Abstract:
In this work we have studied the selection criteria for traffic analysis zones and the effects of their size and number on the model's forecasting capabilities. To do so we have focused on the corridor of Istanbul's Kadtkoy-Kartal Metro Line and evaluated the consistency of demand forecasts and travel assignments versus actual measurements under different sizes of the Traffic Analysis Zones (TAZ). Significant improvements in model accuracy were observed by decreasing the zone size. Specifically, studying the public transport network assignments for the metro line when increasing the number traffic analysis zones from 540 to 1,788 the root mean square error (RMSE) of forecasted vs. actual station-based counts was reduced by 23%. Subsequently, the study used population density and employment density as independent variables for the determination of the optimal radius for the 1,788 zone area, and applied an exponential regression model. Appropriate model parameters were derived for the above case study. The regression model resulted in R-2 values over 0.62.
