表題番号：2023E-037 日付：2024/04/04
研究課題Research on machine learning based cross-area person trajectory forecasting technology
研究者所属（当時） 資格 氏名
（代表者） 国際学術院 国際教養学部 講師 斉　欣
研究成果概要
My research developed a machine learning system for predicting person trajectories across different areas, demonstrating promising results in small-scale experiments. Employing deep learning and feature engineering on a diverse dataset, the system outperformed traditional forecasting methods in accuracy. Future work aims to scale this technology for larger, more complex environments and integrate it into urban planning and management frameworks. Despite initial successes, challenges such as scalability, generalizability, and ethical considerations remain. The findings indicate a significant potential for machine learning in enhancing trajectory forecasting, with broader implications for urban planning and security.