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Prof. Dr. Stefanie Schmidtner

Sustainable Urban Development and Artificial Intelligence

Information

Vita

  • Since 02/2021 at THI
  • 11/2018 - 01/2021: Data Scientist and project lead in the pre-development of smart mobility at Audi AG (Audi Electronics Venture GmbH and Cariad SE)
  • 08/2017 - 10/2018: Data scientist and functions developer at Audi AG
  • 05 - 08/2015: Research stay at Nanyang Technological University, Singapore
  • 10/2012 - 07/2017: Research Scientist and PhD candidate at Susanne Klatten endowed chair for empirical educational research at Technische Universität München, Munich
  • 2007 – 2012: Studies of Mathematics and Physics (secondary education) at Technische Universität München, Munich
E-Mail
Stefanie.Schmidtner@thi.de
Phone
+49 841 9348-3814
Room
K201
Subject Area
Sustainable Urban Development and Artificial Intelligence

Research

Research

Research focus:

  • Sustainable and intelligent mobility systems
  • Data Science & Machine Learning in mobility systems
  • Reinforcement Learning in mobility systems

in research institutes AImotion Bavaria and AININ.

Git Repository

  • Statistics: Lecture and Exercises (Bachelor)
  • AI Applications in Mobility (Bachelor)
  • Introduction to Statistical Learning (Bachelor)
  • Data Science and AI for Intelligent and Sustainable Mobility Systems (Master)
  • Smart Mobility: Trends in Intelligent and Sustainable Mobility Systems (Master)
  • Data Engineering and Analytics (Master)
  • Applied Scientific Work (Master)

Sustainable Urban Development and Artificial Intelligence

The research group for Sustainable Urban Development and Artificial Intelligence focuses on data science and AI applications for intelligent and sustainable mobility systems. The aim of the research group is to combine research on data analysis and machine learning with research on mobility and transport as well as new mobility concepts, and to promote sustainable, intelligent, user-centered, and evidence-based urban development through application-oriented research. Both statistical and machine/deep learning-based methods are used for this purpose.

Our research fields:

  • Application of Data Science and AI in intelligent and sustainable mobility systems
  • Intelligent traffic control and coordination of different modes of transportation
  • AI based evaluation of mobility needs and design mobility solutions
  • Interaction between automated driving and infrastructure/traffic control

Research projects

Members of the research group

Publications

Publications

2026

SCHLAMP, Anna-Lena, Jeremias GERNER, Klaus BOGENBERGER, Werner HUBER und Stefanie SCHMIDTNER, 2026. ROSA: Roundabout Optimized Speed Advisory with Multi-Agent Trajectory Prediction in Multimodal Traffic [Preprint]. arXiv. Available at: https://doi.org/10.48550/arXiv.2602.14780
HORN, Alexander, Philip-Roman ADAM und Stefanie SCHMIDTNER, 2026. A Benchmark Dataset for Bus Travel and Dwell Time Prediction. 2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC). Piscataway: IEEE, Page 2047-2054. ISBN 979-8-3315-2418-0. Available at: https://doi.org/10.1109/ITSC60802.2025.11423733
SCHLAMP, Anna-Lena, Jeremias GERNER, Klaus BOGENBERGER, Werner HUBER und Stefanie SCHMIDTNER, 2026. ROSA: Roundabout Optimized Speed Advisory with Multi-Agent Trajectory Prediction in Multimodal Traffic. 2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC). Piscataway: IEEE, Page 726-733. ISBN 979-8-3315-2418-0. Available at: https://doi.org/10.1109/ITSC60802.2025.11423540

2025

ZHANG, Yunfei, Jeremias GERNER, Mario ILIC, Stefanie SCHMIDTNER und Klaus BOGENBERGER, 2025. Autonomous Vehicles as Sensors: Traffic State Estimation. 104th Annual Meeting of the Transportation Research Board (TRB). Washington: National Academy of Sciences.
ROLLWAGEN, Alice, Alexander HORN, Stefanie SCHMIDTNER und Andreas RIENER, 2025. Communicating Uncertainty in Arrival Time Predictions for Public Transport: A Comparison of Point and Interval Forecasts. MuC´25: Proceedings of the 2025 Conference on Mensch und Computer. New York: ACM, Page 515-519. ISBN 979-8-4007-1582-2. Available at: https://doi.org/10.1145/3743049.3748542
BIALDYGA, Maximilian, Andreas EICH, Christian FACCHI, Andreas FESTAG, Nicole HINTERBERGER, Abhishek Dinkar JAGTAP, Frank LEHMANN, Stefan SCHIESSER, Anna-Lena SCHLAMP, Stefanie SCHMIDTNER und Rui SONG, 2025. Abschlussbericht zum Projekt 5GoIng – 5G-Innovationskonzept Ingolstadt. Hannover: TIB. Available at: https://doi.org/10.34657/22341

