URBAN COMMERCIAL TRANSPORT DEMAND MODELS - INCREASING THEIR POLICY SENSITIVITY BY LINKING THEM WITH SYSTEM DYNAMICS
Benjamin Dahmen, University of Wuppertal, Institute for Freight Transport Planning and Logistics, Bert Leerkamp, University of Wuppertal, Institute for Freight Transport Planning and Logistics
Urban commercial transport demand models only partially satisfy the requirements of urban transport planning. Linking them with System Dynamics can be seen as a promising approach to increase their policy sensitivity.
An increase of urban commercial transport (UCT) is anticipated in the next years. This development is driven, inter alia, by growing e-commerce and the advent of new logistics concepts (e.g. same-day and multi-channel-delivery). This growth of urban transport will further challenge municipalities, esp. those with a growing population. This increases the demand for new tools to analyse and forecast this development.
Overarching goals, like the complete decarbonisation of UCT till 2030 which is postulated by the European Union, will further increase pressure on municipalities to act. They have to propose actions plans and policy measures and must proof their effectiveness with legally backed model calculations. Hence, municipalities have to rely on the application of sophisticated UCT demand models.
UCT demand models are still far away from being as mature as passenger transport demand models and they meet their requirements only partially. The assessment of many policy measures, e.g. from the topics “regulatory policy”, “fiscal policy” and “business operations”, is only possible to a limited extend.
The cause of this problem is a lack of information regarding the effects of policy measures and the adaptive behaviour of the transport sector. Besides, most measures take effect over a certain period of time and often lead to undesired side-effects (e.g. time access restrictions can lead to an increase of total commercial transport). The compilation of all possible impacts and counter-effects of policy measures and their integration into UCT demand models would be desirably. This can be seen as a promising approach to increase the policy sensitivity of UCT demand models.
System dynamics (SD) is a modelling method which is perfectly suited for mapping complex systems. Its strength lies in the modelling of cause-effect chains that are characterised by multiple feedback loops. SD is therefore the ideal modelling framework to map the impacts and feedbacks of policy measures over time.
The aforementioned approach is pursued within the framework of a current research project, funded by the German Research Foundation (DFG). Selected policy measures and their cause-effect chains are mapped as SD-models. These SD-models will then be linked with a practical macroscopic, urban commercial transport demand model (KWM, developed by Ingenieurgruppe IVV GmbH Aachen, Germany). Aim of the research project is the demonstration of feasibility and advantageousness of this approach.
The paper will discuss the approach outlined above. The general concept is discussed and interim results are presented as examples. In this context, selected cause-effect chains of policy measures and their implementation as a SD-model are shown. In addition, the influence on the approach on the policy sensitivity of the KWM is discussed.
Association for European Transport