Forecasting ridership for a metropolitan transit authority

Wen-Chyuan Chiang, Robert A. Russell and Timothy L. Urban

Transportation Research Part A: Policy and Practice, 2011, vol. 45, issue 7, 696-705

Abstract: The recent volatility in gasoline prices and the economic downturn have made the management of public transportation systems particularly challenging. Accurate forecasts of ridership are necessary for the planning and operation of transit services. In this paper, monthly ridership of the Metropolitan Tulsa Transit Authority is analyzed to identify the relevant factors that influence transit use. Alternative forecasting models are also developed and evaluated based on these factors--using regression analysis (with autoregressive error correction), neural networks, and ARIMA models--to predict transit ridership. It is found that a simple combination of these forecasting methodologies yields greater forecast accuracy than the individual models separately. Finally, a scenario analysis is conducted to assess the impact of transit policies on long-term ridership.

Keywords: Public; transit; ridership; Forecasting; models; Scenario; analysis (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (9)

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