[E4] 移動・交通３

5:00 PM - 5:20 PM JST(8:00 AM - 8:20 AM UTC)

[E4-04] 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

*Yixuan Y. Zheng¹, Hideki Takayasu¹, Misako Takayasu¹ (1. Institute of Science Tokyo)

Keywords:

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.