TRB 2016 Blue Ribbon Committee
16th National Transportation Planning Applications Conference

Identifying High Capacity Transit Corridors with the Emergent Network Modeling Framework


Corresponding Author: Dan Tischler, San Francisco County Transportation Authority

Presented By: Dan Tischler, San Francisco County Transportation Authority

Abstract

Travel models are valuable tools for evaluating the potential impacts of transportation policies or projects, but only when you already know what changes you want to test. How can transportation planners use travel demand models to identify promising, but not yet proposed, transit projects? This presentation shares San Francisco’s new approach, the emergent network modeling framework, for identifying future high demand corridors.

San Francisco is a growing city with current and future needs for high capacity rapid transit. Between 2010 and 2015 San Francisco added over 60,000 residents and 125,000 jobs, increases of 7% and over 20% respectively. Regional forecasts anticipate another 200,000 people and commensurate employment growth by 2040. Meanwhile, local and regional transit operators, which already accommodate over one million daily transit boardings, are experiencing rapid ridership growth leading to crush loads on buses and trains.

The San Francisco County Transportation Authority (SFCTA) is coordinating with other San Francisco city agencies to develop a Subway Vision for new grade-separated transit corridors. This Subway Vision will identify high potential corridors for future transit investments that would best address forecasted transportation demand.

The SFCTA is using the SF-CHAMP activity-based model to support Subway Vision corridor identification. Typically, SF-CHAMP-based forecasting requires detailed assumptions about corridors alignments, station location, service frequency, capacity, and other details as input assumptions for a model scenario. However, in this case the Subway Vision project team desired to use the model to identify potential corridors rather than predefining them.

Since existing SFCTA modeling practices did not adequately support the needs for this study, the project team developed the emergent network modeling framework. This framework uses an abstracted and ubiquitous subway network in lieu of detailed transit supply assumptions and allows high demand desire lines to emerge from model outputs. Application of this approach provided valuable insights that supported subsequent network development for the Subway Vision effort.

This presentation will explain the emergent network modeling framework and how San Francisco used it as an important tool in developing San Francisco’s Subway Vision.

Presentation

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