapting to individual driver behaviors and preferences.
Data Source
Figure 1~2
Figure 3a~4
Figure 5
AI summary
The present invention relates to a device (10) for determining driving warning information. It is described to provide (210) driving relevant data. The driving relevant data is provided by an input unit (20). The driving relevant data is processed (220) with an artificial neural network to generate driving awareness data. A processing unit (30) implements the artificial neural network. Driving warning information is output (230) based on the driving awareness data. An output unit (40) outputs the driving warning information.