A new approach for Training Needs Analysis: A case study using an Automated Vehicle

Abstract

Considerable resources are invested each year into training to ensure trainees have the required competencies to safely and effectively perform their tasks/jobs. As such, it is important to develop effective training programmes which target those required competencies. One method that can be used at the start of the training lifecycle to establish the tasks and competencies that are required for a task/job and is considered an important activity to perform when developing a training programme is a Training Needs Analysis (TNA). This article presents a new TNA approach and uses an Automated Vehicle (AV) case study to demonstrate this new approach for a specific AV scenario within the current UK road system. A Hierarchical Task Analysis (HTA) was performed in order to identify the overall goal and tasks that drivers need to perform to operate the AV system safely on the road. This HTA identified 7 main tasks which were decomposed into 26 sub-tasks and 2428 operations. Then, six AV driver training themes from the literature were combined with the Knowledge, Skills and Attitudes (KSA) taxonomy to identify the KSAs that drivers need to perform the tasks, sub-tasks and operations that were identified in the HTA (training needs). This resulted in the identification of over 100 different training needs. This new approach helped to identify more tasks, operations and training needs than previous TNAs which applied the KSA taxonomy alone. As such, a more comprehensive TNA for drivers of the AV system was produced. This can be more easily translated into the development and evaluation of future training programmes for drivers of AV systems.

Keywords: Automated Vehicles; Driver training; Hierarchical Task Analysis; Training Needs Analysis.