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

Klaas Dählmann (), Martina Jahns (), Nadine Pieper () and Jürgen Sauer ()
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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

A chapter in Progress in Sustainable Mobility Research, 2021, pp 53-78 from Springer

Abstract: 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.

Keywords: Agent-based simulation; Empirical data; Fuzzy inference; Ridesharing; Travel mode choice (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prochp:978-3-030-70841-2_4

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DOI: 10.1007/978-3-030-70841-2_4

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