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From Empirical Data to Operational Models: An Approach for the Development of a Decision-Making Component for an Agent-Based Mobility Simulation from Quantitative Survey Data

In: Progress in Sustainable Mobility Research

Author

Listed:
  • Klaas Dählmann

    (Carl von Ossietzky University of Oldenburg)

  • Martina Jahns

    (Technical University of Braunschweig)

  • Nadine Pieper

    (Technical University of Braunschweig)

  • Jürgen Sauer

    (Carl von Ossietzky University of Oldenburg)

Abstract

This contribution illustrates a holistic approach to determine and implement a decision-making component for an agent-based mobility simulation framework based on empirical data. The decision component uses a generic fuzzy inference concept developed for a flexible simulation framework for mobility scenarios, the variables and rule base of which are acquired from quantitative survey data of 194 participants. Using a minimal example case of ridesharing intention, it is shown how such a survey can be analyzed using structural equation modeling to subsequently derive a decision-making model of relevant, empirically estimated determinants for the subsequent implementation as a fuzzy inference system. The fuzzy inference system is applied in a simulation scenario to compare survey results and simulative behavior. The similar overall results of both survey and simulation regarding the used determinants indicate a general feasibility of the approach.

Suggested Citation

  • Klaas Dählmann & Martina Jahns & Nadine Pieper & Jürgen Sauer, 2021. "From Empirical Data to Operational Models: An Approach for the Development of a Decision-Making Component for an Agent-Based Mobility Simulation from Quantitative Survey Data," Progress in IS, in: Jorge Marx Gómez & Jantje Halberstadt & Anna Henkel & Frank Köster & Jürgen Sauer & Jürgen Taeger & (ed.), Progress in Sustainable Mobility Research, pages 53-78, Springer.
    • Handle: RePEc:spr:prochp:978-3-030-70841-2_4
    DOI: 10.1007/978-3-030-70841-2_4
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