Along with much of Europe and the global trend towards in-cab signalling, Great Britain (GB) rail is transitioning to Radio-based European Train Control System (ETCS). In collaboration with several universities and research partners, Network Rail have undertaken a programme of R&D to build on the opportunities that Radio-based ETCS offers, including the move towards automatic train operation (ATO), and integrated, centralised traffic management systems that maximise the potential in capacity, performance and energy efficiency for passenger and freight customers. Bringing the train planning and timetabling capabilities into the modernised, data driven, information rich world is a significant puzzle piece of turning opportunities offered by the signalling and control technologies into the day-to-day operations of the railway. This paper covers the research carried out into the characteristics of a radio-based ETCS railway that can be analysed for a goal-based state of the art train planning capability. It considers the advancement of tools, techniques, processes and skills that are required to plan, operate and regulate the railway through automatic train operations and future traffic management systems, ultimately harmonising planning, real-time operations and post-operations performance analysis.

The railway scheduling problem concerns the determination of trains' scheduled departure and arrival times at stops, and the allocation of capacity in the network. The timetable must be both conflict-free given infrastructure constraints, and stable enough for trains to recover from delays that could occur in normal operations. Existing methods for tactical scheduling contain a tradeoff between having an accurate (microscopic) representation of signalling constraints, and having a simple-enough (macroscopic) infrastructure representation to scale to real-world problem instances. This creates issues for infrastructure managers looking to run more trains on their infrastructure by migrating to Distance-To-Go (DTG) signalling systems (e.g. ETCS Level 2), and to exploit the capabilities of Connected Driver Advisory Systems (C-DAS) and Automatic Train Operation (ATO) to control trains more precisely. In this paper, we present a methodology for incorporating the capabilities of DTG signalling in conjunction with C-DAS and ATO systems into a disjunctive scheduling model for both periodic and nonperiodic instances. We show that the resulting model has both a microscopic infrastructure representation, and a macroscopic computational complexity, allowing railways to quickly compute conflict-free and stable timetables for large problem instances. The resulting model also accurately represents the computation of the brake indication point for both conventional and DTG signalling as a function of the trains' current speed. Tests on a large-scale periodic scheduling instance in the UK show that the model produces timetables with reasonable computation time.