Quantitative analysis of future scenarios of urban mobility using agent-based simulation – A case study

Abstract

Nowadays, urban mobility is facing many challenges such as efficiency, eco-friendliness, and comfort, for instance. Growing cities and not least the discussion about vehicular emissions and climate change are calling for adequate solutions for the existing problems in urban transport. However, because of many reasons including diverging interests, there is no consensus in politics and society at the moment about what these solutions should finally look like. For this purpose, using the example of the city of Berlin, three different future scenarios of urban mobility were simulated in detail by applying advanced tools for integrated agent-based modelling of traffic demand, traffic flow and vehicle emissions. While the first proposed scenario explicitly focuses on eco-friendliness and sustainability, a second one pursues a primarily economic-liberal concept. The third scenario represents a business-as-usual approach that, in particular, tries to find the balance between environmental, economic and social needs. Based on these scenarios, the effects of different political and societal priorities on urban mobility are then analyzed thoroughly with regard to traffic volumes, modal split, travel times, and CO 2 emissions. As a key result, realistic potentials and limitations of behavioral changes (e.g., mode choice) as well as possible CO 2 reductions based on electric mobility, for instance, are derived.

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