[HTML][HTML] A literature review of Artificial Intelligence applications in railway systems
Nowadays it is widely accepted that Artificial Intelligence (AI) is significantly influencing a
large number of domains, including railways. In this paper, we present a systematic literature …
large number of domains, including railways. In this paper, we present a systematic literature …
Research and development of automatic train operation for railway transportation systems: A survey
With the rapid development of communication, control and computer technologies in the last
several decades, automatic train operation (ATO), for which the driver no longer has to …
several decades, automatic train operation (ATO), for which the driver no longer has to …
Dynamic passenger demand oriented metro train scheduling with energy-efficiency and waiting time minimization: Mixed-integer linear programming approaches
In the daily operation of metro systems, the train scheduling problem aims to find a set of
space-time paths for multiple trains that determine their departure and arrival times at metro …
space-time paths for multiple trains that determine their departure and arrival times at metro …
Energy-efficient metro train rescheduling with uncertain time-variant passenger demands: An approximate dynamic programming approach
In a heavily congested metro line, unexpected disturbances often occur to cause the delay of
the traveling passengers, infeasibility of the current timetable and reduction of the …
the traveling passengers, infeasibility of the current timetable and reduction of the …
Artificial intelligence in railway transport: Taxonomy, regulations, and applications
Artificial Intelligence (AI) is becoming pervasive in most engineering domains, and railway
transport is no exception. However, due to the plethora of different new terms and meanings …
transport is no exception. However, due to the plethora of different new terms and meanings …
Blockchain-based federated learning for intelligent control in heavy haul railway
Due to the long train marshaling and complex line conditions, the operating modes in heavy
haul rail systems frequently change when trains travel. Improper traction or braking …
haul rail systems frequently change when trains travel. Improper traction or braking …
An eco-driving algorithm for trains through distributing energy: A Q-Learning approach
Q Zhu, S Su, T Tang, W Liu, Z Zhang, Q Tian - ISA transactions, 2022 - Elsevier
The energy-efficient train operation methodology is the focus of this paper, and a Q-Learning-
based eco-driving approach is proposed. Firstly, the core idea of energy-distribution-based …
based eco-driving approach is proposed. Firstly, the core idea of energy-distribution-based …
Fault diagnosis network design for vehicle on-board equipments of high-speed railway: A deep learning approach
J Yin, W Zhao - Engineering Applications of Artificial Intelligence, 2016 - Elsevier
With the rapid development of high-speed railways (HSRs) throughout the world, the fault
diagnosis systems of vehicle on-board equipments (VOBEs) for high speed trains have …
diagnosis systems of vehicle on-board equipments (VOBEs) for high speed trains have …
A scalable reinforcement learning algorithm for scheduling railway lines
H Khadilkar - IEEE Transactions on Intelligent Transportation …, 2018 - ieeexplore.ieee.org
This paper describes an algorithm for scheduling bidirectional railway lines (both single-and
multi-track) using a reinforcement learning (RL) approach. The goal is to define the track …
multi-track) using a reinforcement learning (RL) approach. The goal is to define the track …
An actor-critic deep reinforcement learning approach for metro train scheduling with rolling stock circulation under stochastic demand
This paper presents a novel actor-critic deep reinforcement learning approach for metro train
scheduling with circulation of limited rolling stock. The scheduling problem is modeled as a …
scheduling with circulation of limited rolling stock. The scheduling problem is modeled as a …