Lane Information Output Using Sensor Fusion in Low Visibility
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Solution Overview
Problem
Drivers face challenges in maintaining visibility and safety, especially in adverse weather conditions or at night, due to insufficient lane information, which increases the risk of accidents and driver fatigue.
Innovation Solution
A vehicle driving assistance device that uses a combination of sensors, including cameras and radar/lidar modules, to detect lanes, calculate distances, and estimate lane curvature, generating a guide image that includes information about lane state and environment, which is then output to the driver through various displays or audio cues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If drivers rely on direct visibility to operate the vehicle, then the driver can directly observe the road conditions, but in adverse weather conditions or at night, the driver does not have enough visibility to operate the vehicle safely
Solution Approach 1:
The patent introduces an intermediary system consisting of imaging devices, processors, and display devices that mediate between the road environment and the driver. The imaging devices capture road images, the processor generates guide images with enhanced lane information, and the display devices present this information to the driver, enabling safe operation under poor visibility conditions without direct observation
Solution Approach 2:
The patent replaces the mechanical/physiological limitation of human vision with an electronic system. Instead of relying on the driver's eyes to directly observe the road, the system uses imaging devices to capture images, processors to generate enhanced guide images with lane information, and display devices to present this information, substituting the natural visual system with an artificial one that can operate effectively in adverse conditions
2Reliability
If no lane information is provided to the driver, then the device complexity is low, but the driver experiences fatigue and the risk of accidents increases
Solution Approach 1:
The patent segments the driving assistance function into distinct modular components: imaging devices for capturing road images, processors for generating guide images with lane information, and display devices for presenting information to the driver. This segmentation allows each component to be optimized independently while working together to prevent accidents, managing complexity through functional decomposition
Solution Approach 2:
The guide image generation system serves multiple functions simultaneously: it displays road conditions, provides lane guidance information, indicates lane curvature, and enhances visibility in adverse weather. This multi-functionality justifies the added device complexity by delivering comprehensive safety benefits through a single integrated system rather than multiple separate systems
3Loss of information
If lane information is displayed on a window of the vehicle, then the driver receives necessary information, but the information may not be sufficient in adverse weather conditions or at night
Solution Approach 1:
The processor generates guide images in advance that include predicted lane information and curvature data before the driver needs to make steering decisions. By preparing this information ahead of time and presenting it through the display device, the system ensures complete lane information is available to the driver before adverse conditions obscure the road, allowing proactive rather than reactive driving responses
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances driver safety and satisfaction by providing necessary lane information even in poor visibility conditions, reducing the risk of accidents and fatigue by accurately guiding the vehicle through adverse environments.
Implementation Method 1
a camera may be used to set a visible area in an image of a road
Implementation Method 2
the other objects may be classified into objects in a visible area and objects in an invisible area based on whether or not the objects are included in the visible area
Implementation Method 3
sensors, including cameras and radar/lidar modules
Data Source
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AI summary
A vehicle driving assistance device includes: a sensing unit configured to capture a front image of a running vehicle; a processor configured to detect a lane by using the front image and estimate the lane by detecting objects around a road, on which the vehicle is running, by using the sensing unit; and an output unit configured to output the estimated lane.