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Title:

How to Increase Rail Ridership in Maryland? Direct Ridership Models (DRM) for Policy Guidance
Cover of How to Increase Rail Ridership in Maryland? Direct Ridership Models (DRM) for Policy Guidance

Accession Number:

01519182

Record Type:

Component

Availability:

Transportation Research Board Business Office

500 Fifth Street, NW
Washington, DC 20001 United States

Abstract:

The state of Maryland aims to double its transit ridership by the end of 2020. The Maryland Statewide Transportation Model (MSTM) has been used to analyze different policy options at a system-wide level. Direct ridership models (DRM) estimate ridership as a function of station environment and transit service features rather than using mode‐choice results from large‐scale traditional models. They have been particularly favored for estimating the benefits of smart growth policies such as Transit Oriented Development (TOD) on transit ridership and can be used as complementary to the traditional four-step models for analyzing smart growth scenarios at a local level and can provide valuable information that a system level analysis cannot provide. In this study, we developed DRMs of rail transit stations, namely light rail, commuter rail, Baltimore metro, and Washington D.C. metro for the state of Maryland. Data for 117 rail stations were gathered from a variety of sources and categorized by transit service characteristics, station built environment features and social-demographic variables. The results suggest that impacts of built environment show differences for light rail and commuter rail. For light rail stations, employment at half-mile buffer areas, service level, feeder bus connectivity, station distance to the CBD, distance to the nearest station, and terminal stations are significant factors affecting ridership. For commuter rail stations only feeder bus connection is found to be significant. The policy implications of the results are discussed.

Supplemental Notes:

This paper was sponsored by TRB committee ADA10(2) Statewide Travel Demand Forecasting.

Monograph Accession #:

01503729

Report/Paper Numbers:

14-3417

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Liu, Chao
Erdogan, Sevgi
Ma, Ting
Ducca, Frederick W

Pagination:

17p

Publication Date:

2014

Conference:

Transportation Research Board 93rd Annual Meeting

Location: Washington DC
Date: 2014-1-12 to 2014-1-16
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Maps; References; Tables

Subject Areas:

Planning and Forecasting; Public Transportation; Terminals and Facilities; I72: Traffic and Transport Planning

Source Data:

Transportation Research Board Annual Meeting 2014 Paper #14-3417

Files:

PRP, TRIS, TRB, ATRI

Created Date:

Jan 27 2014 3:11PM