A Model of Driving Tests Battery Validation

20 Apr 2018

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Designing a driving test battery is the most secure way to predict the driver behavior before obtaining driver license. The objective is to design a psychological test battery to predict the driving behavior of the potential drivers. The participants were 106 persons, both male and female, age between 18 and 45 years old (M=34.4, 4; S.D. =1.32), different levels of education. The validity criterion has been selected according the driving tasks during driving on the road. Thus, the value of the test reveals the fact that the model has a strong predictive value for the chosen criteria.

Key words: criteria, predictors, tachitoscopic test, determination test.


First studies in simulated task environments have shown that quite a large part of the participants do not notice information that is not in accordance with their expectations or when they do notice the information responses are delayed (Martens, 2004; Martens & Fox, 2003). This negative side of getting familiar with a certain task environment might be the result of not spending enough time fixating the objects in the task environment. But this decrease in fixation times to objects in the task environment once people get familiar with the environment has only been shown in computer-simulated environments.

Drivers should question any driving skills test that does not include all the test components as described in the appropriate study guide. In Table 1 can be seen the required driving skills test components and the approximate time needed to complete each. Thus the times are estimates based on an average length driving route, good weather conditions, light traffic and a well-prepared driver. Furthermore the same authors underline that skills tests must include all the segments listed in 

Table 1. In this way a test may take more time than shown in this table, but should

Also the guide underline the procedures of taking curves, entering into the crossroads and others. These represents for the psychologists criteria in validation of the driving tests baterry.

Underlining the importance of visual functions in driving, such as acuity, field, contrast, color and night vision can be measured as part of an eye examination. Functional vision includes performance of daily living skills, reading ability, mobility skills and driving skills. In this way the measurement of visual functions is often used as a substitute from which to estimate functional vision. 

According to the visual standards (Colenbrander, A. & De Laey, J.J., 2006), the visual acuity is measured often, visual field sometimes and contrast sensitivity rarely. The authors underline that estimating predicted driving performance on the basis of a few parameters, many other factors, such as training, experience and familiarity with the driving environment can affect the prediction. In this way the authors present in Figure 1 particularities of vision related functioning.

As it can be observed in Figure 1, the authors undeline that the driving tests included into the tests battery has to predict the driving performances in traffic. In this way, they highlite that the driving safety does not depend so much on what is seen, but rather on how quickly and how adequately drivers respond to what is seen. So, is the moment when the time reaction tests has to be included into a driving tests baterry.

When human observers look at an optic flow stimulus their eye movements show a regular alternation of gaze shifts and slow tracking movements at a frequency of about 2 Hz (Niemann, Lappe, Buscher & Hoffmann, 1999; Lappe & Hoffmann, 2000).Many perceptual experiments have shown that heading can be perceived from optic flow (J.E. Cutting, P.M. Vishton, M. Flückinger, B. Baumberger, and J.D. Gerndt, 1997; Turano and X. Wang, 1994; Warren, D.R. Mestre, A.W. 

Blackwell, and M.W. Morris, 1991; Stone and J.A. Perrone; 1997). They have identified important requirements for accurate analysis as well as sources of error.

A particular concern are eye movements which are induced by optic flow and which, by distorting the structure of the flow field projected in the eye, compromise heading detection.


The objective is focused to design a psychological test battery to predict the driving behavior of the potential drivers in the way of decreasing the accident risk.

The independent variables of the tests baterry are predictors for the driving performances in traffic.

The participants were 106 persons, both male and female, age between 18 and 45 years old (M = 34.4, 4; S.D. = 1.32), different levels of education. Also, the participants were driving school students tested at two driving schools from Bucharest.





Skills and





Examples: Injury


Visual acuity

Visual field




Quality of Life

ICIDH: Disorder Impairment Disability Handicap

ICF: Body




Activities and


Barriers and


Vision: Visual Functions How

the eye functions

Functional Vision How the person



Acuity test

Field test





Driving in





246 Markus Sommer et al. 4



– RT – Reaction Test (Schuhfried, 2007). With the RT is it possible to measure reaction time as both a simple choice and a multiple-choice reaction.

