TL;DR
This paper formalizes design tasks for the European Train Control System with Hybrid Train Detection, proving their computational complexity as NP-hard, which supports future development of automated solutions for railway network optimization.
Contribution
It provides the first formal description and complexity analysis of design tasks for ETCS L2 HTD, establishing NP-hardness results that underpin future automated design methods.
Findings
Formal description of ETCS L2 HTD design tasks
Proof that these tasks are NP-complete or NP-hard
Foundation for developing automated railway network design tools
Abstract
Railway networks have become increasingly important in recent times, especially in moving freight and public transportation from road traffic and planes to more environmentally friendly trains. Since expanding the global railway network is time- and resource-consuming, maximizing the rail capacity of the existing infrastructure is desirable. However, simply running more trains is infeasible as certain constraints enforced by the train control system must be satisfied. The capacity of a network depends (amongst others) on the distance between trains allowed by this safety system. While most signaling systems rely on fixed blocks defined by costly hardware, new specifications provided by Level 2 with Hybrid Train Detection of the European Train Control System (ETCS L2 HTD), formerly known as ETCS Hybrid Level 3, allow the usage of virtual subsections. This additional degree of freedom…
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