Re-Assessment of Driving Simulators for the Training, Testing and Licensing of Commercial Vehicle Drivers

Simulators have been successfully employed within the military sector and commercial airline industry for over 30 years. Simulation technology may supplement the training, testing, and licensing of commercial motor vehicle (CMV) drivers if its value can be sufficiently demonstrated. The Federal Motor Carrier Safety Administration is planning to conduct a simulation validation (“Sim Val”) study in fiscal year 2002 (FY 2002) to do just that. In April 1996, FMCSA (the-then Federal Highway Administration) published a research report which discussed the availability and performance of truck driving simulators available at that time. The research indicated that the truck simulators were sufficiently mature to conduct a validation study. Thus the FMCSA developed and publish Sim Val Research Design (May 1999). Given breakthroughs in technology in recent years and to gain a better understand of the functionalities of the truck simulator currently available, FMCSA is conducting a truck simulator reassessment. To help accomplish this work, FMCSA engaged Veridian Engineering. This paper describes the interim results of the reassessment of truck simulators to ascertain their performance and functionalities in support of the FMCSA SimVal Program. NOTE: This paper contains interim assessments of the simulators discussed. The interim assessments, made by Veridian Engineering and the Expert Team, were reviewed and approved by the respective vendors. Final assessments will be contained in the FMCSA final report

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Airplane Upset Training Evaluation Report

Airplane upset accidents are a leading factor in hull losses and fatalities. This study compared five types of airplane-upset training. Each group was composed of eight, non-military pilots flying in their probationary year for airlines operating in the United States. The first group, 'No aero / no upset,' was made up of pilots without any airplane upset training or aerobatic flight experience; the second group, 'Aero/no upset,' of pilots without any airplane-upset training but with aerobatic experience; the third group, 'No aero/upset,' of pilots who had received airplane-upset training in both ground school and in the simulator; the fourth group, 'Aero/upset,' received the same training as Group Three but in addition had aerobatic flight experience; and the fifth group, 'In-flight' received in-flight airplane upset training using an instrumented in-flight simulator. Recovery performance indicated that clearly training works - specifically, all 40 pilots recovered from the windshear upset. However few pilots were trained or understood the use of bank to change the direction of the lift vector to recover from nose high upsets. Further, very few thought of, or used differential thrust to recover from rudder or aileron induced roll upsets. In addition, recovery from icing-induced stalls was inadequate

A taxonomy of independent variables affecting human performance

As part of an ongoing program to develop a Computer Aided Engineering (CAE) system for human factors engineers, a Human Performance Expert System, Human, was designed. The system contains a taxonomy of independent variables which affect human performance. This taxonomy was developed in a three-step process: (1) review existing taxonomies; (2) add independent variables used in Human; and (3) remove redundancy and ambiguity. This process and the resultant taxonomy are described in this paper

Evaluation of algorithms for combining independent data sets in a human performance expert system

As part of an ongoing program to develop a Computer Aided Engineering (CAE) system for human factors engineers, a Human Performance Expert System, Human, was designed. The system contains a large database of human-performance equations derived from human performance research reported in the open literature. Human accesses these data to predict task performance times, task completion probabilities, and error rates. A problem was encountered when multiple independent data sets were relevant to one task. For example, a designer is interested in the effects of luminance and font size on a number of reading errors. Two data sets exist in the literature: one examining the effects of luminance, the other, font size. The data in the two sets were collected at different locations with different subjects, and at different times in history. How can the two data sets best be combined to address the designer's problems? On the basis of an extensive review of the human performance literature and statistical procedures, four combining algorithms were developed. These four algorithms were tested in two steps. In step one, two reaction-time experiments were conducted: one to evaluate the effect of the number of displays being monitored. The four algorithms were used on the data from these two experiments to predict reaction time in the situation where all three independent variables are manipulated simultaneously. In step two of the test procedure, a third experiment was conducted. Subjects who had not participated in either Experiment 1 or 2 performed a reaction-time task under the combined effects of all three independent variables. The predictions made from step one were compared to the actual empirical data collected in Experiment 3. The best predictor of the mean in Experiment 3 was an unweighted average of the means in Experiments 1 and 2; the best predictor of the standard deviation in Experiment 3 was an unweighted average of the standard deviations, (S.D.s) in Experiments 1 and 2. Based on these results, Human uses an average of the means to combine the results from multiple independent data sets

Women’s Leadership in HF/E: Past, Present and Future

The objective of this panel is to discuss professionalism and leadership in human factors and ergonomics, namely as they pertain to women in the field. As part of this panel, we aim to provide opportunities and guidance for extending the representation of women in leadership roles throughout the field. The panel will be led by Gabriella Hancock and Kimberly Stowers who will introduce the panel and its role in the HF/E Women’s Organization for Mentoring and Networking’s larger campaign to foster professional development for future leaders. Panelists will offer their unique perspective(s) on leadership and professional development leveraging their diverse training(s), experiences, career paths, and perspectives on leadership. Members of the audience are encouraged to come prepared with questions for panelists to better learn the panelists’ thoughts, opinions, and strategies concerning what could and should be done to encourage female leadership in the future. Drs. Hancock and Stowers will foster discussion amongst the panelists, and invite questions and participation from the general audience