Beschreibung
TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. Founded in 1828, today it is a globally oriented, regionally anchored top university as it focuses on the grand challenges of the 21st century. It develops innovative solutions for the world's most pressing issues. TUD has established the Research Training Group "AirMetro - Technological & Operational Integration of Highly Automated Air Transport in Ur...
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TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. Founded in 1828, today it is a globally oriented, regionally anchored top university as it focuses on the grand challenges of the 21st century. It develops innovative solutions for the world's most pressing issues. TUD has established the Research Training Group "AirMetro - Technological & Operational Integration of Highly Automated Air Transport in Urban Areas" (RTG 2947), funded by the German Research Foundation (DFG). This interdisciplinary group, involving five faculties and the German Aerospace Centre (DLR), will conduct research on 11 research topics. The goal is to address the technical and social challenges of Innovative Air Mobility (IAM), considering ecological, economic, technological, and sociological factors. The RTG's structured PhD program aims to train young researchers in highly automated, networked mobility, featuring international collaboration with mentors from the USA, Asia, and Europe. TUD and the RTG embody a university culture that is characterized by cosmopolitanism, mutual appreciation, thriving innovation and active participation. For TUD diversity is an essential feature and a quality criterion of an excellent university. Accordingly, we welcome all applicants who would like to commit themselves, their achievements and productivity to the success of the whole institution.
The Research Training Group RTG 2947 "AirMetro", funded by the DFG, offers a position, as
Research Associate / PhD Student (m/f/x)
(subject to personal qualification employees are remunerated according to salary group E 13 TV-L)
starting May 1, 2026. The position is limited until April 30, 2029. The period of employment is governed by the Fixed Term Research Contracts Act (Wissenschaftszeitvertragsgesetz - WissZeitVG). The position aims at obtaining further academic qualification (usually PhD).
Job ID: RTG2947-T-11/2
Title: System-Level Impact Analysis of IAM using Agent-Based Models
Supervisor: Prof. Dr. Regine Gerike, Chair of Mobility System Planning and co-supervised by at least one additional professor plus an international tutor of the RTG
Description of the PhD topic:
The introduction of urban and regional Innovative Air Mobility (IAM) services will both affect and be affected by existing transport modes, requiring a system-level analysis to understand network-wide impacts. In passenger transport, IAM is expected to become attractive particularly for medium to long trip distances, where time savings on the main trip leg outweigh access and egress times. The introduction of such services therefore has the potential to alter mode choice, destination choice, and overall travel behavior.
This PhD project examines the impact of IAM services on travel behavior using agent-based transport simulation. The doctoral researcher will initially work collaboratively with first-cohort researchers on IAM-related extensions within the MATSim framework.
The core focus of the project is the gradual expansion of behavioral choice dimensions in agent-based models. Beyond mode choice, the research explicitly incorporates destination choice, allowing agents to flexibly select activity locations such as shopping or leisure. This enables the analysis of both mode shifts from existing transport systems and demand induced by new travel opportunities created by IAM.
The overarching aim is to distinguish between IAM demand resulting from shifts from existing transport modes and demand that is induced by changes in travel behavior. Empirical data will be used to support the development and parameterization of the agent-based model, enabling a more realistic representation of IAM travel behavior and its interaction with existing transportation systems. Objectives:
collaborate with first-cohort researchers to further develop and apply IAM-related simulations within the MATSim framework
extend agent-...