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The complexity of value of travel time for self-driving vehicles – a morphological analysis

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  • Maria Nordström
  • Albin Engholm

Abstract

Understanding the value of travel time for mobility concepts based on self-driving vehicles is crucial to accurately value transport investments and predict future travel patterns. In this paper, we carry out a morphological analysis to illustrate the diversity of mobility concepts based on self-driving vehicles and the complexity of determining the value of travel time for such concepts. We consider four categories of parameters that directly or indirectly impact the value of travel time: (i) vehicle characteristics, (ii) operating principles, (iii) journey characteristics and (iv) traveler characteristics. The parameters and respective attributes result in a morphological matrix that spans all possible solutions. Out of these, we analyze five plausible solutions based on the implications of the concept characteristics on the total value of travel time. We conclude by suggesting an alternative approach to differentiate value of travel time based on travel characteristics rather than the usual decomposition into transport modes.

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  • Maria Nordström & Albin Engholm, 2021. "The complexity of value of travel time for self-driving vehicles – a morphological analysis," Transportation Planning and Technology, Taylor & Francis Journals, vol. 44(4), pages 400-417, May.
    • Handle: RePEc:taf:transp:v:44:y:2021:i:4:p:400-417
    DOI: 10.1080/03081060.2021.1919349
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    Cited by:

    1. Manel Elmsalmi & Wafik Hachicha & Awad M. Aljuaid, 2021. "Modeling Sustainable Risks Mitigation Strategies Using a Morphological Analysis-Based Approach: A Real Case Study," Sustainability, MDPI, vol. 13(21), pages 1-17, November.

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