- Dynamic Queue Length Estimation Based on Urban Drone Observations Using Machine Learning Approaches. 103rd Annual Meeting of the Transportation Research Board (TRB), 2024 more…
- Data Collection and Processing of Multimodal Trajectories Collected by Aerial Drones. 9th International Symposium on Transportation Data & Modelling (ISTDM2023), 2023 more…
- The Munich Large-Scale Drone Data Set Containing Pedestrian, Cyclist, Manually Driven and Automated Vehicle Trajectory. 27th World Road Congress, 2023 more…
- Extended Urban Traffic State Estimation Using Different Sensor Strategies. Annual Meeting of the Transportation Research Board (TRB), 2023 more…
- TEMPUS - Test Field Munich - Pilot Test for Urban Automated Road Traffic. 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), IEEE, 2022 more…
- Traffic State Estimation with Loss Constraint. IEEE International Conference on Intelligent Transportation Systems, 2022 more…
- Strategien urbaner Verkehrssteuerung in der DACH Region - Anforderungen an künftige Entwicklungen. KIVI Konsortialtreffen, 2021Ingolstadt, Deutschland more…
Curriculum Vitae
Work experience | |
| since 2021 | Technical University of Munich Chair of Traffic Engineering and Control Researcher |
| 2019 - 2021 | Landeshauptstadt München Baureferat, Mobilitätsreferat Project manager street planning |
| 2018 - 2019 | Obermeyer Planen+Beraten Traffic Engineering and Control Intership and working student position |
Education | |
| 2020 | M.Sc. Civil Engineering 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 |
Publications
Supervised Theses
- Investigation of Traffic Flow Stabilization Measures by Connected and Automated Vehicles. Study Project. Mentoring: Stüger, Kutsch, Metzger.
- Simulative investigation of measures for shockwave damping on freeways. Master Thesis. Start: 16.5.2023; End: 16.11.2023. Mentoring: Metzger, Stüger, Kutsch. Abstract.
- Application of Physics-Informed Deep Learning for Traf-fic State Estimation. Master Thesis. Start: 15.5.2023; End: 15.11.2023. Mentoring: Kutsch. Abstract.
- Estimation of the Characteristics of Highway Infrastructure Using Drone Data. Master Thesis. Start: 8.5.2023; End: 8.11.2023. Mentoring: Zhang, Kutsch. Abstract.
- Behavioral models of the interaction between non-motorized and motorized road users - focus on automated vehicles. Master Thesis. Start: 1.1.2023; End: 1.8.2023. Mentoring: Kutsch, Stüger, Ilic. Abstract.
- Automatic Detection of Traffic Streams with Machine Vision. Master Thesis. Start: 31.1.2023; End: 31.7.2023. Mentoring: Dr. Spangler, Kutsch. Abstract.
- Visualization of traffic demand based on inductive loop data. Study Project. Mentoring: Sautter, Kutsch.
- Development and Application of an Evaluation Tool for Data Quality Assessment of different Sensor Systems. Master Thesis. Start: 15.5.2022; End: 24.10.2022. Mentoring: Ilic, Kutsch. Abstract.
- Bottleneck identification with machine learning using large-scale drone data. Master Thesis. Start: 18.10.2021; End: 25.4.2022. Mentoring: , Kutsch. Abstract.
- Calibration of microscopic traffic simulations in „Aimsun Next“ with a focus on connected and automated vehicles. Bachelor Thesis. Start: 17.6.2022; End: 24.11.2022. Mentoring: Stüger, Kutsch. Abstract.
- Expert interviews and user survey on the sustainable design of passenger transport as well as urban logistics by means of transport bicycles. Bachelor Thesis. Start: 15.11.2021; End: 15.4.2022. Mentoring: Fehn, Kutsch. Abstract.
- Literature review on positive and negative impacts of vehicle platooning. Bachelor Thesis. Start: 20.9.2021; End: 1.2.2022. Mentoring: Kutsch, Margreiter. Abstract.