Perilaku Menyalip

Hartanto Hartanto

doi:10.22146/gamajop.46363

Perilaku Menyalip

Hartanto Hartanto

(Submitted 29 May 2019)

(Published 29 May 2019)

Abstract

Traffic accidents due to overtaking other vehicles can cause serious injuries and even death. This research attempted to explain the effect of spatial cognition in driver when decided to overtake by investigating the character (risk- taking and risk averse), visual types (fast and slow) and motorcycle types (manual, matic, and motor bebek). Twenty three people participated in the study. Participants conducted simulation on Psychopy. Three-way Anova was executed and resulted in 1) As predict with theory, risk taking subject more faster than risk averse (F = 8.083, p = 0.005). 2) There was significantly different effect among visual types (F = 16.459, p = 7.45e-05). 3) Interaction effect significant at factor character and visual types (F = 6.881, p=0.009). 4) Main interaction effect yield the same result (F = 7.774, p = 0.005). Average probabilities road accident naturally increased paralel with frequent intention to overtake. Moreover, high chance to overtake allegedly come with individu with character risk taking, fast visual search and driving bebek type of motor cycle.

Keywords

driving; spatial cognition; traffic psychology

Full Text: PDF

DOI: 10.22146/gamajop.46363

References

Ariana, P. D., & Hastjarjo, T. D., (2018). Pengaruh perhatian terbagi terhadap kesadaran situasi. Jurnal Psikologi Universitas Diponegoro, 17(1), 87-96. doi: 10.14710/jp.17.1.87-96

Balaguero, M. A., Vicente, M. J., Molina, A. G., Tormos, J. M., & Rovira, T. R. (2016). Balloon analogue risk task to assess decision-making in acquired brain injury. International Journal of Psychological Research, 9(1), 30-39. doi: 10.21500/20112084.2098

Bob, P. (2011). Brain, mind, and consciousness advances in neuroscience research. Germany: Springer Science + Business Media.

Cole, L. (2017). Commercial motor – operation safety. Diunduh dari commercialmotor.com

Eckstein, M, P. (2011). Visual search: A retrospective. Journal of Vision, 11 (5). doi: 10.1167/11.5.14

Fukunaga, R., Brown, J. W. & Bogg, T. (2012). Decision making in the Balloon Analogue Risk Task (BART): Anterior cingulate cortex signals loss-aversion but not the infrequency of risky choices. Cognitive Affective & Behavioral Neuroscience, 12(3), 479-90 doi: 10.3758/s13415-012-0102-1

Fukuda, K., & Vogel, E. K. (2009). Human variation in overriding attentional capture. Journal of Neuroscience, 29, 8726–8733.

Fuller, R. (2011). Driver control theory from task difficulty homeostasis to risk allostasis. In Porter, B. E. (Ed). Handbook of traffic psychology. (pp. 13-18). UK: Academic Press is an imprint of Elsevier.

Gastaldi, M., Rossi, R. & Gecchele, G. (2014). Effects of driver task-related fatigue on driving performance. Procedia - Social and Behavioral Sciences, 111, 955-964. doi: 10.1016/j.sbspro.2014.01.130.

Groot, K. D. & Thurik, R. (2018). Disentangling risk and uncertainty: When risk-taking measures are not about risk. Frontiers in Psychology, 9(2194). doi: 10.3389/fpsyg. 2018.02194

Rusmin, A. (2017). Angka kecelakaan lalu-lintas Indonesia termasuk tinggi di ASEAN. http://rri.co.id/post/berita/457518/sigap_polri/angka_kecelakaan_lalulintas_indonesia_termasuk_tinggi_di_asean.html diakses pada tanggal 9 Januari 2019.

Krause, F., & Lindemann, O. (2014). Expyriment: A Python library for cognitive and neuroscientific experiments. Behavior Research Methods, 46(2), 416-428.

