Publikationen am Fachgebiet

Veröffentlichungen

  • Heckmann, K., Budde, J., Schneegans, L. E.,  Hoyer, R. (2024). "Predicting the Future Signalization of Traffic-Actuated Signals Using Extreme Gradient Boosting". In: Transportation Research Record, https://doi.org/10.1177/03611981241277750

  • Heckmann, K., Schneegans, L.E., Hoyer, R. (2023). "Stage Prediction of Traffic Lights Using Machine Learning". In: Proff, H. (eds) Towards the New Normal in Mobility. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-39438-7_36
  • Schneegans, L.E., Duensing, J., Heckmann, K., Hoyer, R. (2023). "Prediction of Signal Phase and Timing Information: Comparison of Machine Learning Algorithm Performance". In: Proceedings of the 12th International Scientific Conference on Mobility and Transport. Lecture Notes in Mobility. Springer, Singapur. https://doi.org/10.1007/978-981-19-8361-0_16
  • Scheegans, L.E., Heckmann, K., Hoyer, R. (2022). "Exploiting Stage Information for Prediction of Switching Times of Traffic Actuated Signals Using Machine Learning", In: 2022 12th International Conference on Advanced Computer Information Technologies (ACIT), Ruzomberok, Slovakai, 2022, pp. 544-548, https://doi.org/10.1109/ACIT54803.2022.9912747.
  • Heckmann, K., Schneegans, L.E., Hoyer, R. (2022) "Estimating Future Signal States and Switching Times of Traffic Actuated Lights". In: Proceedings of the 20th European Transport Congress and 12th Conference on Transport Sciences, Györ, Ungarn

Poster & Präsentationen

Poster:

  • Heckmann, K., Budde, J., Schneegans, L.E., Hoyer, R. (2024) "Predicting the Future Signalization of Traffic-Actuated Signals Using Extreme Gradient Boosting", Konferenz: 103rd Annual Meeting of the Transport Research Board (TRB), 7.-11. January Washington DC (USA)

Präsentation:

  • Schneegans, L.E. (2022) "Prediction of Signal Phase and Timing Information: Comparison of Machine Learning Algorithm Performance", Konferenz: mobilTUM 2022, 5.-7. April. Singapur, 2022.
  • Schneegans, L.E. (2021) "Estimation of Switching Times of Traffic-Actuadted Traffic Signals - first Results - Verfahrensentwicklung für Schaltzeitprognosen an verkehrsabhängigen Lichtsignalanlagen mit Hilfe maschinellen Lernens", Konferenz: Universitätstagung Verkehr 2021