METHOD:
Participants
For this study, a subject pool of at least 120 subjects, with ages ranging from 16 to 80, would serve as ideal study subjects. A normal distribution of subjects across the age ranges should roughly be representative of the typical driving population.
Apparatus and stimuli
An arcades style driving game will be used to simulate driving conditions. A panoramic screen displaying 3D graphics will be used to present the visual stimuli, which includes balls rolling across the street as the driver approaches a park, followed by children darting onto the street in search for the ball; pedestrians running through a yellow light as one tries to turn left or right; a suddenly stalled car; a car ahead that suddenly blows it tire; a car changing lanes without signalling, sometimes cutting of the path of the subject; an approaching emergency vehicle such as a fire truck or ambulance, speeding towards the subject from behind or in front etc. A “screen-within-a-screen” will be displayed in the upper region of the stimulus screen to act as a rear view mirror.
Design and Procedures
There will be two sets of variables: cued versus uncued, and familiar versus unfamiliar, producing four total conditions. In all conditions, subjects are seated before the video screen, with a simulation steering wheel and pedals. Subjects must navigate through a 5 minute driving course through a typical downtown driving scene during hours of relatively high, but well-flowing traffic. They are given the task of backing out of the driveway, then drive to the mall, find a parking spot, park, back out, then return home. Throughout each drive for all conditions, 10 potentially dangerous situations are encountered at random intervals and locations. The subjects will be measured simply by their collision rate with the obstacles. To avoid gory visuals, collisions will cause the car to “pass through” the obstacle as it flashes in orange, rather than simulate blood and wrecked cars. Subjects in the cued condition, during the course of their “drive”, will be provided with flashing exogenous relevant cues 300ms ahead of their approach to the hazzardous situation ahead. For example, if a driver is required to turn left, and one of the obstacles is that a pedestrian suddenly runs through as the light is turning yellow, a red circle would flash and outline the pedestrian to signal to the driver to be more attentive. Subjects in uncued conditions will not be provided with any intervening information. In “familiar” conditions subjects are provided with maps of the 5 block x 5 block “city”, with all houses, building, stores, parks, and street names indicated. They are given 15 minutes to study and remember the map the best they can. The unfamiliar condition will have no benefit of maps. After completing the course once, all subjects will then be provided with the same task but with obstacles randomly distributed at different location. Finally a third trial involves the same task, but on a different city scene, with a different mapping. However, in the second and third trials, the subjects in the cued condition will no longer be provided with cues, but they shall not be informed of this. Familiar conditions subjects will still be given maps to study.
PREDICTED RESULTS and DISCUSSION:
After the first drive, it is predicted that subjects in the cued condition would have a significant advantage over the uncued subjects and commit less collisions. Also subjects in the familiar condition would do better as they are more familiar with the course and can devote more attention to obstacles rather than to looking for street signs. The second trial is given as additional practice to possibly develop an effect on the subjects, and if it exists, should be evident after the third trial. Thus scores for the second trial will be slightly better for all subjects due to practice. The group of focus after the third trial is the group that had cueing in the first and second trial, but no cueing in the third. The question here is whether or not these subjects do better now that they do not have any direct cues. It is predicted that these subjects will do poorer than they did in trial two, but should be roughly equal to or better than their score in trial one. Also comparative to the other conditions, they must still be significantly better. If this holds true, what it suggests is that subjects in the cued condition have learned to use the cues in and of themselves, rather than the circles, to note impending hazards in the road ahead. Thus practice trials that encourage subjects to actively monitor the presence of cues may improve driver attention to not-so-obvious cues.
This student is fully aware of the many limitations of this proposed study. First, there is a need for much more detailed controls, as well as more theoretical concepts must be operationally tested. This design although provides an interesting comparison, is weak at providing any theoretically significant results, and seems to confirm general intuitive understanding of attentional capture. One question that this study does not answer is how and why people are unable to be captured by some rather important cues. This student believes that in typical driving conditions day after day, people really do not encounter many obstacles, thus they are not well tuned in to the subtle cues that act as warnings for upcoming hazards. Perhaps this is why “tunnel vision” is fairly common. The act of driving is so automatic, that people often don’t remember if they had stopped at stop sign or not, but somehow passed an busy intersection safely, or that they had made a turn at all and yet are already almost halfway home. The hope of this project was to show that perhaps we can “undo” this automatic process. This is not to say that an automatic mechanism is a bad thing, for it does allow us to focus more attention on other things. However, when we “automatically” drive as though there are no hazards to worry about, our attention may be generally inhibited because we don’t think we need to attend to the periphery of the road. Through the use of a virtual driving experience, such as the one described here, it may be possible create a situation where highlighted cues that are normally subtle, are able to capture people’s attention–even once the highlighting is no longer present. This ability to capture relevant cues, then shares a critical feature with the hazard (by virtue of the fact that if will eventually cause the hazard). Thus this would be supportive of Folk et al.’s contingent involuntary orienting hypothesis, which stresses that attention can be improved by expanding the attentional set. If this optimistic study can possibly demonstrate any truth to these suggestions, then it may have positive implications for driver training that can improve road safety. However, it is also important to note that the financial obstacles to such a study such as this would be very large–but perhaps measly investment by one willing video game manufacturer may result in more riches for video game manufacturers everywhere.