Christopher D. Wickens

A model for types and levels of human interaction with automation

Technical developments in computer hardware and software now make it possible to introduce automation into virtually all aspects of human-machine systems. Given these technical capabilities, which system functions should be automated and to what extent? We outline a model for types and levels of automation that provides a framework and an objective basis for making such choices. Appropriate selection is important because automation does not merely supplant but changes human activity and can impose new coordination demands on the human operator. We propose that automation can be applied to four broad classes of functions: 1) information acquisition; 2) information analysis; 3) decision and action selection; and 4) action implementation. Within each of these types, automation can be applied across a continuum of levels from low to high, i.e., from fully manual to fully automatic. A particular system can involve automation of all four types at different levels. The human performance consequences of particular types and levels of automation constitute primary evaluative criteria for automation design using our model. Secondary evaluative criteria include automation reliability and the costs of decision/action consequences, among others. Examples of recommended types and levels of automation are provided to illustrate the application of the model to automation design.

Multiple resources and performance prediction

This paper describes the origins and history of multiple resource theory in accounting for differences in dual task interference. One particular application of the theory, the 4-dimensional multiple resources model, is described in detail, positing that there will be greater interference between two tasks to the extent that they share stages (perceptual/cognitive vs response) sensory modalities (auditory vs visual), codes (visual vs spatial) and channels of visual information (focal vs ambient). A computational rendering of this model is then presented. Examples are given of how the model predicts interference differences in operational environments. Finally, three challenges to the model are outlined regarding task demand coding, task allocation and visual resource competition.

Multiple resources and mental workload

Objective: The objective is to lay out the rationale for multiple resource theory and the particular 4-D multiple resource model, as well as to show how the model is useful both as a design tool and as a means of predicting multitask workload overload. Background: I describe the discoveries and developments regarding multiple resource theory that have emerged over the past 50 years that contribute to performance and workload prediction. Method: The article presents a history of the multiple resource concept, a computational version of the multiple resource model applied to multitask driving simulation data, and the relation of multiple resources to workload. Results: Research revealed the importance of the four dimensions in accounting for task interference and the association of resources with brain structure. Multiple resource models yielded high correlations between model predictions and data. Lower correlations also identified the existence of additional resources. Conclusion: The model was shown to be partially relevant to the concept of mental workload, with greatest relevance to performance breakdowns related to dual-task overload. Future challenges are identified. Application: The most important application of the multiple resource model is to recommend design changes when conditions of multitask resource overload exist.

THE PROXIMITY COMPATIBILITY PRINCIPLE: ITS PSYCHOLOGICAL FOUNDATION AND RELEVANCE TO DISPLAY DESIGN

In this report we describe the concept of the proximity compatibility principle (PCP) and demonstrate its relevance to display design: Displays relevant to a common task or mental operation (close task or mental proximity) should be rendered close together in perceptual space (close display proximity). Different forms of task proximity are discussed, as are the different information-processing mechanisms that underlie the effects of the several different design manipulations of display proximity. Experimental data that support this process-based elaboration of PCP are then reviewed in design contexts relating to aviation, graphs, display layout, and decision aiding.

Examining the impact of cell phone conversations on driving using meta-analytic techniques

Objective: The performance costs associated with cell phone use while driving were assessed meta-analytically using standardized measures of effect size along five dimensions. Background: There have been many studies on the impact of cell phone use on driving, showing some mixed findings. Methods: Twenty-three studies (contributing 47 analysis entries) met the appropriate conditions for the meta-analysis. The statistical results from each of these studies were converted into effect sizes and combined in the meta-analysis. Results: Overall, there were clear costs to driving performance when drivers were engaged in cell phone conversations. However, subsequent analyses indicated that these costs were borne primarily by reaction time tasks, with far smaller costs associated with tracking (lane-keeping) performance. Hands-free and handheld phones revealed similar patterns of results for both measures of performance. Conversation tasks tended to show greater costs than did information-processing tasks (e.g., word games). There was a similar pattern of results for passenger and remote (cell phone) conversations. Finally, there were some small differences between simulator and field studies, though both exhibited costs in performance for cell phone use. Conclusion: We suggest that (a) there are significant costs to driver reactions to external hazards or events associated with cell phone use, (b) hands-free cell phones do not eliminate or substantially reduce these costs, and (c) different research methodologies or performance measures may underestimate these costs. Application: Potential applications of this research include the assessment of performance costs attributable to different types of cell phones, cell phone conversations, experimental measures, or methodologies.

