It requires a ‘guiding mind’ able to take account of, and respond to:

• Different policies (eg energy saving, capacity or reliability maximisation, recovery from perturbation) in force at different times and locations
• Changes in these policies in real time, in response to changing operational conditions

The fundamental concept is simple: the train says ‘this is where I am’, and the ‘guiding mind’ says ‘this is what you do’ (eg drive at this speed, coast etc). 

It also makes available complete, accurate and timely information in support of operators and to benefit customers. In advanced form, it enables the automation of traffic regulation on the network.

This approach to traffic management in turn requires a long-term view, currently underdeveloped, about how the railway will be used and operated for different markets and locations.

The benefits of automated network regulation apply under normal operational conditions and where there is abnormal, degraded or emergency working. For normal conditions, it can optimise traffic flow, energy use and power demand, regulating trains ahead of conflicts, using information gained from intelligent trains and infrastructure and advanced position monitoring systems. Where other conditions apply, the decision support capability can optimise for a different policy and help return the network to normal operation. Customer information systems will feed off traffic management systems, providing reliable and up to date information to passengers and freight users.

Much of this transformation could be delivered independently and well in advance of ERTMS, and bring benefits much earlier. ERTMS once delivered, will in any case need to incorporate a fully optimised traffic management layer to realise its full potential. For instance, system capacity will be greatly enhanced on routes where bi-directional operation can become the norm, with timetable rules written to accommodate the new capability. An array of technologies will be required to support this approach to traffic management, including accurate reporting of position and orientation of rolling stock,
consistent geographic referencing systems, driver advisory systems, operational communications systems and real
time braking information, in addition to the modelling to underpin the ‘guiding mind’ software.

Progress and early insights

To take these ideas forward, the ‘Next Generation Traffic Management’ (NGTM) programme, as a first step, is building the economic case for the provision of whole system traffic management, including as a ‘traffic management layer’ for ERTMS, using a systems modelling approach. The case will be based primarily on energy and capacity benefits.

The programme is developing the principles that would apply for traffic management to support policies in place at varying locations and times and principles to support making information available for operational decisions and customer advice.

Supporting activity is investigating:

• Driver advisory systems (DAS) to assist train drivers with guidance on optimal speed and driving techniques to maximise system capacity. First Group is working with Network Rail to trial this technology and early indications are that substantial fuel savings can be made.
• Enhanced train location and identification technologies, and their integration with data transmission initiatives
• Reliable position tracking of trains
• Better understanding of braking (adhesion) capability in real time
• The circumstances where automatic train operation (ATO) might provide safety and punctuality benefits
• ATP cab-signalling without on-track detection and sensor technology that works in bad weather

Underpinning traffic management development is the requirement for a set of premises about the way the railway is to be used in the long term by its customers. A range of scenarios is being developed against which to evaluate different technical ‘operational concepts’ and test them for robustness. Technology issues being considered in this context include crashworthiness, optimisation of both capacity and power supply, standards changes and system trade-offs.

Work to develop driver advisory systems is being progressed for the industry by First Group. Initial tasks are defining data interfaces, understanding the human factors implications (effects on the driver), development of ‘real time’ timetables and modelling the commercial implications for all stakeholders (eg performance regime adjustment should overall network performance decisions cause trains to be delayed for the greater good).

It is clear that many of these ideas, while having a significant impact on cost and carbon for the future railway, are many years from implementation. In the shorter term, it would be possible to develop optimisation algorithms to identify the most favourable timetables, eg in terms of energy and carbon costs and overall reliability.

Traffic management is critically dependent on developments in data and communications and closely associated with a whole-system approach to asset management. In turn it is a key contributor to delivering the challenges of the energy programme, both directly and as an enabler for discontinuous electrification.