Perspectives on Sustainable Mobility in Metropolitan Regions: Shaping Mobility Cultures

  • Sven Kesselring
  • Gebhard Wulfhorst
Part of the Studien zur Mobilitäts- und Verkehrsforschung book series (SZMV)


Traditionally, mobility research originates from a transport perspective. However, in today’s metropolitan regions, a dramatic change is being observed in mobility that is driven by technological and social innovation. This change is reflected through the transformation of scientific analysis and real-life policies from a transport perspective to a mobility perspective.

How should we investigate, govern, and manage this change? In this concluding chapter, we present the necessity for the same and some ideas for future research and development. This outlook is based on the experiences of the first phase of the mobil.LAB doctoral research program and articulates questions that need to be addressed in the second phase of this program.

Future research will be based on the understanding of mobility as a cultural phenomenon. We therefore consider the concept of “mobility culture” as a basis on which to highlight strategic directions. Selected state-of-the-art insights, challenges, and options regarding more sustainable mobility in metropolitan regions are presented in the following topics:
  • New mobility concepts: from selling cars to delivering services

  • New mobility practices: from mode split to reflexive action

  • New mobility policies: from transport departments to mobility networks

  • Shaping sustainable mobility cultures: from theory to practice

Our ambition is to share perspectives on relevant issues concerning sustainable mobility in metropolitan regions. We want to contribute toward the exploration, transformation, and realization of the mobility of tomorrow. We look forward to continuing the discussion on our reflections in research and practice.


Mobility Service Metropolitan Region Smart City Transport Policy Autonomous Driving 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Fachmedien Wiesbaden 2016

Authors and Affiliations

  1. 1.GeislingenDeutschland
  2. 2.MünchenDeutschland

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