Monday, October 14, 2019
A Model of Driving Tests Battery Validation
A Model of Driving Tests Battery Validation MARKUS SOMMER, GERNOT SCHUHFRIEDâËâ", MIHAI ANIÃâ¦Ã ¢EI, MIHAELA CHRAIFâËâ"âËâ" Abstract Designing a driving test battery is the most secure way to predict the driver behavior beforeà obtaining driver license. The objective is to design a psychological test battery to predict the drivingà behavior of the potential drivers. The participants were 106 persons, both male and female, ageà between 18 and 45 years old (M=34.4, 4; S.D. =1.32), different levels of education. The validityà criterion has been selected according the driving tasks during driving on the road. Thus, the value ofà 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. 1. INTRODUCTION First studies in simulated task environments have shown that quite a largeà part of the participants do not notice information that is not in accordance withà their expectations or when they do notice the information responses are delayedà (Martens, 2004; Martens Fox, 2003). This negative side of getting familiar withà a certain task environment might be the result of not spending enough time fixatingà the objects in the task environment. But this decrease in fixation times to objects inà the task environment once people get familiar with the environment has only beenà shown in computer-simulated environments. Drivers should question any driving skills test that does not include all theà test components as described in the appropriate study guide. In Table 1 can be seenà the required driving skills test components and the approximate time needed toà complete each. Thus the times are estimates based on an average length drivingà route, good weather conditions, light traffic and a well-prepared driver. Furthermoreà the same authors underline that skills tests must include all the segments listed inà 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 theà crossroads and others. These represents for the psychologists criteria in validationà of the driving tests baterry. Underlining the importance of visual functions in driving, such as acuity,à field, contrast, color and night vision can be measured as part of an eyeà examination. Functional vision includes performance of daily living skills, readingà ability, mobility skills and driving skills. In this way the measurement of visualà functions is often used as a substitute from which to estimate functional vision.à According to the visual standards (Colenbrander, A. De Laey, J.J., 2006), theà visual acuity is measured often, visual field sometimes and contrast sensitivityà rarely. The authors underline that estimating predicted driving performance on theà basis of a few parameters, many other factors, such as training, experience andà familiarity with the driving environment can affect the prediction. In this way theà authors present in Figure 1 particularities of vision related functioning. As it can be observed in Figure 1, the authors undeline that the driving testsà included into the tests battery has to predict the driving performances in traffic. Inà this way, they highlite that the driving safety does not depend so much on what isà seen, but rather on how quickly and how adequately drivers respond to what isà seen. So, is the moment when the time reaction tests has to be included into aà driving tests baterry. When human observers look at an optic flow stimulus their eye movementsà show a regular alternation of gaze shifts and slow tracking movements at aà frequency of about 2 Hz (Niemann, Lappe, Buscher Hoffmann, 1999; Lappe à Hoffmann, 2000).Many perceptual experiments have shown that heading can be perceivedà from optic flow (J.E. Cutting, P.M. Vishton, M. Flà ¼ckinger, B. Baumberger, andà J.D. Gerndt, 1997; Turano and X. Wang, 1994; Warren, D.R. Mestre, A.W.à Blackwell, and M.W. Morris, 1991; Stone and J.A. Perrone; 1997). They haveà identified important requirements for accurate analysis as well as sources of error. A particular concern are eye movements which are induced by optic flow andà which, by distorting the structure of the flow field projected in the eye, compromiseà heading detection. 2. THE OBJECTIVES, HYPOTHESYS, PARTICIPANTS The objective is focused to design a psychological test battery to predict theà 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 drivingà performances in traffic. The participants were 106 persons, both male and female, age betweenà 18 and 45 years old (M = 34.4, 4; S.D. = 1.32), different levels of education. Also,à the participants were driving school students tested at two driving schools fromà Bucharest. Organ structure Organ function Skills and abilities Societal consequenc. THE ORGAN THE PERSON Examples: Injury Degeneration Visual acuity Visual field Reading Mobility Employment Quality of Life ICIDH: Disorder Impairment Disability Handicap ICF: Body structure Body function Activities and Participation