Driver behaviour with adaptive cruise control

This paper reports on the evaluation of adaptive cruise control (ACC) from a psychological perspective. It was anticipated that ACC would have an effect upon the psychology of driving, i.e. make the driver feel like they have less control, reduce the level of trust in the vehicle, make drivers less situationally aware, but workload might be reduced and driving might be less stressful. Drivers were asked to drive in a driving simulator under manual and ACC conditions. Analysis of variance techniques were used to determine the effects of workload (i.e. amount of traffic) and feedback (i.e. degree of information from the ACC system) on the psychological variables measured (i.e. locus of control, trust, workload, stress, mental models and situation awareness). The results showed that: locus of control and trust were unaffected by ACC, whereas situation awareness, workload and stress were reduced by ACC. Ways of improving situation awareness could include cues to help the driver predict vehicle trajectory and identify conflicts

Predicting operator workload during system design

A workload prediction methodology was developed in response to the need to measure workloads associated with operation of advanced aircraft. The application of the methodology will involve: (1) conducting mission/task analyses of critical mission segments and assigning estimates of workload for the sensory, cognitive, and psychomotor workload components of each task identified; (2) developing computer-based workload prediction models using the task analysis data; and (3) exercising the computer models to produce predictions of crew workload under varying automation and/or crew configurations. Critical issues include reliability and validity of workload predictors and selection of appropriate criterion measures

Cockpit data management

This study is a continuation of an FAA effort to alleviate the growing problems of assimilating and managing the flow of data and flight related information in the air transport flight deck. The nature and extent of known pilot interface problems arising from new NAS data management programs were determined by a comparative timeline analysis of crew tasking requirements. A baseline of crew tasking requirements was established for conventional and advanced flight decks operating in the current NAS environment and then compared to the requirements for operation in a future NAS environment emphasizing Mode-S data link and TCAS. Results showed that a CDU-based pilot interface for Mode-S data link substantially increased crew visual activity as compared to the baseline. It was concluded that alternative means of crew interface should be available during high visual workload phases of flight. Results for TCAS implementation showed substantial visual and motor tasking increases, and that there was little available time between crew tasks during a TCAS encounter. It was concluded that additional research should be undertaken to address issues of ATC coordination and the relative benefit of high workload TCAS features

Spacecraft crew procedures from paper to computers

Described here is a research project that uses human factors and computer systems knowledge to explore and help guide the design and creation of an effective Human-Computer Interface (HCI) for spacecraft crew procedures. By having a computer system behind the user interface, it is possible to have increased procedure automation, related system monitoring, and personalized annotation and help facilities. The research project includes the development of computer-based procedure system HCI prototypes and a testbed for experiments that measure the effectiveness of HCI alternatives in order to make design recommendations. The testbed will include a system for procedure authoring, editing, training, and execution. Progress on developing HCI prototypes for a middeck experiment performed on Space Shuttle Mission STS-34 and for upcoming medical experiments are discussed. The status of the experimental testbed is also discussed

Workload modeling using time windows and utilization in an air traffic control task

In this paper, we show how to assess human workload for continuous tasks and describe how operator performance is affected by variations in break-work intervals and by different utilizations. A study was conducted examining the effects of different break-work intervals and utilization as a factor in a mental workload model. We investigated the impact of operator performance on operational error while performing continuous event-driven air traffic control tasks with multiple aircraft. To this end we have developed a simple air traffic control (ATC) model aimed at distributing breaks to form different configurations with the same utilization. The presented approach extends prior concepts of workload and utilization, which are based on a simple average utilization, and considers the specific patterns of break-work intervals. Copyright 2011 by Human Factors and Ergonomics Society, Inc. All rights reserved

Cognitive load theory, educational research, and instructional design: some food for thought

