Nowadays, the transport industry plays an important role in human well-being and the functioning of any settlement. Transport systems are involved in almost all areas of production and services. Therefore, any failure in its operation can lead to significant material costs. One of the most important such systems is “driver – vehicle – road – environment”. It should be noted, that the main link in it is “driver”. The correctness and duration of decision-making in different road situations depend on the driver`s functional state. This directly affects the level of traffic safety. Consequently, the tasks of modern transport research are the introduction of methods of the vehicle driver`s conditions monitoring and the detection of his fatigue in its early stages. That`s why the actuality of studying the human operator role in the transport process and the creation of modern means of driving assistance are increasing now.
1. Stepanov O. V. (2015). Vplyv psykholohichnoho chynnyka liudyny na bezpeku systemy "Vodii - Avtomobil - Doroha - Seredovyshche" [Impact of psychological human factor on safety of the Driver - Automobile - Road - Environment system]. Teoriia i praktyka upravlinnia sotsialnymy systemamy [The theory and practice of social systems management], Volume 4, 85 - 93. (in Ukrainian).
2. Braun, M., & Serres, K. (2017, September). Asam: an emotion sampling method for the automotive industry. Proceedings of the 9th International Conference on Automotive User Interfaces and Interactive Vehicular Applications Adjunct, 230-232. (in English).
https://doi.org/10.1145/3131726.3132044
3. Thomas M. Gable, Andrew L. Kun, Bruce N. Walker, & Riley J. Winton (2015). Comparing heart rate and pupil size as objective measures of workload in the driving context: initial look. Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI '15). Association for Computing Machinery, New York, NY, USA. 20 - 25. doi: 10.1145/2809730.2809745 (in English).
https://doi.org/10.1145/2809730.2809745
4. Hill, J. D., & Boyle, L. N. (2007). Driver stress as influenced by driving maneuvers and roadway conditions. Transportation Research Part F: Traffic Psychology and Behaviour, 10(3), 177-186 (in English).
https://doi.org/10.1016/j.trf.2006.09.002
5. Bock, F., Siegl, S., Bazan, P., Buchholz, P., & German, R. (2018). Reliability and test effort analysis of multi-sensor driver assistance systems. Journal of Systems Architecture, 85, 1-13. doi: 10.1016/j.sysarc.2018.01.006 (in English).
https://doi.org/10.1016/j.sysarc.2018.01.006
6. Hiuliev N. U. (2016). Liudskyi faktor i dorozhni zatory [Human factor and traffic congestion]. Kharkiv: O.M. Beketov NUUE (in Ukrainian).
7. Wilson, G. F., & Russell, C. A. (2003). Operator functional state classification using multiple psychophysiological features in an air traffic control task. Human Factors, 45(3), 381-389. doi : 10.1518/hfes.45.3.381.27252 (in English)
https://doi.org/10.1518/hfes.45.3.381.27252
8. Kuznetsov, A., Mutaeva, I., & Kuznetsova, Z. (2017). Diagnostics of functional state and reserve capacity of young athletes' organism. In icSPORTS, 111-114. doi: 10.5220/0006513901110114 (in English).
https://doi.org/10.5220/0006513901110114
9. Prasolenko, O., Burko, D., & Halkin, A. (2017). Galvanic skin response as a estimation method of the driver's emotional state. American Journal of Science, Engineering and Technology, 2(1), 50-56. (in English).
10. Prasolenko, О., Lobashov, O., & Galkin, A. (2015). The human factor in road traffic city. International Journal of Automation, Control and Intelligent Systems, 1(3), 77-84. (in English).
11. Postranskyy T. M. (2015). Metodyka doslidzhennia funktsionalnoho stanu vodiiv transportnykh zasobiv [Methods of the vehicle driver's functional state investigation]. Naukovo-vyrobnychyi zhurnal «Avtoshliakhovyk Ukrainy» [Scientific and Industrial Journal "The Avtoshliakhovyk Ukrayiny"], Volume 3, 30-34. (in Ukrainian).
12. Wang F. (2014). Comprehensive Analysis of Fatigue Driving Based on EEG and EOG. Journal of Northeastern University, 175-178 (in English).
13. Singh, R. K., Sarkar, A., & Anoop, C. S. (2016, May). A health monitoring system using multiple non-contact ECG sensors for automotive drivers. IEEE International Instrumentation and Measurement Technology Conference Proceedings, 1-6. doi: 10.1109/I2MTC.2016.7520539 (in English).
https://doi.org/10.1109/I2MTC.2016.7520539
14. Zontone, P., Affanni, A., Bernardini, R., Piras, A., & Rinaldo, R. (2019, September). Stress detection through electrodermal activity (EDA) and electrocardiogram (ECG) analysis in car drivers. 27th European Signal Processing Conference (EUSIPCO), 1-5. doi : 10.23919/EUSIPCO.2019.8902631 (in English).
https://doi.org/10.23919/EUSIPCO.2019.8902631
15. Prykhodko V., & Chernykh V. (2019). Vyznachennia rivnia uvahy ta indeksu napruzhennia vodiia v laboratornykh umovakh v rizni periody doby [Determining the attention level by the functional indicator of the stress index in different periods of day]. Problemy z transportnymy potokamy i napriamy yikh rozviazannia. III vseukrainska naukovo-teoretychna konferentsia [Problems with traffic flows and directions of their connection. III Ukrainian scientific-theoretical conference], 134-136. (in Ukrainian).
16. Medychne obladnannya [Medical equipment]. Retrieved from https://xai-medica.com/ua/equipments.html (in Ukrainian).