Driver training and assessment framework for enhanced safety, productivity and quality

Public safety is prime concern in rail industry and driver training is crucial. Apprentice train drivers are required to complete massive hours under supervision of experienced drivers to attain the required skill sets causing productivity issues. Traditional training is paper based, and assessments are individually evaluated without any scientific rigor resulting in quality challenges. This research developed a virtual reality-based framework to eliminate human cognitive bias in training environments, focusing upon hazard situations. A relationship matrix-based assessment was developed to assist managers in recruitment and training. The results from these studies can be transferred to other similar effected industries.