Leather, N. C. (2009). Risk-taking behavior in adolescence: A literature review. Journal of Child Health Care, 13, 295-304. doi: 10.1177/13674935093337443

Lejuez, C. W., Richards, J. B., Read, J. P., Kahler, C. W., & Ramsey, S. E. (2002). Evaluation of a behavioral measure of risk taking: The Balloon Analogue Risk Task (BART). Journal of Experimental Psychology: Applied, 8(2), 75–84

Li, Q., Qiao, F., Wang, X., & Yu, L. (2017). Drivers' smart advisory system improves driving performance at STOP sign intersections. Journal of Traffic and Transportation Engineering (English Edition), 4(3), 262-271.

Ngueutsa, R., & Kouabenan, D. R. (2017). Accident history, risk perception and traffic safe behaviour. Ergonomics, 60(9), 1273-1282.

Ma, C., Hao, W., Xiang, W., & Yan, W. (2018). The impact of aggressive driving behavior on driver-injury severity at highway-rail grade crossings accidents. Journal of Advanced Transportation, 58, 1-10. doi: 10.1155/2018/9841498

Nugroho, S. A. (2018). Hari pertama simulasi uji psikologi SIM. https://otomotif.kompas.com/read/2018/06/21/180500315/hari-pertama-simulasi-uji-psikologi-sim diakses pada tanggal 10 Januari 2019.

Ott, B. R., Davis, J. D., Papandonatos, G. D., Hewitt S., Festa, E. K., Heindel, W. C., Snellgrove, C. A., & Carr, D. B. (2013). Assessment of driving-related skills prediction of unsafe driving in older adults in the office setting. Journal of the American Geriatrics Society, 61(7), 1164-1169. doi: 10.1111/jgs.12306.

Epub Pope, C. N., Bell, T. R., & Stavrinos, D. (2017). Mechanisms behind distracted driving behavior: The role of age and executive function in the engagement of distracted driving. Accident Analysis & Prevention, 98, 123–129. doi: 10.1016/j.aap.2016.09.030

Peirce, J., & MacAskill, M. (2018). Building experiments in PsychoPy. Perception, 48(2). doi: 10.1177/0301006618823976 R

Core Team. (2013). R: A language and environment for statistical computing, R foundation for statistical computing. Diunduh dari https://www.R-project.org

Smith, A. P. (2016). A UK survey of driving behaviour, fatigue, risk taking and road traffic accidents. BMJ Open, 6(8). doi: 10.1136/bmjopen-2016-01146

Stephens, A. N., & Groeger, J. A. (2012). Driven by anger: The causes and consequences of anger during virtual journeys. In Sullman, M. & Dorn, L. (Eds.). Advances in Traffc Psychology, 1-55. England: Ashgate Publishing Company.

Theeuwes, J. (2018). Visual selection: Usually fast and automatic; seldom slow and volitional; A reply to commentaries. Journal of Cognition, 1(1), 21. doi: 10.5334/joc.32

Trif, V. (2015). Spatial cognition: Theoritical considerations. Procedia – Social and Behavioral Sciences, 187, 168-172.

Van Rossum, (1995). Python founder, Technical report CS-R9526, Centrum voor Wiskunde en Informatica (CWI).

Amsterdam. Wali, B., Ahmed, A., Iqbal, S., & Hussain, A. (2017). Effectiveness of enforcement levels of speed limit and drink driving laws and associated factors e Exploratory empirical analysis using a bivariate ordered probit model. Journal of Traffic and Transportation Engineering (English Edition), 4(3), 272-279. doi: 10.1016/j.jtte.2017.04.001

Walshe, E. A. I., McIntosh, C.,W., Romer,D. I & Flaura K. Winston, F. K. (2017). Executive function capacities, negative driving behavior and crashes in young drivers. International Journal of Environmental Research and Public Health, 14(11). doi: 10.3390/ijerph14111314

Wickham, H. (2016). Ggplot2: Elegant graphics for data analysis. New York: Springer-Verlag. http://ggplot2.org

Wolfe, J. (2018). Visual search. In Wixted, J. T. & Serences, J. T. (Eds.), Stevens’ handbook of experimental psychology and cognitive neuroscience (pp 569-624), Fourth edition. New York : John Wiley & Sons, Inc.

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