@article{Pfaff2017,
  author    = {Pfaff, Raphael},
  title     = {Apps f{\"u}r den G{\"u}terwagen? Wie der G{\"u}terwagen 4.0 die effiziente Integration der G{\"u}terbahn in ERTMS erm{\"o}glicht},
  series = {Ingenieurspiegel},
  journal   = {Ingenieurspiegel},
  number    = {2},
  pages     = {1 -- 2},
  year      = {2017},
  language  = {de}
}
@article{Pfaff2023,
  author    = {Pfaff, Raphael},
  title     = {Braking distance prediction for vehicle consist in low-speed on-sight operation: a Monte Carlo approach},
  series = {Railway Engineering Science},
  volume    = {31},
  journal   = {Railway Engineering Science},
  number    = {2},
  publisher = {SpringerOpen},
  issn      = {2662-4753 (eISSN)},
  doi       = {10.1007/s40534-023-00303-7},
  pages     = {135 -- 144},
  year      = {2023},
  abstract  = {The first and last mile of a railway journey, in both freight and transit applications, constitutes a high effort and is either non-productive (e.g. in the case of depot operations) or highly inefficient (e.g. in industrial railways). These parts are typically managed on-sight, i.e. with no signalling and train protection systems ensuring the freedom of movement. This is possible due to the rather short braking distances of individual vehicles and shunting consists. The present article analyses the braking behaviour of such shunting units. For this purpose, a dedicated model is developed. It is calibrated on published results of brake tests and validated against a high-definition model for low-speed applications. Based on this model, multiple simulations are executed to obtain a Monte Carlo simulation of the resulting braking distances. Based on the distribution properties and established safety levels, the risk of exceeding certain braking distances is evaluated and maximum braking distances are derived. Together with certain parameters of the system, these can serve in the design and safety assessment of driver assistance systems and automation of these processes.},
  language  = {en}
}
@article{FranzenPindersPfaffetal.2018,
  author    = {Franzen, Julius and Pinders, Erik and Pfaff, Raphael and Enning, Manfred},
  title     = {RailCrowd's virtual fleets: Make most of your asset data},
  series = {Deine Bahn},
  journal   = {Deine Bahn},
  number    = {9},
  publisher = {Bahn-Fachverlag},
  address   = {Berlin},
  issn      = {0948-7263},
  pages     = {11 -- 13},
  year      = {2018},
  abstract  = {For smaller railway operators or those with a diverse fleet, it can be difficult to collect sufficient data to improve maintenance programs. At the same time, new rules such as entity in charge of maintenance - ECM - regulations impose an additional workload by requiring a dedicated maintenance management system and specific reports. The RailCrowd platform sets out to facilitate compliance with ECM and similar regulations while at the same time pooling anonymised fleet data across operators to form virtual fleets, providing greater data insights.},
  language  = {en}
}
@article{EnningPfaff2017,
  author    = {Enning, Manfred and Pfaff, Raphael},
  title     = {G{\"u}terwagen 4.0 - Der G{\"u}terwagen f{\"u}r das Internet der Dinge. Teil 1: Gesamtsystembetrachtung und grundlegendes Konzept},
  series = {ETR - Eisenbahntechnische Rundschau},
  volume    = {66},
  journal   = {ETR - Eisenbahntechnische Rundschau},
  number    = {1/2},
  publisher = {DVV Media Group},
  address   = {Hamburg},
  issn      = {0013-2845},
  pages     = {12 -- 16},
  year      = {2017},
  language  = {de}
}
@article{BabilonWilbringTappertetal.2018,
  author    = {Babilon, Katharina and Wilbring, Daniela and Tappert, Tim and Pfaff, Raphael and Enning, Manfred},
  title     = {Schienenfahrzeugtechnik hands on - FH Aachen IMechE Railway Challenge},
  series = {Ingenieurspiegel},
  journal   = {Ingenieurspiegel},
  number    = {2},
  publisher = {Public Verlag},
  address   = {Bingen},
  issn      = {1868-5919},
  pages     = {20 -- 22},
  year      = {2018},
  language  = {de}
}