Traffic Incident

Traffic incident management research focuses on improving the speed and effectiveness of response to road incidents, aiming to minimize disruption and enhance safety. Current efforts leverage machine learning, particularly algorithms like Random Forests and Gradient Boosting, along with large language models and graph transformers, to analyze diverse data sources such as vehicle trajectories, accident reports, and sensor data for real-time incident detection, severity classification, and impact prediction. These advancements enable more accurate predictions of incident duration and optimized resource allocation, including the integration of unmanned aerial vehicles, ultimately leading to reduced congestion and improved road safety.