Visual Detection of Traffic Incident through Automatic Monitoring of Vehicle Activities
Abdul Karim, Muhammad Amir Raza, Yahya Z. Alharthi, Ghulam Abbas, Salwa Othmen, M.S. Hossain et al. · 2024 · 20 citationsRead the paper
Intelligent transportation systems (ITSs) derive significant advantages from advanced models like YOLOv8, which excel in predicting traffic incidents in dynamic urban environments. Roboflow plays a crucial role in organizing and preparing image data essential for computer vision models. Initially, a dataset of 1000 images is utilized for training, with an additional 500 images reserved for validation purposes. Subsequently, the Deep Simple Online and Real-time Tracking (Deep-SORT) algorithm enhances scene analyses over time, offering continuous monitoring of vehicle behavior. Following this, the YOLOv8 model is deployed to detect specific traffic incidents effectively. By combining YOLOv8 with Deep SORT, urban traffic patterns are accurately detected and analyzed with high precision. The findings demonstrate that YOLOv8 achieves an accuracy of 98.4%, significantly surpassing alternative methodologies. Moreover, the proposed approach exhibits outstanding performance in the recall (97.2%), precision (98.5%), and F1 score (95.7%), underscoring its superior capability in accurate prediction and analyses of traffic incidents with high precision and efficiency.
6 ideas Seedlabs derived from this research
A specialized monitoring software for city traffic control centers that uses YOLOv8 and Deep-SORT to automatically detect and alert operators to traffic accidents or stalls in real-time.
AI score 80/100An automated monitoring tool that uses YOLOv8 and Deep-SORT to detect and alert city operators of traffic accidents or illegal vehicle activities in real-time.
AI score 73/100A service that turns intersection camera feeds into verified collision events with timestamped video evidence, automatically notifying emergency services and insurers to speed up response and claims.
AI score 60/100A plug-in video analytics module that attaches to existing traffic cameras to automatically detect accidents, stalls, and abnormal vehicle behavior in real time and alert traffic control centers within seconds.
AI score 59/100A plug-in software module that upgrades existing city traffic cameras with real-time incident detection by running YOLOv8 + Deep SORT on the live video feed, automatically alerting traffic control centers within seconds of an incident.
AI score 52/100A cloud-based service that ingests dashcam or depot camera footage from commercial fleets and uses YOLOv8 + Deep SORT to automatically flag near-misses, collisions, and unsafe vehicle behaviors, feeding insurers and fleet managers actionable risk reports.
AI score 48/100