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Title: MICROMODEL FOR OBJECTIVE ESTIMATION OF DRIVER MENTAL WORKLOAD FROM TASK DATA
Accession Number: 00756064
Record Type: Component
Record URL: Availability: Transportation Research Board Business Office 500 Fifth Street, NW Find a library where document is available Abstract: Observation of driver performance during a 58,000-km (36,000-mi) field study of van pooling indicates that a good estimate of mental workload can be made from an analysis of objective performance data alone. Drivers traversed a mix of rural secondary roads, limited-access expressways, high-density, limited-access urban drives, and downtown city streets on a daily commute from upstate New York to New York City. Data included road characteristics, time, traffic density, speed, weather, brake applications, subsidiary task performance, and subjective difficulty ratings. Driving workload had two components, a steady-state load dictated by road conditions, speed, and traffic density and a transient load determined by the degree of uncertainty in the driving situation. Brake actuations represent the uncertainty inherent in driving while the log sub 2 of the speed is a first approximation of the steady-state information processing load imposed by tracking requirements of vehicle control. Unpredictability of traffic appeared to be the major determinant of perceived difficulty. Workload homeostasis occurred as drivers modified their performance to keep workload within a comfortable range. An objective workload index of the general form, workload = f (brake actuation rate + log sub 2 speed) based on this micromodel of driver behavior predicts subjective driving difficulty. An analysis of variance shows that the workload index distinguished between road types at the p < .0001 level of significance. The workload index correlates at r = .74, 18(df), with the subjective driving degrees of freedom difficulty ratings and at r = .81, 18 df, with the mental workload estimates of the best subsidiary task.
Supplemental Notes: This paper appears in Transportation Research Record No. 1631, Driver and Vehicle Modeling.
Language: English
Corporate Authors: Transportation Research Board 500 Fifth Street, NW Authors: Zeitlin, L RPagination: p. 28-34
Publication Date: 1998
Serial: ISBN: 0309065038
Features: Figures
(1)
; References
(44)
; Tables
(2)
TRT Terms: Uncontrolled Terms: Old TRIS Terms: Subject Areas: Highways; Safety and Human Factors; I83: Accidents and the Human Factor
Files: TRIS, TRB, ATRI
Created Date: Nov 2 1998 12:00AM
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