A new research paper on urban rail passenger demand forecasting in Tokyo
2016年4月に策定された国土交通省交通政策審議会答申「東京圏における今後の都市鉄道のあり方について」で用いられている東京都市圏鉄道需要予測モデルに関する研究論文が国際誌 “Transportation Research Record” に掲載決定しました（Conference Paperはこちらで閲覧できます）．芝浦工業大学岩倉先生，東京大学加藤先生，運輸総合研究所伊東様，株式会社社会システムの皆様と数年に渡って議論と分析を繰返してきた内容であり，我が国の都市鉄道需要予測手法の State-of-Practice を海外に発信することができました．関係各位に深くお礼申し上げます．
Latest Urban Rail Demand Forecast Model System in the Tokyo Metropolitan Area
By Hironori Kato, Daisuke Fukuda, Yoshihisa Yamashita, Seiji Iwakura and Tetsuo Yai
This paper reports on an urban rail travel demand forecast model system, which technically supported the formulation of the Tokyo Urban Rail Development Master-plan 2016. The model system was included in the forthcoming 15-year urban rail investment strategy for Tokyo. The model system was utilized to quantitatively assess urban rail projects including 24 new rail development projects, which had been proposed in response to expected changes in socio-demographic patterns, land-use market, and the government’s latest transportation policy goals. The system covers the entire urban rail network within the Tokyo Metropolitan Area (TMA) of approximately 50-km radius with a population of over 34 million. The system must handle over 80 million trips per day. Three demand models are used to predict daily rail passenger link flows: the urban rail demand model, the airport rail access demand model, and the high-speed-rail rail access demand model. These practical models have unique characteristics such as incorporating differences in behavior between aged and non-aged travelers, reflecting expected influences of urban redevelopment on trip generation and distribution, highlighting urban rail access to airports or high-speed-rail stations, examining impacts of in-vehicle crowding on rail route choice, and deploying urban rail-station access/egress mode choice models for rail route choice. It is concluded that the model system would be well calibrated with observed data for reproducing travel patterns, identifying potential problems, assessing proposed projects, presenting results with high accuracy, and assisting decision-making of urban rail planners.
