Sensitivity of Trip Distribution to Subarea Focusing

The expected accuracy of a proposed method for reducing computational costs of urban and regional travel demand forecasting is explored. The technique investigated is a data aggregation approach called subarea focusing. In subarea focusing a subarea of interest in a study region is isolated for analysis. An imaginary boundary (called the window) is drawn around the subarea. Areal data within the window are maintained at a fine (zonal) level of detail while data outside the window are aggregated into districts. Network data are not simplified. The effects of subarea focusing on trip distribution outputs were investigated. Three subareas (Seattle CBD, Tacoma CBD, and the suburban city of Bellevue) and three levels of aggregation were investigated. Both regional and centroid-to-centroid errors were calculated. The error analyses indicate that subarea focusing is a sufficiently accurate technique for conventional demand forecasting.