GPS Trajectory

GPS trajectory analysis focuses on understanding and modeling the movement of objects, primarily people and vehicles, as recorded by GPS devices. Current research emphasizes developing robust methods for handling noisy or incomplete data, often employing machine learning techniques like transformers, graph convolutional networks, and diffusion probabilistic models to improve accuracy and efficiency in tasks such as anomaly detection, travel time prediction, and map generation. These advancements have significant implications for various fields, including urban planning, transportation optimization, and public health, by enabling more accurate modeling of human mobility and improved resource allocation. Furthermore, privacy-preserving techniques are being actively developed to mitigate concerns associated with the use of location data.