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Publication Number: FHWA-RD-96-145
Date: February 1998
Development of Human Factors Guidelines for Advanced Traveler Information Systems and Commercial Vehicle Operations: The Effects of Inaccurate Traffic Information on Driver Behavior and Acceptance of an Advanced In-Vehicle Traveler Information System
CHAPTER 4. DISCUSSION
The goal of this experiment was to provide an initial answer to two questions asked by ATIS designers:
(1) How reliable must traffic information be for motorists to trust and use it?
(2) How does the familiarity of the setting influence trust and use of unreliable traffic information?
Results showed for several dependent variables (e.g., penalty cost, trust, trust minus self–confidence) that while 100 percent accurate information yields best driver performance and subjective opinion, information that is 71 percent accurate remains acceptable and useful. Drivers are willing to tolerate some error in a simulated ATIS. However, when information accuracy drops to 43 percent, driver performance and opinion suffer. Thus, information accuracy above 71 percent is recommended to system designers. Future research is needed to evaluate information accuracy between 44 percent and 70 percent.
Drivers did not use simulated ATIS accurate information as effectively in the familiar setting as in the unfamiliar setting. Inaccurate traffic information was more harmful in the familiar setting. These results may imply that commercial success for in–vehicle ATIS will be easier to accomplish in unfamiliar settings, e.g., for use in rental vehicles for visitors, than in one's home city. Because drivers have greater self–confidence in familiar settings, they are more critical of ATIS advice and hold to a higher standard of user acceptability when they know the area geography. Thus, to achieve user acceptance, in–vehicle systems intended for purchase by a driver in a private passenger vehicle will likely have to meet higher standards than systems intended for commercial use.
Driver trust was decreased by inaccurate traffic information but recovered when accurate information was received. However, the more likely that information was inaccurate, the less the recovery. For the 43 percent accuracy condition, T–SC became negative, implying that drivers would prefer their own solutions to those offered by the simulated ATIS device. So, although drivers do not demand perfect traffic information, high degrees of inaccuracy will cause drivers to ignore system advice, especially in familiar settings.
It is interesting to compare present results with those of Bonsall and Parry (1991) and Allen et al. (1991) summarized in the Introduction. When familiarity is defined as knowledge of a local geography, we found that familiarity was harmful since penalty costs were higher; Allen et al. (1991) found no effect of familiarity. When familiarity is defined as learning over repeated trials, we found no decrement in driver trust over the first two repeated trials. However, penalty cost did decrease on the second trial. This conflicts with results of Bonsall and Parry who found drivers less likely to accept advice over repeated trials. Note that experiments using artificial networks to some extent necessarily confound familiarity with the traffic network and familiarity with the simulated ATIS device, since the network is learned by using the new device. While artificial networks can be useful microworlds for the ergonomics researcher, we believe that they are most useful when topographically matched to a real network as in this study.
Finally, we also note that this experiment manipulated information reliability in only one of several ways that might be meaningful to drivers. In this experiment, accuracy was based upon level of service. Drivers judged whether the actual level of service on a particular traffic link matched their expectations based upon information provided by the simulated ATIS. Other traffic dimensions may be equally salient for drivers. For example, Janssen and Van der Horst (1993) presented drivers in a simulator with length of congestion in kilometers, delays relative to normal travel times in minutes, and travel times in minutes. Reliability was manipulated by altering the variability of these estimates. They found that travel time information was most resistant to degradations in reliability. So the present results may not generalize to all of the possible formats and types of information traffic engineers can offer to drivers.