D-MOD Dynamic Modelling of Operator Demand: a new simulator module for the evaluation of signaler’s demand

Delamere, Lise; Lumby, Andy; Treble, Peter; Golightly, David

Abstract

Estimating signaler demand is critical for ensuring signaling workstations are both feasible to run, and acceptable to staff. While human factors tools exist, they are typically manual, time consuming and rely of the skill of an expert. One solution, explored in this paper, is to use signaling simulators to assist in the estimation of demand.
Full fidelity signaling simulators are already widely used in the UK. Simulators give the ability to ensure a consistent standard of competency ranging from normal routine tasks to abnormal situations (e.g. faults and failures) monitored by an experienced trainer/assessor. Whilst the original aim of full fidelity simulators was to support training and assessment of signalers, the requirement for an accurate timetable and infrastructure model, and of a realistic workstation Human Machine Interface (HMI), opens up other applications.
The aim of the Dynamic Modelling of Operator Demand (DMOD) project is to use the Hitachi Information Control System’s simulation environment (TREsim signaling simulator) to deliver a workstation evaluation tool. The paper will present how the existing elements of simulator have been expanded and utilized for demand modelling, covering the architecture of D-MOD, the process of selecting and developing demand metrics, and the design of an HMI to deliver a working proof of concept.

Citation

Delamere, L., Lumby, A., Treble, P., & Golightly, D. D-MOD Dynamic Modelling of Operator Demand: a new simulator module for the evaluation of signaler’s demand. Presented at 2016 IEEE International Conference on Intelligent Rail Transportation

• Conference Name: 2016 IEEE International Conference on Intelligent Rail Transportation
• End Date: Aug 25, 2016
• Acceptance Date: May 19, 2016
• Deposit Date: Jun 21, 2016
• Peer Reviewed: Peer Reviewed
• Keywords: Simulator; Railway signaler; Training; Workload
• Public URL: https://nottingham-repository.worktribe.com/output/789297
• Related Public URLs: http://www.ieee-icirt.com/
• Contract Date: Jun 21, 2016