2024

SCHLAMP, Anna-Lena, Jeremias GERNER, Klaus BOGENBERGER und Stefanie SCHMIDTNER, 2024. User-Centric Green Light Optimized Speed Advisory with Reinforcement Learning. 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC). Piscataway: IEEE, Page 3463-3470. ISBN 979-8-3503-9946-2. Available at: https://doi.org/10.1109/ITSC57777.2023.10422501
GERNER, Jeremias, Dominik RÖSSLE, Daniel CREMERS, Klaus BOGENBERGER, Torsten SCHÖN und Stefanie SCHMIDTNER, 2024. Enhancing Realistic Floating Car Observers in Microscopic Traffic Simulation. 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC). Piscataway: IEEE, Page 2396-2403. ISBN 979-8-3503-9946-2. Available at: https://doi.org/10.1109/ITSC57777.2023.10422398
RÖSSLE, Dominik, Jeremias GERNER, Klaus BOGENBERGER, Daniel CREMERS, Stefanie SCHMIDTNER und Torsten SCHÖN, 2024. Unlocking Past Information: Temporal Embeddings in Cooperative Bird’s Eye View Prediction [Preprint]. arXiv. Available at: https://doi.org/10.48550/arXiv.2401.14325
MEESS, Henri, Jeremias GERNER, Daniel HEIN, Stefanie SCHMIDTNER, Gordon ELGER und Klaus BOGENBERGER, 2024. First steps towards real-world traffic signal control optimisation by reinforcement learning. Journal of Simulation, 18(6), 957-972. ISSN 1747-7778. Available at: https://doi.org/10.1080/17477778.2024.2364715
GERNER, Jeremias, Klaus BOGENBERGER und Stefanie SCHMIDTNER, 2024. Temporal Enhanced Floating Car Observers. 2024 IEEE Intelligent Vehicles Symposium (IV). Piscataway: IEEE, Page 1035-1040. ISBN 979-8-3503-4881-1. Available at: https://doi.org/10.1109/IV55156.2024.10588538
GERNER, Jeremias, Klaus BOGENBERGER und Stefanie SCHMIDTNER, 2024. Investigating Floating Car Observers for Traffic State Estimation through Co-Simulation. MFTS: The 5th Symposium on Management of Future Motorway and Urban Traffic System 2024. Haifa: Technion.

2022

MEESS, Henri, Jeremias GERNER, Daniel HEIN, Stefanie SCHMIDTNER und Gordon ELGER, 2022. Reinforcement Learning for Traffic Signal Control Optimization: A Concept for Real-World Implementation. AAMAS '22: Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems. Richland: International Foundation for Autonomous Agents and Multiagent Systems, Page 1699-1701. ISBN 978-1-4503-9213-6. Available at: https://dl.acm.org/doi/10.5555/3535850.3536081
MEESS, Henri, Jeremias GERNER, Daniel HEIN, Stefanie SCHMIDTNER und Gordon ELGER, 2022. Real World Traffic Optimization by Reinforcement Learning: A Concept. In: KIEU, Minh Le, Koen H. van DAM, Jason THOMPSON, Nick MALLESON, Alison HEPPENSTALL und Jiaqi GE, Editors International Workshop on Agent-Based Modelling of Urban Systems (ABMUS) Proceedings: 2022. [s. l.]: figshare, Page 49-54. Available at: https://doi.org/10.6084/m9.figshare.19733800.v1
MEESS, Henri, Jeremias GERNER, Daniel HEIN, Stefanie SCHMIDTNER und Gordon ELGER, 2022. Reinforcement Learning for Traffic Signal Control Optimization: A Concept for Real-World Implementation. AAMAS '22: Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems. Richland: International Foundation for Autonomous Agents and Multiagent Systems, Page 1699-1701. ISBN 978-1-4503-9213-6. Available at: https://dl.acm.org/doi/10.5555/3535850.3536081
  • Rotary Research Award 2023 of the Rotary Club Ingolstadt
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