Program for stream The 2nd International Workshop on Artificial Intelligence for RAILwayS (AI4RAILS)

MB-49: AI4RAILS keynote
Stream: The 2nd International Workshop on Artificial Intelligence for RAILwayS (AI4RAILS)
Room: Virtual Room 49
Chair(s): Nikola Bešinović

• Keynote: Data Science in Alstom: Our Road from Mobility Leader to Digital Giant
  Nenad Mijatovic

MC-49: AI4RAILS I
Stream: The 2nd International Workshop on Artificial Intelligence for RAILwayS (AI4RAILS)
Room: Virtual Room 49
Chair(s): Nikola Bešinović

• Ant colony optimization: improved performance for train routing in complex rail networks
  Bianca Pascariu, Marcella Samà, Paola Pellegrini, Andrea D'Ariano, Dario Pacciarelli, Joaquin Rodriguez
• Predicting Key Figures of Rail Freight Service Networks with Machine Learning
  Tobias Pollehn, Daniel Haalboom
• A Hybrid VNS-TS Algorithm for an Integrated Railway Rescheduling and Rerouting
  Banafsheh Khosravi, Kullachet Korpattanachaijaroen, Djamila Ouelhadj
• A Reinforcement Learning Approach for Railway Scheduling
  Cedric Steinbach, Arturo Crespo Materna

MD-49: AI4RAILS II
Stream: The 2nd International Workshop on Artificial Intelligence for RAILwayS (AI4RAILS)
Room: Virtual Room 49
Chair(s): Rob Goverde

• A Multi-Agent Approach to the Train Unit Shunting Problem
  Wan-Jui Lee, Quintess Barnhoorn
• TORS: A Train Unit Shunting and Servicing Simulator
  Jacobus G.M. van der Linden, Jesse Mulderij, Bob Huisman, Joris den Ouden, Marjan van den Akker, Han Hoogeveen, Mathijs de Weerdt
• An Evolutionary Approach to Solve the Train Unit Shunting and Servicing Problem
  Casper Athmer, Mathijs de Weerdt, Laurens Bliek
• Contextual hyperparameter optimization for the Train Unit Shunting Problem
  Leon van der Knaap, Laurens Bliek, Mathijs de Weerdt

TB-50: AI4RAILS III
Stream: The 2nd International Workshop on Artificial Intelligence for RAILwayS (AI4RAILS)
Room: Virtual Room 50
Chair(s): Zhiyuan Lin

• Train delay and dwell pattern recognition using K-means clustering approaches: a comparison before, during and after Covid-19 lockdown
  Zhiyuan Lin, Manuel Ojeda Cabral, Yulin Peng
• Real-time predictive analytics over space and time: A comparative analysis for delay prediction in railway transportation
  Léon Sobrie, Veerle Hennebel, Bart Roets, Marijn Verschelde
• Exploring significant predictors of freight rail intermodal operation delays using causal machine learning
  Juan Pineda, William McDonald, Wei Zheng, Francesco Viti
• Applying Machine Learning for Yard Departure Prediction
  Niloofar Minbashi, Markus Bohlin, Carl-William Palmqvist, Behzad Kordnejad

TC-50: AI4RAILS IV
Stream: The 2nd International Workshop on Artificial Intelligence for RAILwayS (AI4RAILS)
Room: Virtual Room 50
Chair(s): Rob Goverde

• Towards Risk Assessment of Learned Computer Vision for ATO
  Rustam Tagiew, Thomas Buder, Kai Hofmann, Christian Klotz, Roman Tilly
• Multiple-Train Energy Consumption Minimization in Real-Time Railway Traffic Management
  Federico Naldini, Paola Pellegrini, Joaquin Rodriguez
• AI for self-driving trains
  Pavel Popov
• Parameter estimation of train trajectory models using reservoir computing
  Alex Cunillera, Nikola Bešinović, Niels van Oort, Rob Goverde

TD-50: AI4RAILS V
Stream: The 2nd International Workshop on Artificial Intelligence for RAILwayS (AI4RAILS)
Room: Virtual Room 50
Chair(s): Zhiyuan Lin

• Vision-based railway track extraction and obstacle detection using deep learning for autonomous train
  Amine Boussik, Antoine Plissonneau, Wael Ben Messaoud, Abdelmalik Taleb-Ahmed, Smail Niar, Abdelghani Bekrar , Damien Trentesaux
• Degradation modeling of railway tracks by analysing longitudinal level change with machine learning techniques
  Nadine Friesen, Saskia Bluhm, Nils Nießen
• Artificial Intelligence in railway transport: the state-of-the-art survey and future research agenda
  Ruifan Tang, Lorenzo De Donato, Nikola Bešinović, Francesco Flammini, Zhiyuan Lin, Ronghui Liu, Mauro José Pappaterra, Tianli Tang, Valeria Vittorini, Ziyulong Wang
• Mountain Railway Alignment Optimization with Deep Reinforcement Learning
  Qing He, Tianci Gao