Author(s)

F. Tillema, K.M. van Zuilekom & M. F.A.M. van Maarseveen

Abstract

Modelling the number of trips produced by the inhabitants of a zone, the trip generation, is complex and highly dependent on the quality and availability of data. It seems almost impossible to model/forecast the number of trips a person makes without adequate amounts of data. Transportation engineers are commonly faced with a question that is related to this topic; how to perform reliable trip generation with scarce and expensive field data. It is therefore interesting to find the method that gives the best results with the smallest data sets. This paper deals with trip generation and explores the performance of neural networks and commonly used regression models. This research tries to answer the question whether neural networks can out-perform traditional regression metho

Keywords