Accident Hotspot

Accident hotspots, areas with a statistically significant higher-than-average frequency of traffic accidents, are a key focus in transportation safety research. Current research emphasizes developing improved methods for identifying these hotspots, employing techniques like clustering algorithms (e.g., Affinity Propagation Clustering) and advanced machine learning models such as Conditional Generative Adversarial Networks (CGANs) to analyze crash data and predict accident likelihood. These advancements aim to enhance the accuracy and efficiency of hotspot identification, ultimately leading to more effective strategies for targeted safety interventions and a reduction in traffic accidents.