Martin Sommer, M. Sc.

Martin Sommer, M. Sc.

  • Engesserstr. 5

    76131 Karlsruhe

M. Sc. Martin Sommer


  • Studium Wirtschaftsingenieurwesen (2011-2018)
  • Mitarbeiter am ITIV seit September 2018


Betreuung des Praktikums Informationstechnik I
Betreuung der Vorlesung Projektmanagement in der Entwicklung von Produkten für sicherheitskritische Anwendungen

Betreute abgeschlossene studentische Arbeiten

  • MA: "Einsatz von Deep Learning Methoden zur Personenzählung
    im öffentlichen Nahverkehr; Use of Deep Learning Methods for People Counting in Public Transport"
  • MA: "Vergleich von Reinforcement Learning und Modellprädiktiver
    Regelung zur Klimaregelung in Elektrobussen; Comparison Between Reinforcement Learning and Model Predictive Control for Climate Control in Electric Buses"
  • MA: "Vorhersage von Störgrößen zur Verbesserung des Wärmemanagements von Elektrofahrzeugen; Predicting Disturbance Variables to Improve Thermal Management of Electric Vehicles"
  • BA: "Modellierung eines Fahrgastraummodells innerhalb einer Modellprädiktiven Klimaregelung für einen Elektrobus; Modelling of a Passenger Compartment Model within a Model Predictive Climate Control System for an Electric Bus;"
  • MA: "Entwicklung und Modellierung einer modellprädiktiven Klimaregelung für einen Elektrobus; Development and Modelling of a Model Prediktive Climate Control System for an Electric Bus;"
  • BA: "Knowledge Discovery in Databases: Entwicklung eines Algorithmus zur Berechnung  von Passagieraufkommen; Knowledge Discovery in Databases: Development of an Algorithm to Calculate Ridership Data"
  • MA: "A Distributed Platform Approach to Cooperative Perception Based on Cellular-V2X Communication"
  • MA: "A Reinforcement Learning Approach for Optimal Air Conditioning Control; Ein Ansatz des bestärkenden Lernens für eine optimale Klimaregelung;"


Multi-layer Approach for Energy Consumption Optimization in Electric Buses
Rösch, T.; Raghuraman, S.; Sommer, M.; Junk, C.; Baumann, D.; Sax, E.
2023. 2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring), 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/VTC2023-Spring57618.2023.10199518
Ontology for Vehicle Function Distribution
Ruhnau, J.; Sommer, M.; Henle, J.; Walz, A.; Becker, S.; Sax, E.
2023. 2023 IEEE International Systems Conference (SysCon), Vancouver, Canada, 17-20 April 2023, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SysCon53073.2023.10131097
Fleet data used for self-learning functions in commercial vehicles
Sommer, M.; Rösch, T.; Sax, E.
2023. 17th International Conference Commercial Vehicles 2023, 81–91, VDI Verlag
Adaptive application development and integration process for modern automotive software
Rösch, T.; Sommer, M.; Sax, E.
2022. ICCTA ’22: Proceedings of the 2022 8th International Conference on Computer Technology Applications, 85–90, Association for Computing Machinery (ACM). doi:10.1145/3543712.3543718
Use of Deep Learning Methods for People Counting in Public Transport
Baumann, D.; Sommer, M.; Schrempp, Y.; Sax, E.
2022. 2022 International Conference on Connected Vehicle and Expo (ICCVE), Lakeland, FL, March 7-9, 2022, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICCVE52871.2022.9742924
Automated and networked city buses – Optimized, demand-oriented service through intelligent use of data
Rossel, N.; Sommer, M.; Sax, E.
2021. GmbH, VDI Wissensforum (Hrsg.), Commercial Vehicles 2021 : truck, bus, van, trailor : 16th International Conference, September 7 - 8, 2021, Linz, Austria, 215–228, VDI Verlag. doi:10.51202/9783181023808-215
Model Predictive HVAC Control with disturbance variable forecasting for city buses
Sommer, M.; Sax, E.; Rösch, T.
2021. 2021 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) Mauritius, Mauritius, 7-8 Oct. 2021, 1–7, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICECCME52200.2021.9591111
Intelligent Control of HVAC Systems in Electric Buses
Sommer, M.; Junk, C.; Rösch, T.; Sax, E.
2021. Human Interaction, Emerging Technologies and Future Applications IV : Proceedings of the 4th International Conference on Human Interaction and Emerging Technologies: Future Applications (IHIET – AI 2021), April 28-30, 2021, Strasbourg, France. Ed.: T. Ahram, 68–75, Springer International Publishing. doi:10.1007/978-3-030-74009-2_9
Adaptive Customized Forward Collision Warning System Through Driver Monitoring
Stang, M.; Sommer, M.; Baumann, D.; Zijia, Y.; Sax, E.
2020. Proceedings of the Future Technologies Conference (FTC) 2020, Volume 2. Ed.: K. Arai, 757–772, Springer International Publishing. doi:10.1007/978-3-030-63089-8_50
TalkyCars: A Distributed Software Platform for Cooperative Perception among Connected Autonomous Vehicles based on Cellular-V2X Communication
Sommer, M.; Stang, M.; Muetsch. Ferdinand; Sax, E.
2020. IEEE Intelligent Vehicles Symposium, October 19 - November 13, 2020, (Virtual) Las Vegas, NV
Evolutionary Algorithms to Generate Test Cases for Safety and IT-Security in Automotive Systems
Lauber, A.; Sommer, M.; Fuchs, M.; Sax, E.
2020. SYSCON 2020 : the 14th Annual IEEE International Systems Conference : August 24-27, 2020, virtual conference : 2020 conference proceedings, Art.Nr. 09275836, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SysCon47679.2020.9275836
FEEDI - A Smart Wearable Foot-Band for Navigation and Guidance Using Haptic Feedback
Stock, S.; Bertemes, A.; Stang, M.; Böhme, M.; Grimm, D.; Stork, W.
2020. Human Interaction, Emerging Technologies and Future Applications II : Proceedings of the 2nd International Conference on Human Interaction and Emerging Technologies: Future Applications (IHIET – AI 2020), April 23-25, 2020, Lausanne, Switzerland. Ed.: T. Ahram, 349–355, Springer. doi:10.1007/978-3-030-44267-5_52
Using Machine Learning to Optimize Energy Consumption of HVAC Systems in Vehicles
Böhme, M.; Lauber, A.; Stang, M.; Pan, L.; Sax, E.
2020. Human Interaction and Emerging Technologies. Ed.: T. Ahram, 706–712, Springer International Publishing. doi:10.1007/978-3-030-25629-6_110
Applied Machine Learning: Reconstruction of Spectral Data for the Classification of Oil-Quality Levels
Stang, M.; Böhme, M.; Sax, E.
2019. 5th International Conference on Research in Engineering, Technology and Science (ICRETS 2019), Lissabon, P, February 3-7, 2019, 1–13, ISRES Publishing