Year: 2025
Type: article
Abstract: : Real-time visual perception is becoming a crucial component in enhancing road safety as smarter transportation systems gain international attention. In order to improve vehicle awareness, this study proposes an integrated vision-based system that combines lane recognition, multi-object tracking, and object detection. In order to promote safer driving, the system processes video input to identify lane boundaries, detect and follow nearby vehicles, and foresee possible hazards. It operates dependably in a variety of road conditions by utilizing both deep learning and conventional computer vision techniques. The model provides a strong basis for advanced driver-assistance and autonomous vehicle technologies, as demonstrated by its consistent real-time output and high accuracy when tested on actual urban driving scenarios.
Authors: Swapnil Sonawane, Shreyas Panzade, Sakshi Wagh
Institution: Vidyalankar Institute of Technology
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409602189