Combination of unsatisfactory psychophysiological parameters as a marker of driver accident risk
Abstract
Background. The high rate of road accidents necessitates the development of novel approaches to enhance road safety. A promising direction is the diagnostic assessment of the psychophysiological preparedness of pre-drivers for improving parameters critical for safe road traffic. Aims: the study aimed to identify pre-drivers who are potentially dangerous from a psychophysiological perspective during their training stage and develop effective methods for training their psychophysiological parameters to improve the overall competency of driving school graduates. Materials and methods. From 2022 to 2024, psychophysiological testing was conducted on a cohort of three thousand pre-drivers, comprising students of the Mustang driving school and drivers undergoing rehabilitation and skill-refresher courses, irrespective of age and gender. Primary psychophysiological indicators were assessed using the UPDK-MK Avtomobilny system (ZAO “Neyrokom”). The resulting data were processed and analyzed according to the author's methodology. Results. The findings showed that a combination of unsatisfactory values across specific psychophysiological parameters had a significant negative correlation with an individual’s capacity for safe driving. Such drivers were either reluctant to drive after completing their training or were involved in traffic accidents with a higher frequency. Conclusion. Timely diagnosis and targeted training of psychophysiological preparedness are essential for enhancing the quality of driver education and improving road safety.
Downloads
References
2. Petrenko N.V. Psychophysiology of work and professional selection of drivers. Tekhnosfernaya bezopasnost = Technosphere safety. 2017;2:91–98. (in Russ.).
3. Yanuchkova O.E. Improving road safety in the context of professional selection of drivers taking into account psychophysiological qualities. Intellekt. Innovatsii. Investitsii = Intellect. Innovations. Investments. 2022;6:135–145. (in Russ.). DOI: 10.25198/2077-7175-2022-6-135.
4. Maslyuk V.V. Psychophysiological examination of drivers – European experience. Vestnik Kharkovskogo natsionalnogo avtomobilno-dorozhnogo universiteta = Bulletin of the Kharkiv Na-tional Automobile and Road University. 2014;61-62:131–136. (in Russ.).
5. Nikolaev R.V. The Impact of Human Factors on Road Safety. Tekhnika i tekhnologiya transporta = Technique and Technology of Transport. 2018;2:1–7. (in Russ.).
6. Prokhorova A.M. Use of psychophysiological and psychological indicators in professional selection of drivers engaged in passenger and cargo transportation. Sovremennaya nauka = Modern science. 2020;2:53–58. (in Russ.). DOI: 10.53039/2079-4401.2020.2.2.014
7. Mukhin E.M., Prokhorova A.M., Spirin M.E. et al. The influence of psychophysiological characteristics of drivers with up to three years of driving experience on their violations of traffic rules and road accidents. Vestnik Kemerovskogo gosudarstvennogo universiteta = Bulletin of Kemerovo state university. 2013;3:8–12. (in Russ.).
8. Barría C., Guevara C.A., Jimenez-Molina A. et al. Relating emotions, psychophysiological indicators and context in public transport trips: Case study and a joint framework for data collection and analysis. Transportation Research Part F: Traffic Psychology and Behaviour. 2023;95:413–431. DOI: 10.1016/j.trf.2023.05.002
9. Tao X., Gao D., Zhang W. et al. A multimodal physiological dataset for driving behaviour analysis. Scientific data. 2024;11(1):1–21. DOI: 10.1038/s41597-024-03222-2
10. Jimenez-Molina A., Diaz-Guerra F., Retamal C. et al. Towards Psychophysiological Markers for Affect-Aware Vehicles. Lecture Notes in Networks and Systems. 2022;594:571–582. DOI: 10.1007/978-3-031-21333-5_58.
11. Lazarou E., Exarchos T.P. Predicting stress levels using physiological data: Realtime stress prediction models utilizing wearable devices. AIMS Neuroscience. 2024;11(2):76–102. DOI: 10.3934/Neuroscience.2024006.
12. Ni J., Chen J., Xie W. et al. The impacts of the traffic situation, road conditions, and driving environment on driver stress: A systematic review. Transportation Research Part F: Traffic Psychology and Behaviour. 2024;103:141–162. DOI: 10.1016/j.trf.2024.04.006.
13. Li W., Li G., Tan R. et al. Review and Perspectives on Human Emotion for Connected Automated Vehicles. Automotive Innovation. 2024;7;1:4–44. DOI: 10.1007/s42154-023-00270-z.
14. Miller J.A., Nikan S., Zaki M.H. Navigating the Handover: Reviewing Takeover Requests in Level 3 Autonomous Vehicles. IEEE Open Journal of Vehicular Technology. 2024:1–16. DOI: 10.1109/OJVT.2024.3443630.
15. Bergomi M., Vivoli G., Rovesti S. et al. Role of some psycho-physiological factors on driving safety. Annali di Igiene: Medicina Preventiva e di Comunità. 2010;22(5):387–400.
16. Piccinin L., Leoni J., Villa E. et al. Learning-based estimation of operators psycho-physiological state. Expert Systems with Applications. 2025;276(1-4):127097. DOI: 10.1016/j.eswa.2025.127097.
17. Mitin I.N. Psychophysiological factor of road safety. Okhrana truda i tekhnika bezopasnosti na avtotransportnykh predpriyatiyakh i v transportnykh tsekhakh = Occupational health and safety at motor transport enterprises and in transport workshops. 2017;5-6:53–63. (in Russ.).
18. Sharmin S., Ivan J.N., Marsh K.L. et al. Driver Psychology Latent Classes as Predictors of Traffic Incident Occurrence in Naturalistic Driving Study Data. Transportation Research Record. 2022;2267:839-857. DOI: 10.1177/03611981221108985.
19. Gershon P., Sita K.R., Zhu C. et al. Distracted driving, visual inattention, and crash risk among teenage drivers. American Journal of Preventive Medicine. 2019;56(4):494–500. DOI: 10.1016/j.amepre.2018.11.024.
20. Cunningham M.L., Regan M.A. Driver distraction and inattention. Transport and Sustainability. 2018;11:57–82. DOI: 10.1108/S2044-9941201811.
21. Bulynko O.V. Perception of the road situation as a factor in traffic safety Vestnik universiteta grazhdanskoi zashchity MChS Belarusi = Vestnik of the Institute for Command Engineers of the MES of the Republic of Belarus. 2019;3;1:67–72. (in Russ.).
References on translit
-Copyright (c) 2025 Psychology. Psychophysiology

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

