Modelling Stability in Travel Behaviour

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Travel demand models are an indispensable tool for the assessment of transport facilities or policies in transport planning. The analysis period of common travel demand models is typically one day. Travel behavior research, however, has found that multi-day surveys are necessary to observe certain characteristics of travel. An observation period of one day is typically too short to observe variability and stability in travel behavior. In the case of mode choice, stability can be identified with a monomodal travel behavior, while variability can be identified with a multimodal travel behavior. For transport planning this insight is important since it can be assumed that a monomodal person (high stability in mode choice) reacts differently than a multimodal person (high variability in mode choice) to a change in travel supply. For example a person who always uses the car will probably be less affected by an improvement in public transport than a person who occasionally uses public transport. The project aims at improving the realism of travel demand models by incorporation stability in destination choice and mode choice behavior. For this purpose several approaches to model stability in destination choice and mode choice will be examined. The resulting models will be tested in a microscopic travel demand simulation. Based on indicators describing stability in travel behavior, the results of the different models will be compared with each other and with the data of the German Mobility Panel and a regional household travel survey. The comparison based on these indicators allows assessing the performance of the individual models in regard to reproducing stability in travel behavior. Suitable indicators to describe stability in travel behavior will be identified and developed within the scope of this project. The result of the project will be the insight how realism of travel demand models can be improved by incorporating stability in the destination choice and mode choice behavior. It can be expected that the improved reproduction of stability in travel behavior also improves the quality of the forecasts made by these models.