Yellow light stimulus modalities are available in the test battery, so that different stimulus constellations for the measurement of reaction time can be created. These can range from individual stimuli to simultaneous or sequentially presented stimulus combinations. The use of a rest key and a reaction key makes it possible to distinguish between reaction and motor time.

– Determination test (Schuhfried, 2007). The test is used to measure reactive stress tolerance and the associated ability to react and requires the respondent to use his cognitive skills to distinguish different colors and sounds, to memorize the relevant characteristics of stimulus configurations, response buttons and assignment rules, and to select the relevant responses according to the assignment rules laid down in the instructions and/or learned in the course of the test. The difficulty of the DT arises from the need to sustain continuous, rapid and varying responses to rapidly changing stimuli.

– Tachitoscopic test (Schuhfried, 2007). The ATAVT tests observational ability by briefly presenting pictures of traffic situations. The items are constructed using an explicit, theory-led rationale which is based on detailed analysis of the cognitive processes involved in working the test. The design of the ATAVT is based on the principles used in the well-established TAVTMB test but builds on these by taking account of recent research findings relating to the perception of scenes and objects.

– Visiotest-Stereoscopy. The Visiotest-Campitest with 6 visual acuity tests and the extension of the peripheral visual field. For the research, only the stereoscopic visual test was used. The test consist in a table with letters (A, B, C) which for a person with stereoscopic vision appears at different distances.The correlation matrix from Table 3 reveal the statistically significant correlations between the criterias and the predictors. Thus, the criteria right curve, cross road correlate statistically significant and positive with the following predictors: tahitoscop corect (34**), DT corect (.27**), reaction time (.41**), motor time (.32**). The same criteria correlate statistically significant and negative (p < 0.05) with the following predictors: viziotest-stereoscopy (–.34**), Dt omitted (–.23**), and tahito incorect (–.59*).

Taking in consideration the criteria stop to the pedestrian crossing from the same Table 3, can be observed a statistically significant and positive correlation between this criteria and the following predictors: DT corrrect (.38**), motor time reaction (.19*) and S.D. motor time (.17*). The same criteria correlate statistically significant and negative with the following predictors: Viziotest-stereoscopy (–.42**), DT omitted (–.41**) and tahito incorrect (–.18*).Analizing the correlation between the criteria total performances in driving and the predictors can be observed a statistically significant and positive correlation with the following predictors: tahitoscop correct (.46**), DT correct (.53**), reaction time (.38**), motor time (.42**), S.D. reaction time (.31**) and S.D. motor time (.27**). The same criteria correlate statistically significant and negative with the predictors: Viziotest-stereoscopy (–.51**), DT omitted (–.27**) and tahito incorrect (–.32**).

Applying the regression model for the criteria total performances in driving the following regresssion model had been obtained (5).

Table 4


Model R R Square Adjusted R square

1 0.742 0.550 0.526

a) Predictors: (Constant), tahitoscop correct, tahitoscop incorrect, DT correct, DT incorrect, DT omitted, TR motor time, S.D. reaction time, S.D. motor time, viziotest-stereoscopy; b) Dependent variable: total performances in driving.

Table 4 underlines an error reduction of the model with 55% and a strong correlation between the independent variables and the criteria (0.742).

Calculating the F value (23.29) the regression model have a strong predictive value for the criteria total performances in driving (p < 0.001).Obtaining a driver’s license cannot be considered the end of driver training.

Continued driver training in the form of guided lifelong self-improvement activities is essential for acquiring new skills (Sommer, Herle, Hausler, 2007). These new skills are required as driving gets more complex with technology: car audio devices, reading maps on screens, using computers, note taking, talking on phone or radio, GPS device. The Standard Quality Driving Curriculum needs to be kept up-dated continuously and the latest additions are to be made available. These updates are to focus on new developments that technology brings to vehicles and roads, all of which require the acquisition of new skills by drivers.

The research finding reveal that designing psychological test batteries comes in the help of safety traffic and minimizing the accident probability to occur only taking in consideration the criteria validity.

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