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.

The Maryland-Washington, DC region has been experiencing significant land-use changes and changes in local and regional travel patterns due to increasing growth and sprawl. The region's highway and transit networks regularly experience severe congestion levels. Before proceeding with plans to build new transportation infrastructure to address this expanding demand for travel, a critical question is how future land use will affect the regional transportation system. This article investigates how an integrated land-use and transportation model can address this question. A base year and two horizon-year land use-transport scenarios are analyzed. The horizon-year scenarios are: (1) business as usual (BAU) and (2) high gasoline prices (HGP). The scenarios developed through the land-use model are derived from a three-stage top-down approach: (a) at the state level, (b) at the county level, and (c) at the statewide modeling zone (SMZ) level that reflects economic impacts on the region. The transportation model, the Maryland Statewide Transport Model (MSTM), is an integrated land use-transportation model, capable of reflecting development and travel patterns in the region. The model includes all of Maryland, Washington, DC, and Delaware, and portions of southern Pennsylvania, northern Virginia, New Jersey, and West Virginia. The neighboring states are included to reflect the entering, exiting, and through trips in the region. The MSTM is a four-step travel-demand model with input provided by the alternative land-use scenarios, designed to produce link-level assignment results for four daily time periods, nineteen trip purposes, and eleven modes of travel. This article presents preliminary results of the land use-transportation model. The long-distance passenger and commodity-travel models are at the development stage and are not included in the results. The analyses of the land use-transport scenarios reveal insights to the region's travel patterns in terms of the congestion level and the shift of travel as per land-use changes. The model is a useful tool for analyzing future land-use and transportation impacts in the region.

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