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Technical University of Munich

Natalie Steinmetz

Picture of Natalie Steinmetz

M.Sc. Natalie Steinmetz

Research Focus

  • Urban traffic control
  • Automated and connected driving in urban areas

Curriculum Vitae

Work experience
since 2021 Technical University of Munich
Chair of Traffic Engineering and Control
Researcher
2020-2021 Schlothauer & Wauer GmbH
Traffic Engineering, Traffic signal control
Working student and master thesis
2019-2020 Technical University of Munich
Chair of Traffic Engineering and Control
Research assistant
2017-2019 Siemens AG/Siemens Mobility GmbH
Innovative mobility solutions, automated driving
Working student

Education
2021 M.Sc. Civil Engineering
Thesis: Optimized traffic signal control strategies for emergency vehicles based on Vehicle-to-X communication
Fields of Study: Traffic Control and Transport Planning, Computation in Engineering, Road and Railway Construction
Technical University of Munich
2018 B.Sc. Environmental Engineering
Technical University of Munich

Teaching

  • Mentoring and Exercises in the lecture series "Traffic Control Basics" (since WS 2021/22)
  • Lecture "Urban Traffic Control - LISA" for the lecture series "Traffic Control Extension" (since SS 2021)
  • Exercise "Green Wave" in the module "Traffic Engineering and Transport Planning Supplementary Module" (since SS 2021)
  • Exercises in the module "Traffic Engineering and Transport Planning Basic Module" (WS 2021/22)

Publications

  • Kutsch, Alexander; Kessler, Lisa; Steinmetz, Natalie; Bogenberger, Klaus: Dynamic Queue Length Estimation Based on Urban Drone Observations Using Machine Learning Approaches. 103rd Annual Meeting of the Transportation Research Board (TRB), 2024 more…
  • Schmidt, K.J.; Steinmetz, N.; Margreiter, M.: Bus Priority Procedure for Signalized Intersections Based on Bus Occupancy and Delay. SUMO User Conference, 2024 more…
  • Matiunina, Daria; Sautter, Natalie; Loder, Allister; Bogenberger, Klaus: Predicting Parking Occupancy with Deep Learning on Noisy Empirical Data. 2023 8th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), IEEE, 2023 more…
  • Sautter, Natalie; Kessler, Lisa; Belikhov, Danil; Bogenberger, Klaus: A Multimodal Performance Index for the Evaluation of Urban Traffic Control Measures. 2023 8th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), IEEE, 2023 more…
  • Sautter, Natalie; Kessler, Lisa; Belikhov, Danil; Bogenberger, Klaus: Multimodal Performance Evaluation of Urban Traffic Control: A Microscopic Simulation Study. 4th Symposium on Management of Future Motorway and Urban Traffic Systems 2022 (MFTS2022), 2022 more…
  • Ilic, Mario; Sautter, Natalie; Margreiter, Martin; Loder, Allister; Bogenberger, Klaus: Changing Strategic Alignments in European Urban Traffic Control – Requirements for Future Developments. hEART - 10th Symposium of the European Association for Research in Transportation, 2022 more…
  • Ilic, Mario; Sautter, Natalie; Margreiter, Martin; Loder, Allister; Bogenberger, Klaus: Revisiting Urban Traffic Control in Austria, Germany and Switzerland - Requirements for Future Developments. Transportation Research Board - 101st Annual Meeting 2022, 2022 more…
  • Bogenberger, Klaus; Blum, Philipp; Danld, Florian; Hamm, Lisa-Sophie; Loder, Allister; Malcolm, Patrick; Margreiter, Martin; Sautter, Natalie: MobilityCoins - A new currency for the multimodal urban transportation system. arXiv, 2021 more…
  • Ilic, Mario; Sautter, Natalie; Margreiter, Martin; Loder, Allister; Kessler, Lisa; Kutsch, Alexander; Bogenberger, Klaus: Strategien urbaner Verkehrssteuerung in der DACH Region - Anforderungen an künftige Entwicklungen. KIVI Konsortialtreffen, 2021Ingolstadt, Deutschland more…

