Activity-Based Travel Demand Forecasting Using Micro-Simulation: Stochastic Error Investigation of FEATHERS Framework

Activity-based models of travel demand employ in most cases a micro-simulation approach, thereby inevitably including a stochastic error that is caused by the statistical distributions of random components. As a result, running a transport micro-simulation model several times with the same input will generate different outputs. In order to take the variation of outputs in each model run into account, a common approach is to run the model multiple times and to use the average value of the results. The question then becomes: What is the minimum number of model runs required to reach a stable result? In this chapter, systematic experiments are carried out by using the FEATHERS, an activity-based micro-simulation modeling framework currently implemented for Flanders (Belgium). Six levels of geographic detail are taken into account, which are building block level, subzone level, zone level, superzone level, province level, and the whole Flanders. Three travel indices (i.e., the average daily number of activities per person, the average daily number of trips per person, and the average daily distance travelled per person), as well as their corresponding segmentations with respect to socio-demographic variables, transport mode alternatives, and activity types are calculated by running the model 100 times. The results show that application of the FEATHERS at a highly aggregated level only requires limited model runs. However, when a more disaggregated level is considered (the degree of the aggregation here not only refers to the Qiong Bao Hasselt University, Belgium Bruno Kochan Hasselt University, Belgium Tom Bellemans Hasselt University, Belgium Davy Janssens Hasselt University, Belgium Geert Wets Hasselt University, Belgium