Cognitive load is a theoretical notion with an increasingly central role in the educational research literature. The basic idea of cognitive load theory is that cognitive capacity in working memory is limited, so that if a learning task requires too much capacity, learning will be hampered. The recommended remedy is to design instructional systems that optimize the use of working memory capacity and avoid cognitive overload. Cognitive load theory has advanced educational research considerably and has been used to explain a large set of experimental findings. This article sets out to explore the open questions and the boundaries of cognitive load theory by identifying a number of problematic conceptual, methodological and application-related issues. It concludes by presenting a research agenda for future studies of cognitive load

NASA TLA workload analysis support. Volume 1: Detailed task scenarios for general aviation and metering and spacing studies

The techniques required to produce and validate six detailed task timeline scenarios for crew workload studies are described. Specific emphasis is given to: general aviation single pilot instrument flight rules operations in a high density traffic area; fixed path metering and spacing operations; and comparative workload operation between the forward and aft-flight decks of the NASA terminal control vehicle. The validation efforts also provide a cursory examination of the resultant demand workload based on the operating procedures depicted in the detailed task scenarios

Integrating Constrained Experiments in Long-term Human-Robot Interaction using Task– and Scenario–based Prototyping

© 2015 The Author(s). Published with license by Taylor & Francis© Dag Sverre Syrdal, Kerstin Dautenhahn, Kheng Lee Koay, and Wan Ching Ho. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The moral rights of the named author(s) have been asserted. Permission is granted subject to the terms of the License under which the work was published. Please check the License conditions for the work which you wish to reuse. Full and appropriate attribution must be given. This permission does not cover any third party copyrighted material which may appear in the work requested.In order to investigate how the use of robots may impact everyday tasks, 12 participants interacted with a University of Hertfordshire Sunflower robot over a period of 8 weeks in the university’s Robot House.. Participants performed two constrained tasks, one physical and one cognitive , 4 times over this period. Participant responses were recorded using a variety of measures including the System Usability Scale and the NASA Task Load Index . The use of the robot had an impact on the experienced workload of the participants differently for the two tasks, and this effect changed over time. In the physical task, there was evidence of adaptation to the robot’s behaviour. For the cognitive task, the use of the robot was experienced as more frustrating in the later weeks.Peer reviewedFinal Published versio

EEG-based mental workload neurometric to evaluate the impact of different traffic and road conditions in real driving settings

Car driving is considered a very complex activity, consisting of different concomitant tasks and subtasks, thus it is crucial to understand the impact of different factors, such as road complexity, traffic, dashboard devices, and external events on the driver’s behavior and performance. For this reason, in particular situations the cognitive demand experienced by the driver could be very high, inducing an excessive experienced mental workload and consequently an increasing of error commission probability. In this regard, it has been demonstrated that human error is the main cause of the 57% of road accidents and a contributing factor in most of them. In this study, 20 young subjects have been involved in a real driving experiment, performed under different traffic conditions (rush hour and not) and along different road types (main and secondary streets). Moreover, during the driving tasks different specific events, in particular a pedestrian crossing the road and a car entering the traffic flow just ahead of the experimental subject, have been acted. A Workload Index based on the Electroencephalographic (EEG), i.e., brain activity, of the drivers has been employed to investigate the impact of the different factors on the driver’s workload. Eye-Tracking (ET) technology and subjective measures have also been employed in order to have a comprehensive overview of the driver’s perceived workload and to investigate the different insights obtainable from the employed methodologies. The employment of such EEG-based Workload index confirmed the significant impact of both traffic and road types on the drivers’ behavior (increasing their workload), with the advantage of being under real settings. Also, it allowed to highlight the increased workload related to external events while driving, in particular with a significant effect during those situations when the traffic was low. Finally, the comparison between methodologies revealed the higher sensitivity of neurophysiological measures with respect to ET and subjective ones. In conclusion, such an EEG-based Workload index would allow to assess objectively the mental workload experienced by the driver, standing out as a powerful tool for research aimed to investigate drivers’ behavior and providing additional and complementary insights with respect to traditional methodologies employed within road safety research