World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
47
Citations
7205
World Ranking
4959
National Ranking
100

Overview

Rob M.P. Goverde is affiliated with Delft University of Technology in the Netherlands and focuses primarily on engineering research, with extensive work in industrial and manufacturing engineering as well as mechanical engineering. Their research also explores areas within transportation, automotive engineering, and strategy and management.

Their main topics of investigation include:

  • Railway Systems and Energy Efficiency
  • Railway Engineering and Dynamics
  • Transportation Planning and Optimization
  • Maritime Ports and Logistics
  • Electrical Contact Performance and Analysis
  • Transport and Economic Policies
  • Electric and Hybrid Vehicle Technologies

They have published frequently in the following venues:

  • Journal of Rail Transport Planning & Management (13 publications)
  • Transportation Research Part C Emerging Technologies (9 publications)
  • IEEE Transactions on Intelligent Transportation Systems (8 publications)
  • SSRN Electronic Journal (3 publications)
  • Transportation Research Part A Policy and Practice (2 publications)

Some of their recent papers include:

  • "A literature review of Artificial Intelligence applications in railway systems," 2022, Transportation Research Part C Emerging Technologies
  • "A multi-state train-following model for the analysis of virtual coupling railway operations," 2020, Journal of Rail Transport Planning & Management
  • "Artificial Intelligence in Railway Transport: Taxonomy, Regulations, and Applications," 2021, IEEE Transactions on Intelligent Transportation Systems
  • "Train trajectory optimization for improved on-time arrival under parametric uncertainty," 2020, Transportation Research Part C Emerging Technologies
  • "A hybrid Delphi-AHP multi-criteria analysis of Moving Block and Virtual Coupling railway signalling," 2021, Transportation Research Part C Emerging Technologies

Goverde has collaborated frequently with several researchers, including:

  • Egidio Quaglietta (15 joint publications)
  • Nikola Bešinović (13 joint publications)
  • Niels van Oort (9 joint publications)
  • Ronghui Liu (7 joint publications)
  • Valeria Vittorini (6 joint publications)

In addition to journal articles, Goverde has contributed to book publications, notably with Springer International Publishing. One such title is Energy-Efficient Train Operation, published in 2023.

Best Publications

  • Review of energy-efficient train control and timetabling

    Gerben M. Scheepmaker;Rob M.P. Goverde;Leo G. Kroon

  • Railway Timetable Stability Analysis Using Max-plus System Theory

    Rob M.P. Goverde

  • Recent applications of big data analytics in railway transportation systems: A survey

    Faeze Ghofrani;Qing He;Rob M.P. Goverde;Xiang Liu

  • A literature review of Artificial Intelligence applications in railway systems

    Unknown

  • A delay propagation algorithm for large-scale railway traffic networks

    Rob M.P. Goverde

  • Punctuality of railway operations and timetable stability analysis

    Rob M P Goverde

  • A multi-state train-following model for the analysis of virtual coupling railway operations

    Egidio Quaglietta;Meng Wang;Rob M.P. Goverde

  • Railway line capacity consumption of different railway signalling systems under scheduled and disturbed conditions

    Rob M.P. Goverde;Francesco Corman;Francesco Corman;Andrea D’Ariano

  • Multiple-phase train trajectory optimization with signalling and operational constraints

    Pengling Wang;Pengling Wang;Rob M.P. Goverde

  • Multi-train trajectory optimization for energy-efficient timetabling

    Pengling Wang;Rob M.P. Goverde

  • An integrated micro–macro approach to robust railway timetabling

    Nikola Bešinović;Rob M.P. Goverde;Egidio Quaglietta;Roberto Roberti

  • Railway timetable rescheduling with flexible stopping and flexible short-turning during disruptions

    Yongqiu Zhu;Rob M.P. Goverde

  • Predictive modelling of running and dwell times in railway traffic

    Pavle Kecman;Rob M. P. Goverde

  • Multi-train trajectory optimization for energy efficiency and delay recovery on single-track railway lines

    Pengling Wang;Rob M.P. Goverde

  • Artificial Intelligence in Railway Transport: Taxonomy, Regulations, and Applications

    Unknown

  • Rescheduling models for railway traffic management in large-scale networks

    Pavle Kecman;Francesco Corman;Andrea D’Ariano;Rob M. P. Goverde

  • A three-level framework for performance-based railway timetabling

    Rob M P Goverde;Nikola Bešinović;Anne Binder;Valentina Cacchiani

  • Online Data-Driven Adaptive Prediction of Train Event Times

    Pavle Kecman;Rob M. P. Goverde

  • Modeling railway disruption lengths with Copula Bayesian Networks

    Aurelius A. Zilko;Dorota Kurowicka;Rob M.P. Goverde

  • The ON-TIME real-time railway traffic management framework: A proof-of-concept using a scalable standardised data communication architecture

    Egidio Quaglietta;Egidio Quaglietta;Paola Pellegrini;Rob M.P. Goverde;Thomas Albrecht

  • Online train delay recognition and running time prediction

    Ingo A. Hansen;Rob M.P. Goverde;Dirk J. van der Meer

  • The interplay between energy-efficient train control and scheduled running time supplements

    Gerben M. Scheepmaker;Rob M.P. Goverde

Frequent Co-Authors

Oded Cats
Oded Cats Delft University of Technology
Andrea D'Ariano
Andrea D'Ariano Roma Tre University
Winnie Daamen
Winnie Daamen Delft University of Technology
Paolo Toth
Paolo Toth University of Bologna
Leo Kroon
Leo Kroon Erasmus University Rotterdam
Henk A. Dijkstra
Henk A. Dijkstra Utrecht University
Stefan C. Dekker
Stefan C. Dekker Utrecht University
Tao Tang
Tao Tang Beijing Jiaotong University
Anita Schöbel
Anita Schöbel Technical University of Kaiserslautern

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