Compatibility and Resource Competition between Modalities of Input, Central Processing, and Output

Synthesized auditory displays and speech recognizers were used in two experiments to develop guidelines for their implementation in military aircraft. In the first experiment, the competition between encoding and response modalities of concurrent tasks was examined. The memory search task was more susceptible to competition for visual encoding, whereas the tracking task bore the greater impact from shared manual responding. The second experiment examined competition between tasks for encoding and response modalities and the optimum assignment of modalities to a given task. A simulated flight task was performed concurrently with either a spatial task (target acquisition) or a verbal task (memory). Best performance and least interference with the flight task were obtained when the spatial task was displayed visually and responded to manually and also when the verbal task was displayed auditorily and responded to with speech.

Applied attention theory

Introduction Single Channel Theory and Automaticity Theory Attention Control Visual Attention Control, Scanning and Information Sampling Visual Search Spatial Attention and Displays Resources and Effort Time Sharing and Multiple Resource Theory Executive Control: Attention Switching, Interruptions and Task-Management Individual Differences in Attention Cognitive Neurosciences and Neuroergonomics

Situation Awareness, Mental Workload, and Trust in Automation: Viable, Empirically Supported Cognitive Engineering Constructs

Cognitive engineering needs viable constructs and principles to promote better understanding and prediction of human performance in complex systems. Three human cognition and performance constructs that have been the subjects of much attention in research and practice over the past three decades are situation awareness (SA), mental workload, and trust in automation. Recently, Dekker and Woods (2002) and Dekker and Hollnagel (2004; henceforth DWH) argued that these constructs represent “folk models” without strong empirical foundations and lacking scientific status. We counter this view by presenting a brief description of the large science base of empirical studies on these constructs. We show that the constructs can be operationalized using behavioral, physiological, and subjective measures, supplemented by computational modeling, but that the constructs are also distinct from human performance. DWH also caricatured as “abracadabra” a framework suggested by us to address the problem of the design of automated systems (Parasuraman, Sheridan, & Wickens, 2000). We point to several factual and conceptual errors in their description of our approach. Finally, we rebut DWHs view that SA, mental workload, and trust represent folk concepts that are not falsifiable. We conclude that SA, mental workload, and trust are viable constructs that are valuable in understanding and predicting human-system performance in complex systems.

The event-related brain potential as an index of display-monitoring workload

As an index of task workload, the possible advantages of the event-related brain potential (ERP) over traditional secondary task and physiological measures are described and previous efforts to validate the use of ERPs in this context are discussed. An experiment is then reported in which perceptual load, incurred by monitoring a simulated air-traffic-control display for discrete events, is assessed using (a) measures of the P300 component of ERPs elicited by auditory probe stimuli and (b) a reaction time secondary task. The ERP measures were found to reflect systematically differences in task workload and to covary closely with the reaction time measure. The results are discussed within the framework of a multidimensional conception of human processing resources and task workload.

Modeling drivers' visual attention allocation while interacting with in-vehicle technologies

In 2 experiments, the authors examined how characteristics of a simulated traffic environment and in-vehicle tasks impact driver performance and visual scanning and the extent to which a computational model of visual attention (SEEV model) could predict scanning behavior. In Experiment 1, the authors manipulated task-relevant information bandwidth and task priority. In Experiment 2, the authors examined task bandwidth and complexity, while introducing infrequent traffic hazards. Overall, task priority had a significant impact on scanning; however, the impact of increasing bandwidth was varied, depending on whether the relevant task was supported by focal (e.g., in-vehicle tasks; increased scanning) or ambient vision (e.g., lane keeping; no increase in scanning). The computational model accounted for approximately 95% of the variance in scanning across both experiments.