Széchenyi Plan Plus | Government of Hungary. Funded by the European Union. NextGeneration EU.

EN HU
  • Discover
    • News
    • Events
    • Report
  • Research & development
    • Areas of application
    • Research topics
  • Resources
    • Publications
    • Lead researchers
  • Partners
    • Consortium members
    • International partners
    • Industry contacts
    • University contacts
  1. Home
  2. Publications
2022 IEEE 16th International Symposium on Applied Computational Intelligence and Informatics (SACI) / 25-28 May 2022

MILP-Based Optimization of the Extended Real-Time Railway Traffic Management Problem

The conflict-free preplanned railway timetable often results in conflicting trains due to traffic perturbation. Therefore, the real-time railway traffic management problem arises that requires the rerouting and rescheduling of the trains. The optimization aims to minimize the secondary delays assigned to the trains solving the traffic management problem. In this paper, we propose a mixed-integer linear programming model extending the previous works in this field with a safety-relevant signaling concept, the so-called overlaps. The proposed model provides a strategic decision minimizing the delay propagation that is safer and more feasible considering the actual railway traffic regulations. The results are verified through a simulation environment highlighting the impact of overlaps in different infrastructures and scenarios.

Url
https://doi.org/10.1109/SACI55618.2022.9919542
Authors
Lindenmaier, L.
Aradi, Sz.
Bécsi, T.
Lövétei, I. F.
Institutes

Kapcsolat

Prof. Dr. Péter Gáspár

H-1111 Budapest, Kende u. 13-17.

+36 1 279 6000

autonom@nemzetilabor.hu

© 2020-2023 National Laboratory for Autonomous Systems, Budapest