This article describes a new approach in developing computational driver models in vehicle simulations for evaluating intelligent driving support systems (IDSSs). As IDSSs become more intelligent and provide active safety controls, a more comprehensive understanding of a driver's cognitive processes is required as well as vehicle dynamics. One hundred thirty drivers participated in a psychophysical experiment of velocity estimation at 71 checkpoints on a road section. The perceived velocity, as a dependent variable, was modeled using analysis of covariance (ANCOVA) with respect to the driver's fundamental human factors (i.e., age, gender, and driving experience) as independent variables. As a result, eight different perceived velocity models were defined as part of the cognitive processes with quantitative covariates in different modalities (i.e., radius of road, level of interior noise, as well as vehicle velocity). Moreover, driver models implemented with different perceptual processes also exhibited considerable changes in the results of vehicle simulations on double lane change maneuvers. The results presented in this study suggest that defining the perceptual processes of different groups of drivers is an essential process in developing vehicle simulation environments for evaluating IDSS. Consequently, the results from this study may provide meaningful data for early stages of new vehicle design. C 2010 Wiley Periodicals, Inc.
, mypark a(hanyang.ac.kr Cognitive attention conditions of multimedia system users were represented by simple operations of two vector sets: stimulus and human information processing channels. A vector-set model illustrated how humans use cognitive attention resources. A comprehensive psychophysical scaling system (MMES) has been designed to measure subjective multidimensional human perception. Unlike paperbased magnitude estimation systems, the MMES has an additional auditory peripheral cue that varies with corresponding visual magnitude. As the simplest, purely psychological case, bimodal dividedattention conditions were simulated to establish the superiority of the MMES. Subjects were given brief presentations of pairs of simultaneous stimuli consisting of visual line-lengths and auditory white-noise levels. In the visual or auditory focused-attention conditions, only the line-lengths or the noise levels perceived should be reported respectively; on the other hand, in the divided-attention conditions, both the line-lengths and the noise levels should be reported. There were no significant differences among the different attention conditions (no divided-attention decrement). Human performance was better when the proportion of magnitude in stimulus pairs were identically presented (cross-modal congruity effect). The additional auditory cues in the MMES improved the correlations between the magnitude of stimuli and MMES values in the divided-attention conditions.
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