Implementing computer vision in road traffic management brings significant impacts, making transportation systerms more efficient, safe, and sustainable. This advanced technology analyzes real-time traffic conditions, providing crucial data for effective traffic management. Using computer vision, authorities can monitor traffic flow, detect incidents, and manage congestion more effectively. The primary aim of this paper is to explore the challenges and impacts associated with using computer vision in road traffic management while offering insights for future research and practical applications. A Systematic Literature Review (SLR) was conducted, adhering to the PRISMA Flowchart Diagram methodology, to identify and evaluate relevant studies in this field. The systematic approach ensures a comprehensive understanding of the current state of computer vision in the transportation sector. The findings from this review underscore the transformative potential of computer vision in enhancing traffic management systems. Moreover, this work highlights several existing challenges that need to be addressed to maximize the benefits of computer vision. These challenges include the need for more advanced algorithms capable of handling diverse and complex traffic scenarios and integrating this technology with existing infrastructure. By identifying these challenges, the paper provides valuable insights for future research, emphasizing the importance of developing more robust and adaptive computer vision systems. Ultimately, this research aims to contribute to advancing computer vision in road traffic management, promoting safer and more efficient transportation systems worldwide.
The Influence of Computer Vision on Road Traffic
20.11.2024
273568 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Computer vision-aided road traffic monitoring
Kraftfahrwesen | 1991
|Vision-based road-traffic monitoring sensor
IET Digital Library Archive | 2001
|Vision based road traffic data collection
Tema Archiv | 1993
|