Advanced OR and AI Methods in Transportation COLLECTING ACTIVITY-TRAVEL DIARY DATA BY MEANS OF A HAND-HELD COMPUTER-ASSISTED DATA COLLECTION TOOL Bruno KOCHAN, Davy JANSSENS, Tom BELLEMANS, Geert WETS 1 Abstract. Activity-based transportation models have set the standard for modelling travel demand for the last decade. It seems common practice nowadays to collect the data to estimate these activity-based transportation models by means of activity diaries. This paper explores potential advantages and disadvantages that may occur in the collection of this type of data by means of a hand-held computer-assisted data collection tool. 1. Introduction The demand for transport services is expected to grow considerably as incomes rise, the trend toward urbanization continues and as the process of globalization moves forward with expected increases in world trade and personal travel. In order to meet this rising demand and because governments cannot afford to allow transport constraints to have a negative impact on the future competitiveness of their products, considerable future long-term investments are indispensable. In order to better guide and substantiate the decisions of transportation planners, the use of traffic and transportation models has been advocated by governments and by research communities. Since 1950, due to the rapid increase in car ownership and car use in the US and in Western Europe; several models of transport mode, route choice and destination were used by transportation planners. These models were necessary to predict travel demand in the long run and to support investment decisions in new road infrastructure which originated from this increased level of car use. In those days, travel was assumed to be the result of four subsequent decisions which were modelled separately. Within transportation literature these models are also referred to as four-step models. More recently, especially in the eighties and early nineties, several researchers claimed that very limited insight was offered into the relationship between travel and non-travel aspects in the widely used four-step 1 Limburgs Universitair Centrum, Transportation Research Institute, Faculty of Applied Economic Sciences, Universitaire Campus Gebouw D, B-3590 Diepenbeek, Belgium, {bruno.kochan;davy.janssens;tom.bellemans;geert.wets}@luc.ac.be