Model complexities and requirements for multimodal transport network design: Assessment of classical, state-of-the-practice, and state-of-the-research models

Model complexities and requirements for multimodal transport network design: Assessment of classical, state-of-the-practice, and state-of-the-research models

Van Eck, G.
Brands, T.
Wismans, L.J.J.
Pel, A.J.
Van Nes, R.

Civil Engineering and Geosciences

Transport & Planning

2014-12-04

In the aim for a more sustainable transport system, governments try to stimulate multimodal trip making by facilitating smooth transfers between modes. The assessment of related multimodal policy measures requires transport models that are capable of handling the complex nature of multimodality. This complexity sets requirements for adequate modeling of multimodal travel behavior and can be categorized into three classes related to the range and combinatorial complexity of the choice set, the mathematical complexity of the choice model, and the complexity in demand-supply interactions. Classical modeling approaches typically fail to meet these requirements while state-of-the-practice approaches only partly fulfill these. Hence, the hypothesis of this study is that application of such models in network design implies an ill decision-making process. Both approaches are therefore compared with the theoretically sound super-network approach. Requirements for multimodality are constructed, and all three models are tested regarding how these requirements can be met. The findings of this comparison are supported by realistic examples in the real-world transport network of the Amsterdam Metropolitan Area. It is shown that the theoretical shortcomings of classical and state-of-the practice approach indeed result in incorrect predictions of multimodal travel behavior. The flexibility of the super-network approach, on the other hand, is capable of describing the expected impact of supply changes on travel behavior. This illustrates the urgency for applying sound multimodal modeling approaches in network design studies.

http://resolver.tudelft.nl/uuid:64eb0b1f-cbd1-4802-93ad-a8ce82c3a9fa

https://doi.org/10.3141/2429-19

Transportation Research Board

0361-1981

Transportation Research Record, 2429, Travel Demand Forecasting 2014, Vol. 1; Authors version

Institutional Repository

conference paper

(c) 2014 The Author(s)
TRB