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Local knowledge in rail signalling and balancing trade-offs.

David Golightly¹, Mark S Young²

¹Future Mobility Group, Stephenson Building, Newcastle University, NE1 7RU, UK.

Applied Ergonomics

|March 4, 2022

Summary

This summary is machine-generated.

Rail signallers rely on local knowledge, which requires an updated framework to include public interactions at crossings. This research explores how local knowledge balances safety and performance in rail signalling operations.

Keywords:

Local knowledge Rail control Signalling

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Area of Science:

Human Factors
Transportation Science
Cognitive Psychology

Background:

Rail signalling control heavily relies on signallers' local knowledge and cognitive processes.
Existing Local Knowledge Frameworks (Pickup et al., 2013) provide a basis for understanding this knowledge.
Signaller work involves a continuous cognitive balancing act between system performance and safety constraints.

Purpose of the Study:

To investigate the role of local knowledge in rail signalling operations.
To evaluate and expand upon the existing Local Knowledge Framework.
To understand how local knowledge influences the trade-offs between safety and performance.

Main Methods:

Fieldwork involving interviews with rail signallers and operations managers.
Direct observation of signaller work activities.
Analysis of data to identify components and mechanisms of local knowledge.

Main Results:

The current Local Knowledge Framework needs expansion to incorporate public interactions at user-worked and level crossings.
Identified challenges in the effective transmission of local knowledge among signallers.
Highlighted the crucial role of local knowledge in specific signalling functions and their interaction for safety-performance trade-offs.

Conclusions:

Local knowledge is vital for effective rail signalling, extending beyond operational tasks to include public interface management.
The framework for understanding signaller local knowledge requires enhancement to reflect real-world complexities.
Findings have implications for the design of signaller work and training to improve both safety and operational efficiency.