Supervised Theses

  • Schmidt, Katia: Use of Artificial Intelligence to Calibrate Microscopic Driving Behaviour Models.
    Master Thesis. Start: 19.4.2024; End: 19.10.2024. Mentoring: Stüger, Steinmetz. Abstract.
  • Ahmed, Sameer: State Vector Design for Reinforcement Learning in Traffic Signal Control.
    Master Thesis. Start: 20.1.2024; End: 20.7.2024. Mentoring: Steinmetz, Karalakou. Abstract.
  • Bachir, Hussein: Adaptive traffic signal control with connected vehicle data.
    Master Thesis. Start: 23.10.2023; End: 23.4.2024. Mentoring: Steinmetz, Dr. Rostami. Abstract.
  • Rahman, Md. Atikur: From Single Intersections to Network Traffic State: Ma-chine Learning in Traffic State Estimation.
    Master Thesis. Start: 9.10.2023; End: 9.4.2024. Mentoring: Zhang, Steinmetz. Abstract.
  • Ebbing, Lucas: The latest sensor technology and measurement techniques in connected and automated vehicles.
    Bachelor Thesis. Start: 25.1.2024; End: 16.4.2024. Mentoring: Dr. Rostami, Sautter. Abstract.
  • Schmidt, Katia Juliane: Development of an adaptive bus priority procedure in urban road networks.
    Study Project. Mentoring: Sautter, Margreiter.
  • Sulthana, Parveen: Quality and potential analysis of traffic signal switching time pre-diction based on finite state theory.
    Master Thesis. Start: 14.4.2023; End: 14.10.2023. Mentoring: Dr. Spangler, Sautter. Abstract.
  • Rahman, Md. Manjurur: Demand Generation and Calibration for Microscopic Traffic Simulation using OD Matrices.
    Master Thesis. Start: 27.9.2022; End: 21.4.2023. Mentoring: Sautter, Dr. Kessler. Abstract.
  • Ortgiese, Tobias: Investigation of the switching behaviour of traffic-dependent light signal systems under full load.
    Bachelor Thesis. Start: 1.7.2023; End: 29.12.2023. Mentoring: Steinmetz, Dr. Spangler. Abstract.
  • Yu, Qinghui: Realistic Estimation of Bicycle Traffic Demand for Microscopic Simulations.
    Bachelor Thesis. Start: 8.5.2023; End: 8.10.2023. Mentoring: Dr. Kessler, Steinmetz. Abstract.
  • Zajic, Viktor: Literature review on Reinforcement Learning in Traffic Signal Control.
    Bachelor Thesis. Start: 22.11.2022; End: 8.5.2023. Mentoring: Sautter, Stüger. Abstract.
  • Udris, Tom: Rational Choice in Transportation - Really that Reasonable?.
    Bachelor Thesis. Start: 16.11.2022; End: 16.4.2023. Mentoring: Schönhofer, Sautter. Abstract.
  • Schneider, Jan: Literature review on the potential of Connected Autonomous Vehicles for system optimum routing.
    Bachelor Thesis. Start: 10.11.2022; End: 10.4.2023. Mentoring: Sautter, Dr. Spangler. Abstract.
  • Faizi, Asadullah: Visualization of traffic demand based on inductive loop data.
    Study Project. Mentoring: Sautter, Kutsch.
  • Chan, Cheuk Yin: Microscopic Simulation Studies for the Assessment of Urban Traffic Control based on a Multimodal Performance Index.
    Study Project. Mentoring: Sautter, Dr. Kessler.
  • Hrabia, Nadine: Methodological Prioritization of Road Users in Urban Traffic Control Considering Different Request Types.
    Master Thesis. Start: 16.3.2022; End: 14.9.2022. Mentoring: Margreiter, Sautter. Abstract.
  • Isele, Larissa: Use of microdeposits in parcel logistics and possible contribution to traffic reduction.
    Bachelor Thesis. Start: 20.6.2022; End: 20.11.2022. Mentoring: Fehn, Sautter. Abstract.
  • Steinbach, Jennifer: Literature Review on Multi-intersection Control for Connected Autonomous Vehicles.
    Bachelor Thesis. Start: 15.4.2022; End: 15.9.2022. Mentoring: Sautter, Niels. Abstract.
  • Walter, Daniel: Development of evaluation criteria for existing urban traffic control systems.
    Bachelor Thesis. Start: 9.12.2021; End: 9.5.2022. Mentoring: Sautter, Dr. Kessler. Abstract.
  • Daskalov, Aleks: Literature Review on Methods for Data Fusion and applications for Traffic Engineering and Control.
    Bachelor Thesis. Start: 18.10.2021; End: 18.4.2022. Mentoring: Dr. Spangler, Sautter. Abstract.
  • Kinkela, Corinna: Literature review on the potential impact of different urban traffic control measures.
    Bachelor Thesis. Start: 15.11.2021; End: 15.4.2022. Mentoring: Sautter, Ilic. Abstract.
  • Rahman, Md. Manjurur: Comparative Evaluation of Fixed-Time Traffic Control and Traffic-Actuated Control in a SUMO network using the CROSSIG-SUMO-Interface.
    Study Project. Mentoring: Ilic, Sautter.
  • Sayed, Abu: Developing a regression model for the public transport demand at intersections.
    Study Project. Mentoring: Dr. Loder, Sautter.
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