A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Using repeated cross-sectional travel surveys to enhance forecasting robustness: Accounting for changing mode preferences
Highlights Use of multiple repeated cross sectional datasets to increase forecasting capacity. Evolution of mode choice preference structures over time and temporal transferability of mode choice models. Heteroscedastic Generalized Extreme Value model.
Abstract Transportation system capacity and performance, urban form and socio-demographics define the influences and constraints conditioning the preferences of urban residents for different transport modes. Changes in characteristics of urban areas are likely to lead to changes in preferences for alternative modes of transport over time; as a consequence, statistical models to forecast mode choice need to be sensitive to both purposeful changes to urban systems as well as exogenous shocks. We make use of the 1996, 2001 and 2006 household surveys conducted in the Greater Toronto and Hamilton Area to study mode preference evolution and model forecasting performance. These repeated cross-sectional household surveys provide an opportunity to investigate aggregate structural changes in commuting mode preferences over time, in a manner sensitive to changes in the urban area. We focus on commuting mode choices because these trips are prime determinants of peak period congestion and peak spreading. We then address how to combine the three cross-sections econometrically in a robust way that allows for use of a single mode choice model across the entire period. Using independent data from 2012, we are able to compare the individual year and combined models in terms of forecasting performance to demonstrate the combined model’s more robust forecasting performance into the future.
Using repeated cross-sectional travel surveys to enhance forecasting robustness: Accounting for changing mode preferences
Highlights Use of multiple repeated cross sectional datasets to increase forecasting capacity. Evolution of mode choice preference structures over time and temporal transferability of mode choice models. Heteroscedastic Generalized Extreme Value model.
Abstract Transportation system capacity and performance, urban form and socio-demographics define the influences and constraints conditioning the preferences of urban residents for different transport modes. Changes in characteristics of urban areas are likely to lead to changes in preferences for alternative modes of transport over time; as a consequence, statistical models to forecast mode choice need to be sensitive to both purposeful changes to urban systems as well as exogenous shocks. We make use of the 1996, 2001 and 2006 household surveys conducted in the Greater Toronto and Hamilton Area to study mode preference evolution and model forecasting performance. These repeated cross-sectional household surveys provide an opportunity to investigate aggregate structural changes in commuting mode preferences over time, in a manner sensitive to changes in the urban area. We focus on commuting mode choices because these trips are prime determinants of peak period congestion and peak spreading. We then address how to combine the three cross-sections econometrically in a robust way that allows for use of a single mode choice model across the entire period. Using independent data from 2012, we are able to compare the individual year and combined models in terms of forecasting performance to demonstrate the combined model’s more robust forecasting performance into the future.
Using repeated cross-sectional travel surveys to enhance forecasting robustness: Accounting for changing mode preferences
Habib, Khandker M. Nurul (author) / Swait, Joffre (author) / Salem, Sarah (author)
Transportation Research Part A: Policy and Practice ; 67 ; 110-126
2014-06-11
17 pages
Article (Journal)
Electronic Resource
English
Development of Travel Demand Models Using Repeated Cross-sectional Data
| British Library Online Contents | 1995