This work aimed to organise recommendations for keeping people engaged during human supervision of driving automation, encouraging a safe and acceptable introduction of automated driving systems. First, heuristic knowledge of human factors, ergonomics, and psychological theory was used to propose solution areas to human supervisory control problems of sustained attention. Driving and non-driving research examples were drawn to substantiate the solution areas. Automotive manufacturers might (1) avoid this supervisory role altogether, (2) reduce it in objective ways or (3) alter its subjective experiences, (4) utilize conditioning learning principles such as with gamification and/or selection/training techniques, (5) support internal driver cognitive processes and mental models and/or (6) leverage externally situated information regarding relations between the driver, the driving task, and the driving environment. Second, a cross-domain literature survey of influential human-automation interaction research was conducted for how to keep engagement/attention in supervisory control. The solution areas (via numeric theme codes) were found to be reliably applied from independent rater categorisations of research recommendations. Areas (5) and (6) were addressed by around 70% or more of the studies, areas (2) and (4) in around 50% of the studies, and areas (3) and (1) in less than around 20% and 5%, respectively. The present contribution offers a guiding organisational framework towards improving human attention while supervising driving automation.

Highly mechanized forestry operations are essential for efficient timber harvesting. Therefore, the skills of harvester operators appear to be key to productive and sustainable use of the machines. Recent research has revealed a knowledge deficit regarding the work practices of forest machine operators. This urges systematic research into forestry machine handling and a corresponding refinement of analytical methods. Current analyses of operator tasks in forestry are less formalized and focus predominantly on machine efficiency and overall performance, but not so much on the human-related conditions of work performance and workload. Therefore, the objective of this paper is to introduce hierarchical task analysis (HTA) into forestry science. HTA is a versatile, formalized human-factors method that can be used to describe the work objectives of forest machine operators. HTA is suitable, for example, for describing (in)efficient work practices and thus as a basis for designing machine operator training and for systematically evaluating assistive technologies. The task analyses in this paper draw on a recently published empirical approach to analyzing work practices, workflows, and machine operator behavior for optimal human–machine collaboration in forestry application research. Specifically, the main work methods of clearcutting and thinning stand in European forestry were considered, with examples from Scandinavian and German method application. The process of HTA is described and a prototypical approach to HTA for both working methods provided. As a result, this work could show that a single work practice affects operator goals within different work elements and sets out how inefficient work practices can be described in terms of operator goals. With the introduction and exemplary application of HTA, a structured task definition in human-centered approaches is encouraged to analyze work practices, workflows, and machine operator behavior for optimal human–machine collaboration in forestry application research.

Variance in productivity of fully mechanized timber harvesting under comparable stand and terrain conditions requires the investigation of the influence of work practices of machine operators. Work practices can vary among operators and may result in a wide range of productivity. Therefore, it is of great interest to identify positive and negative work practices of forest machine operators to improve forest work. For the qualitative analysis of work practices, 15 forest machine operator instructors were interviewed in Norway, Sweden, and Germany in semi-structured interviews. Additionally, a literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was performed. The interviews brought up detailed positive work practices and showed negative examples of machine handling, specifically related to boom operation. The literature review retrieved 2482 articles of which 16 were examined in more detail. The review showed that work practice characteristics were only sparsely covered, however, still overlapped with the work practice recommendations from the operator instructor interviews. Further, the literature search unveiled a scientific knowledge gap related to the quantification of applied work practices. Generally, positive work practices can include using optimal working ranges from 4–6 m, frequent machine repositioning, a matched fit of operator skill and crane speed, and an assortment pile size that matches the maximum grapple loads. Training is recommended to focus on crane control in terms of movement precision and work range adherence whereby the speed-accuracy trade-off should be improved to meet productivity requirements and increase efficiency in forest machine operator work.

Freeway merging of heavy goods vehicles (HGV) is a safety–critical manoeuvre. However, at present, it is largely unknown how HGV drivers perceive and execute the merging manoeuvre, and how current advanced driver support and automation systems (ADAS) contribute. We performed semi-structured in-depth interviews with 15 HGV drivers to assess their visual and cognitive processes while merging, interactions with other road users, and attitudes towards ADAS as a basis for future support and automation system design. Results show that the reported execution of merging varies substantially between drivers. Drivers reported reliance on courtesy of other traffic but stated that car drivers are often causing conflicts, whereas other HGV drivers are more cooperative. Current ADAS were perceived as useful in general, with remarks about misuse and abundance of systems. We recommend the introduction of driver support and automation systems which facilitate cooperative behaviour and support effective communication.