The Effect of the Degree of Static Automation in Simulated Submarine Track Management

Automation that supports our workplaces is intended to relieve the requirement for humans to control tasks, as a way to reduce operator workload and maximize system capacity. Researchers have long recognized the potential costs associated with automation. These costs include the loss of an operator’s understanding of a task and an inability to anticipate future task events (situation awareness; SA; Endsley, 1995) that can occur due to automation induced complacency (Parasuraman, Molloy, & Singh, 1993), and the subsequent lack of ability to regain manual control after automation (Kaber & Endsley, 2004). These costs to automation are more likely to occur when the degree of automation (DOA) increases. DOA has been defined based on whether automation is doing more or less ‘work’ (levels of automation; Sheridan & Verplank, 1978), and at which of the four stages of human information processing the automation is directed; information acquisition, information analysis, decision selection, and action implementation (stages of automation; Parasuraman, Sheridan, & Wickens, 2000). As the DOA increases, performance and workload tend to improve. However, SA and return-to-manual performance can decline. Recent research by Chen, Huf, Visser, and Loft (2017) reported that a low DOA had minimal benefits to performance and workload, and also impaired SA and non-automated task performance compared to a manual control condition in a simulated submarine track management task. However, the low DOA did not lead to any return-to-manual deficits when automation was unexpectedly removed. The current study compared the effects of low and high DOA on operator performance, workload, SA, non-automated task performance, and return-to-manual performance in submarine track management. Participants (N= 122) monitored a tactical display that presented the location and heading of contacts in relation to the Ownship and landmarks, and a ‘waterfall’ display that presented sonar bearings of contacts and how those bearings change with time. Participants performed three tasks: classification, closest point of approach (CPA), and dive. The classification task involved classifying contacts depending on how long they had spent within display regions. The CPA task involved monitoring changes in contact heading to determine their closest point of approach to the Ownship. The dive task involved integrating contact location and heading information to determine when the submarine could safely dive. Automated assistance was provided for the classification and CPA tasks, but not for the dive task. The low DOA condition received information acquisition and analysis support (stages 1 and 2), whereas the high DOA received decision selection support (stage 3). In a mixed design, the between-subjects factor was condition (no automation, high DOA, low DOA) and the within-subjects factor was automation state (routine, automation removal). Participants completed three track management scenarios, and during the last scenario the automation was unexpectedly removed. Firstly, we predicted that a high DOA would have larger benefits to performance and workload compared to a low DOA, but that these benefits might be accompanied by costs to SA, non-automated task performance, and return-to-manual performance. Secondly, we predicted that a low DOA would show minimal benefits to performance and workload, significant costs to SA and non-automated task performance, and no effect on return-to-manual performance when compared to no automation, thus replicating the findings of Chen et al. (2017). The results from this study indicated that relative to the low DOA condition, participants provided with high DOA support had better performance and lower workload, without any further costs to SA, non-automated task performance, or return-to-manual performance. Furthermore, relative to no automation, participants provided with low DOA support only had minor benefits to performance (replicating Chen et al., 2017) and no benefits to workload, and significant costs to SA and non-automated task performance. In summary, the high DOA produced larger benefits to performance and workload than the low DOA, without increasing costs. In light of these results, the automated system that recommended decisions was effectively utilized by operators in the current context, and appeared to be superior to the automated system that supported information acquisition and analysis.