Problem 1: Application of a growth-factor model for forecasting (15) Compute the inter-zonal trip distribution for the forecast year. Be sure to perform the row and column factoring to match the row and column totals of your trip distribution matrix against the predicted productions and attractions. You can stop after two iterations (i.e., one column factoring and one row factoring iteration). For computing future trip prediction, assume the following trip generation equations: 1.5+2.5*(household size) Number of trips produced by a household Number of trips attracted to a zone 1.45 (number of jobs in the zone) +1.3 * (total population/100), make necessary corrections if total productions and total attractions do not match. The socio-economic predictions have been made for the study region for the forecast year (Table 1). The base-year inter-zonal trip interchange matrix is also provided in Table 2. Table 1. Socio-economic forecasts Number of Zone households Average household size Number of jobs 1 200 2.375 827 2 270 1.842 1138 3 375 1.73 1110 4 275 2.16 1241 5 260 2.52 1069 Table 2. Base year inter-zonal trip interchange (flow) matrix Tij 1 2 3 فيا 4 5 Pi 1 250 125 375 75 150 975 2 100 400 50 225 200 975 3 225 420 350 1260 4 155 215 320 175 400 1265 5 190 300 300 450 150 1390 Aj 900 1100 1270 1345 1250 5865 Compute the trip interchange/distribution for the forecast year using the average growth factor approach. Perform two iterations.

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Problem 1: Application of a growth-factor model for forecasting (15) Compute the inter-zonal trip distribution for the forecast year. Be sure to perform the row and column factoring to match the row and column totals of your trip distribution matrix against the predicted productions and attractions. You can stop after