Barriers and Facilitators Vision: Visual Functions How the eye functions Functional Vision How the person functions DRIVING Acuity test Field test Contrast Driving ability test Driving in actual trafic Traffic conditions 246 Markus Sommer et al. 4 3. THE METHOD 3.1. THE INSTRUMENTS ââ¬â RT ââ¬â Reaction Test (Schuhfried, 2007). With the RT is it possible toà 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 differentà stimulus constellations for the measurement of reaction time can be created. Theseà can range from individual stimuli to simultaneous or sequentially presentedà stimulus combinations. The use of a rest key and a reaction key makes it possibleà to distinguish between reaction and motor time. ââ¬â Determination test (Schuhfried, 2007). The test is used to measure reactiveà stress tolerance and the associated ability to react and requires the respondent toà use his cognitive skills to distinguish different colors and sounds, to memorize theà relevant characteristics of stimulus configurations, response buttons and assignmentà rules, and to select the relevant responses according to the assignment rules laidà down in the instructions and/or learned in the course of the test. The difficulty ofà the DT arises from the need to sustain continuous, rapid and varying responses toà rapidly changing stimuli. ââ¬â Tachitoscopic test (Schuhfried, 2007). The ATAVT tests observationalà ability by briefly presenting pictures of traffic situations. The items are constructedà using an explicit, theory-led rationale which is based on detailed analysis of theà cognitive processes involved in working the test. The design of the ATAVT isà based on the principles used in the well-established TAVTMB test but builds onà these by taking account of recent research findings relating to the perception ofà scenes and objects. ââ¬â Visiotest-Stereoscopy. The Visiotest-Campitest with 6 visual acuity testsà and the extension of the peripheral visual field. For the research, only theà stereoscopic visual test was used. The test consist in a table with letters (A, B, C)à which for a person with stereoscopic vision appears at different distances.The correlation matrix from Table 3 reveal the statistically significantà correlations between the criterias and the predictors. Thus, the criteria right curve,à cross road correlate statistically significant and positive with the followingà predictors: tahitoscop corect (34**), DT corect (.27**), reaction time (.41**),à motor time (.32**). The same criteria correlate statistically significant and negativeà (p Taking in consideration the criteria stop to the pedestrian crossing from theà same Table 3, can be observed a statistically significant and positive correlationà between this criteria and the following predictors: DT corrrect (.38**), motor timeà reaction (.19*) and S.D. motor time (.17*). The same criteria correlate statisticallyà significant and negative with the following predictors: Viziotest-stereoscopyà (ââ¬â.42**), DT omitted (ââ¬â.41**) and tahito incorrect (ââ¬â.18*).Analizing the correlation between the criteria total performances in drivingà and the predictors can be observed a statistically significant and positiveà correlation with the following predictors: tahitoscop correct (.46**), DT correctà (.53**), reaction time (.38**), motor time (.42**), S.D. reaction time (.31**) andà S.D. motor time (.27**). The same criteria correlate statistically significant andà negative with the predictors: Viziotest-stereoscopy (ââ¬â.51**), DT omitte d (ââ¬â.27**)à and tahito incorrect (ââ¬â.32**). Applying the regression model for the criteria total performances in drivingà the following regresssion model had been obtained (5). Table 4 Summary 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, DTà omitted, TR motor time, S.D. reaction time, S.D. motor time, viziotest-stereoscopy;à b) Dependent variable: total performances in driving. Table 4 underlines an error reduction of the model with 55% and a strongà correlation between the independent variables and the criteria (0.742). Calculating the F value (23.29) the regression model have a strong predictiveà value for the criteria total performances in driving (p Continued driver training in the form of guided lifelong self-improvement activitiesà is essential for acquiring new skills (Sommer, Herle, Hausler, 2007). These newà skills are required as driving gets more complex with technology: car audioà devices, reading maps on screens, using computers, note taking, talking on phoneà or radio, GPS device. The Standard Quality Driving Curriculum needs to be keptà up-dated continuously and the latest additions are to be made available. These updatesà 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 comesà in the help of safety traffic and minimizing the accident probability to occur onlyà taking in consideration the criteria validity.
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