Visibility Enhancement and Fog Detection: Solutions Presented in Recent Scientific Papers with Potential for...

Area of Science:

• Environmental Science
• Computer Vision
• Automotive Engineering

Background:

• Natural phenomena like fog, rain, snow, haze, and sun glare pose significant risks to drivers by reducing visibility.
• These conditions affect contrast, color perception, and can cause dangerous glare, impacting driving safety and speed decisions.
• Visibility is paramount for autonomous vehicles, necessitating advanced solutions to navigate adverse weather.

Purpose of the Study:

• To synthesize recent scientific literature (past 10 years) on methods and systems for estimating and improving visibility in adverse weather conditions.
• To identify technological advancements in sensors, communication, and data processing relevant to overcoming visibility challenges.
• To specifically focus on the fog phenomenon, identified as the most dangerous environmental factor for mobile systems.

Main Methods:

• Comprehensive literature search of scientific publications over the last decade.
• Analysis of research focusing on methods to estimate or enhance visibility in adverse weather.
• Categorization of solutions including image processing techniques, optical power measurement, and sensor systems.

Main Results:

• Fog presents the most significant danger to mobile systems among various adverse weather conditions.
• Various methods based on image processing, optical power measurement, and sensor systems have been explored to address visibility issues.
• Technological evolution in sensors and data processing offers potential for new solutions.

Conclusions:

• Visibility estimation and enhancement in adverse weather are critical for mobile and autonomous systems.
• Fog is a primary concern, with image processing and sensor-based approaches showing promise.
• Continued research integrating sensor technology and data processing is essential for improving driving safety.