@InProceedings{10.1007/978-3-032-11442-6_34,
author="Leslie, Rebekah
and Earnshaw, Calvin
and Jam, Favour
and Komnata, Kacper
and Maita, Andreas
and Cardoso, Rafael C.",
editor="Bramer, Max
and Stahl, Frederic",
title="TrafficSim: A Simulation Framework for the Scottish Rail Network in ROS2",
booktitle="45th SGAI International Conference on Artificial Intelligence",
year="2025",
publisher="Springer Nature Switzerland",
address="Cham",
pages="444--450",
doi="10.1007/978-3-032-11442-6_34",
abstract="Rail networks are continuously expanding to introduce new routes or modify existing ones in an effort to optimise the balance between efficiency and cost. Simulation tools can help better understand current pressures on a rail network and facilitate experiments, including the addition of new or altered railway lines. In this paper, we present TrafficSim, a simulation framework for modelling the Scottish Rail Network using ROS2 and Pyrobosim. TrafficSim enables autonomous train movement with a custom A* planner, incorporates safety constraints such as exclusive line access, and supports real-time timetable and freight simulations. Initial experiments show that freight delivery times vary with train density, highlighting both the scalability of the package and the limitations of the current rail network infrastructure.",
isbn="978-3-032-11442-6"
}

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