Latest Urban Rail Demand Forecast Model System in the Tokyo Metropolitan Area

Abstract

A model system to forecast urban rail travel demand technically supported the formulation of the Tokyo Urban Rail Development Master Plan for 2016. The model system was included in the forthcoming 15-year urban rail investment strategy for Tokyo and was used to make a quantitative assessment of urban rail projects, including 24 new rail development projects that had been proposed in response to expected changes in sociodemographic patterns, land use markets, and the government’s latest transportation policy goals. The system covered the entire urban rail network within the Tokyo metropolitan area, with approximately a 50-km radius and a population of more than 34 million. The system would have to have handled more than 80 million trips per day. Three demand models were used to predict daily rail passenger link flows: urban rail, airport rail access, and high-speed rail access. These practical models had unique characteristics, such as incorporating differences in behavior between older and younger travelers, reflecting expected influences of urban redevelopment on trip generation and distribution, highlighting urban rail access to airports or high-speed-rail stations, examining effects of in-vehicle crowding on rail route choice, and deploying mode choice models for urban rail station access–egress for rail route choice. The authors 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.

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References

Urban Rail Transport Strategy in the Tokyo Metropolitan Area. Council for Transport Policy, April 2016 (in Japanese).

Morichi

, Iwakura

, Morishige

, Itoh

, and Hayasaki

. Tokyo Metropolitan Rail Network Long-Range Plan for the 21st Century. Presented at 80th Annual Meeting of the Transportation Research Board, Washington, D.C., Jan. 2001.

Kato

Urban Rail Investment in Tokyo from 2000 to 2010. Paper 2014-5, International Transport Forum’s Discussion Paper Series. Organisation for Economic Co-operation and Development, Paris, 2014, pp. 1–27.

Suzuki

, Murakami

, Hong

Y.-H.

, and Tamayose

. Financing Transit-Oriented Development with Land Values: Adapting Land Value Capture in Developing Countries. World Bank Publications, Washington, D.C., 2015. https://doi.org/10.1596/978-1-4648-0149-5.

Central Japan Railway Company Annual Report 2013. Central Japan Railway Co., Nagoya, Japan. http://english.jrcentral.co.jp/company/ir/annualreport/_pdf/annualreport2013.pdf.

Yai

, Iwakura

, and Morichi

. Multinomial Probit with Structured Covariance for Route Choice Behavior. Transportation Research Part B: Methodological, Vol. 31, No. 3, 1997, pp. 195–207. https://doi.org/10.1016/S0191-2615(96)00025-2.

Kato

Recent Issues in Air Transportation Demand Forecast. Kosei-ken Series, No. 683. Aviation Policy Research Association, Tokyo, 2014 (in Japanese).

Transportation Planning Council in the Tokyo Metropolitan Area. Fifth Person Trip Survey in the Tokyo Metropolitan Area: Tokyo Metropolitan Area Understood with Person’s Trips. Transportation Letters in the Tokyo Metropolitan Area, Vol. 22, pp. 1–14, 2010 (in Japanese). http://www.tokyo-pt.jp/publicity/file/vol22.pdf.

Kato

, Kaneko

, and Inoue

. Comparative Analysis of Transit Assignment: Evidence from Urban Railway System in the Tokyo Metropolitan Area. Transportation, Vol. 37, No. 5, 2010, pp. 775–799. https://doi.org/10.1007/s11116-010-9295-8.

10.

Yaginuma

, Fukuda

, and Schmöcker

J-D.

. A Large Scale Application of a Hyperpath-Based Railway Assignment Model Considering Congestion Effects to Tokyo Metropolitan Area. Proceedings of the Conference on Advanced Systems for Public Transport, Santiago, Chile, 2012.

11.

Spiess

, and Florian

. Optimal Strategies: A New Assignment Model for Transit Networks. Transportation Research Part B: Methodological, Vol. 23, No. 2, 1989, pp. 83–102. https://doi.org/10.1016/0191-2615(89)90034-9.

12.

Fukuda

, and Ito

. Development of Hyperpath-Based Risk-Averse Route Guidance System and Its Verification. Presented at 7th Regional Symposium on Infrastructure Development, Nov. 5–7, 2015, Bangkok, Thailand.

13.

Tsuchiya

, Fukuda

, Sakashita

, and Muto

. Analysis of Travel Time Reliability Improvement for Airport Access Roads in Tokyo Metropolitan Area. Paper 182. Proceedings of Infrastructure Planning, Vol. 51, 2015 (in Japanese).

14.

Williams

H. C. W. L.

Travel Demand Models, Duality Relations and User Benefit Analysis. Journal of Regional Science, Vol. 16, No. 2, 1976, pp. 147–166. https://doi.org/10.1111/j.1467-9787.1976.tb00960.x.

15.

Kato

Valuation of Urban Rail Service: Experiences from Tokyo, Japan. Paper 2014-1, International Transport Forum’s Discussion Paper Series. Organisation for Economic Co-operation and Development, Paris, 2014, pp. 1–29.

16.

Kitamura

, Kikuchi

, Fujii

, and Yamamoto

. An Overview of PCATS/DEBNetS Micro-Simulation System: Its Development, Extension, and Application to Demand Forecasting. In Simulation Approaches in Transportation Analysis: Recent Advances and Challenges ( Kitamura

and Kuwahara

, eds.), Springer, Boston, Mass., 2005, pp. 371–399.

17.

Kamegai

, and Fukuda

. Comparison of Analytical Approximation Methods for Multinomial Probit Model: A Case Study with Passengers’ Rail-Route Choice Analysis in the Tokyo Metropolitan Area. Presented at 20th International Conference of Hong Kong Society for Transportation Studies, Hong Kong, Dec. 2015.