Speed Map

Speed maps represent a rapidly developing field focused on predicting and controlling vehicle speeds across various contexts, from roadways to off-road environments. Current research emphasizes the use of machine learning models, including recurrent neural networks (RNNs), mixture-of-experts (MoE) approaches, and spatio-temporal diffusion networks, to improve prediction accuracy and incorporate contextual factors like incidents, weather, and road geometry. These advancements aim to enhance traffic flow, optimize navigation for autonomous vehicles, and improve safety by predicting and mitigating risky driving behaviors. The resulting insights have implications for intelligent transportation systems, autonomous navigation, and traffic management strategies.