Driver Acceptance of Unreliable Traffic Information in Familiar and Unfamiliar Settings

Abstract

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.

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Barry H. Kantowitz is chief scientist for the Battelle Human Factors Transportation Center in Seattle, Washington. He received a Ph.D. in psychology in 1969 from the University of Wisconsin.

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Richard J. Hanowski is a research scientist at the Battelle Human Factors Transportation Center. He received an M.S. in psychology from the University of Idaho in 1993.

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Susan C. Kantowitz is a research scientist at the Battelle Human Factors Transportation Center. She received an M.S. in developmental psychophysiology from Purdue University in 1975.