講演情報
[P2-08]東京都市圏における鉄道通勤経路選択の統計力学的モデルGPSデータによる実証分析
*鄭 軼せん1、高安 秀樹1、高安 美佐子1 (1. 東京科学大学)
キーワード：
都市交通、経路選択モデル、GPS軌跡、統計力学
This study applies a multinomial logit (MNL) framework to analyze railway commuters’ route choices using a large-scale dataset of smartphone GPS trajectories. We design a data processing pipeline that extracts structured commuting paths, including transport mode and transfer information, from raw location traces. The model highlights key behavioral patterns in commuter decision-making, such as the substantial disutility associated with transfers and the influence of station capacity on route attractiveness. Our findings demonstrate that passively collected GPS data can support robust revealed-preference modeling at metropolitan scale, offering new opportunities for understanding commuter route choice and informing transit planning.