Local knowledge in rail signalling and balancing trade-offs

The control of rail signalling is known to be highly dependent on local knowledge and local factors. It is also known to be highly cognitive in its nature involving a constant balancing of system performance within the constraints of safety. In the current paper, data generated through field work with signallers were used to understand the role of local knowledge, set against the background of an existing Local Knowledge Framework (Pickup et al., 2013) that was proposed to help determine the contents and mechanisms behind local knowledge in rail signalling. The field work included interviews with signallers and operations managers along with observations of signaller work. The results showed that the local knowledge framework needs to be expanded to include aspects related to the general public at user worked crossings and level crossings. In addition, the analysis highlights some of the issues with the transmission of local knowledge. The paper then discusses some of the gaps in the current framework, highlighting the importance not only of local knowledge for specific functions of signalling, but how these interact to support trade-offs to balance performance with safety. The implications for the design of signaller work are discussed. •Presents data to explore cognitive aspects of rail signaller performance.•Builds upon a pre-existing Local Knowledge Framework.•Identifies new additions to model for level crossings and behaviours of public.•Identifies issues with learning geographical knowledge for area of control.•Links informal local knowledge with the need to balance operational performance with safety.