Vehicle Windscreen Display Using GAN Scene Reconstruction
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Solution Overview
Problem
Current methods fail to provide clear visibility to drivers through vehicle windshields during obscured conditions such as rain, snow, or dust accumulation, leading to increased risk of accidents.
Innovation Solution
A system that uses sensors to monitor windscreen visibility, generates a visibility score, and employs a generative adversarial network (GAN) to dynamically convert the windscreen into a display surface, reconstructing the surrounding area in real-time and rendering it on a transparent display layer for the driver.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a transparent display device is used on the windscreen, then digital content and 3D images can be displayed, but the display becomes obscured or blurred during rain, snow, or dust accumulation
Solution Approach 1:
The system creates a synthetic copy of the external scene using GAN-based image generation. Instead of relying on the physical transparency of the windscreen, the system generates a digital replica of the surrounding environment based on sensor data (cameras, LIDAR, radar) and displays it on the transparent display device, effectively copying the visual information that would normally be seen through the clear windscreen.
Solution Approach 2:
The transparent display device acts as an intermediary between the obscured external environment and the driver's view. When the windscreen is obscured, the system mediates the visual information by generating synthetic images of the external scene and presenting them through the display, bridging the gap between the blocked physical view and the driver's need for visual information.
2Loss of information
If the windscreen is converted into a display surface, then clear visibility can be provided through GAN-reconstructed visuals, but the system complexity increases
Solution Approach 1:
The windscreen system is designed to perform multiple functions: it serves as both a physical protective barrier and a dynamic display surface. The transparent display device integrated into the windscreen can operate in multiple modes - remaining transparent when conditions are good, or displaying GAN-reconstructed images when obscured. This multi-functionality consolidates what would otherwise require separate systems (protective windscreen plus independent display system).
Solution Approach 2:
The system replaces traditional mechanical visibility solutions (windshield wipers, heating elements, hydrophobic coatings) with an electronic/software-based approach using GANs and transparent displays. Instead of mechanically clearing the windscreen surface, the system uses image generation algorithms to reconstruct the visual scene, substituting mechanical clearing mechanisms with computational imaging.
3Loss of information
If GAN-enabled adaptation is initiated in real-time, then clear visual reconstruction can be achieved, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by continuously collecting and preprocessing data from external sensors (cameras, LIDAR, radar) even before obscuration occurs. The GAN model is pre-trained on extensive datasets of external environments, allowing it to rapidly generate plausible reconstructions when needed. This preliminary data collection and model training reduces the computational burden during real-time obscured conditions.
Solution Approach 2:
The system dynamically adjusts its processing based on the level of obscuration and driving conditions. When the windscreen is only partially obscured, the GAN processes fewer pixels or lower resolution images. When fully obscured, it activates full processing power. The system also dynamically switches between using actual camera feeds (when partially visible) and GAN-generated images (when fully obscured), optimizing processing time based on real-time conditions.
Data Source
AI summary
A method for rendering clear visibility through the windscreen of a vehicle. The method includes monitoring, by one or more sensors, visibility of a windscreen, wherein monitoring includes analyzing a level of visibility of the windscreen, generating a visibility score, and responsive to the visibility score falling below a predetermined threshold, converting, dynamically, the windscreen into a display surface. The method further includes analyzing an external sensor feed of a vehicle to identify the visibility of a surrounding area. The method further includes initiating, dynamically, a generative adversarial network (GAN) enabled adaptation of the surrounding area of the vehicle, in real-time, to reconstruct a visual based on the external sensor feed, and rendering, in real-time, the GAN enabled adaptation of the surrounding area of the vehicle on a transparent display layer of the windscreen of the vehicle.