Suchergebnisse

Selecting measures is a necessary component of human factors research. Proper selection must take into account the representation problem (how is the assignment of numbers to objects or phenomena justified?) and the uniqueness problem (to what degree is this assignment unique?). Other key human factors measurement issues include subject representativeness, variable representativeness, and setting representativeness. It is difficult to create a single measure that captures essential characteristics of complex systems. Several examples illustrate how theory can guide measurement selection in such diverse human factors research as vigilance, turning off warning alarms, information requirements for military command centers, subjective workload, heart-rate signal analysis, and heat stress in nuclear power plants.

Problems associated with scaling and normalizing empirical performance operating characteristics (POCs) are examined. Normalization methods proposed by Wickens (1980) and by Mountford and North (1980) are critically evaluated. Computer simulations are used to generate raw-score and normalized POCs. The interpretation of transformed empirical POCs (Wickens, Mountford, and Schreiner, 1981) is shown 10 contain inconsistencies. The normalization techniques reviewed fail to resolve POC scaling problems. Caution must be exercised when interpreting transformed POCs.

How reliable must traffic information be for motorists to trust and accept such advice? This study provides data to aid the designer of advanced traveler information systems (ATIS) in selecting an appropriate level of system accuracy. The Battelle Route Guidance Simulator was used to study the effects of information accuracy and familiarity of the driving environment on objective and subjective indices of driver performance and opinion. The simulator provided real-time information and traffic video. Information was 100%, 71%, or 43% accurate. Drivers experienced either Seattle and its environs or an artificial setting that was topologically matched to Seattle. Results showed that 100% accurate information yielded the best driver performance and subjective opinion, information that was 71% accurate was still accepted and used, but information that was 43% accurate produced powerful decrements in performance and opinion. Simulated ATIS information was not used as effectively in the familiar Seattle setting. Driver trust decreased with inaccurate information but recovered---though not always fully---with subsequent accurate information.

In a likelihood alarm display (LAD) information about event likelihood is computed by an automated monitoring system and encoded into an alerting signal for the human operator. Operator performance within a dual-task paradigm was evaluated with two LADs: a color-coded visual alarm and a linguistically coded synthetic speech alarm. The operator's primary task was one of tracking; the secondary task was to monitor a four-element numerical display and determine whether the data arose from a "signal" or "no-signal" condition. A simulated "intelligent" monitoring system alerted the operator to the likelihood of a signal. The results indicated that (1) automated monitoring systems can improve performance on primary and secondary tasks; (2) LADs can improve the allocation of attention among tasks and provide information integrated into operator decisions; and (3) LADs do not necessarily add to the operator's attentional load.