01629492

Component

https://doi.org/10.3141/2668-07

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.

01646167

17-03038

English

pp 60–77

2017

Transportation Research Record: Journal of the Transportation Research Board

9780309441643

Digital/other

Figures (2) ; References (17) ; Tables (5)

Forecasting; Metropolitan areas; Railroad transportation; Travel demand; Urban transportation

Tokyo (Japan)

Planning and Forecasting; Public Transportation; Railroads

PRP, TRIS, TRB, ATRI

Dec 8 2016 11:08AM

• Conceptual Framework for Understanding Latent Demand: Accounting for Unrealized Activities and Travel
• Estimating Household Travel Energy Consumption in Conjunction with a Travel Demand Forecasting Model
• Identification of Representative Patterns of Time Use Activity Through Fuzzy C-Means Clustering
• Incorporating Land Use into Methods of Synthetic Population Generation and of Transfer of Behavioral Data
• Multimodal Trip Generation Model to Assess Travel Impacts of Urban Developments in the District of Columbia
• Peer-to-Peer Ridesharing with Ride-Back on High-Occupancy-Vehicle Lanes: Toward a Practical Alternative Mode for Daily Commuting
• Who is Picking Up the Child from Day Care? Understanding the Intrahousehold Dynamics in Drop-Off and Pickup Allocation for Households with Dependent Children