Ensuring the transport process requires proper interaction of all parts of the system "driver - car - road - environment" and its subsystems. In this case, the driver is often a "weak" component of the system, and his actions can reduce the level of road users` safety. It should be noted that the reliability of the driver can be considered as the probability of his trouble-free and error-free operation, as well as the proper level of his regulatory mechanisms functioning. In this case, to analyze the activities and readiness of the driver for his professional activities, indicators of functional status are often used. Thus, the study of the "human factor" in the transport process is an important task to ensure the reliability of the whole transport system.
Today the most of all transportation is carried out by road. The timeliness and safety of cargo delivery and passenger safety depend on the driver's actions. At the same time, the driver is influenced by a considerable number of external environmental factors during his work. One of the most important factors is the mountainous traffic conditions, which often have many changes in plan and the profile of roads. Another feature of such traffic conditions is the height above sea level, affecting the human body, particularly its functional state.
Considering the above, the paper measures the heart rate variability of bus drivers moving on a route that was partly in the mountain's conditions. During the research, video recording and registration of the vehicle's geolocation were also carried out. This made it possible to establish indicators of the driver`s functional state in specific periods. After processing the obtained values, the influence of mountainous traffic conditions on the bus drivers` indicator of regulatory systems’ activity was established.
1. Pegin, P., & Pegina, O. (2018). A method to assess accident psychological severity in drivers. Transportation research procedia, Volume 36, 562-566. doi: 10.1016/j.trpro.2018.12.152 (in English) https://doi.org/10.1016/j.trpro.2018.12.152
2. Dolia, V. & Englezi, I. (2015). Determine the safe transport of dangerous goods route. Journal of Transport Problems”, Volume 10. 31 – 44. doi: 10.21307/tp-2015-004 (in English) https://doi.org/10.21307/tp-2015-004
3. Chen, J., Wang, H., Hua, C., Wang, Q., & Liu, C. (2018). Graph analysis of functional brain network topology using minimum spanning tree in driver drowsiness. Cognitive neurodynamics, 12(6), 569-581. (in English). https://doi.org/10.1007/s11571-018-9495-z
4. Maria, Rosaria De Blasiis, Selene Diana & Valerio, Veraldi (2018). Safety audit for weaving maneuver: A driver simulation safety analysis. Journal of Transportation Safety & Security, Volume 10. Issue 1-2. 159 – 175. doi: 10.1080/19439962.2017.1323060 (in English) https://doi.org/10.1080/19439962.2017.1323060
5. Prasolenko, O. (2019). Teoretychni osnovy ta praktychni metody vyznachennia nadiinosti diialnosti vodiia v mistakh u temnu poru doby [Theoretical frameworks and practical methods for determination of driver's reliability in cities at night]. Problemy z transportnymy potokamy i napriamy yikh rozviazannia: tezy dopovidei III Vseukrainskoi naukovo-teoretychnoi konferentsii [Problems with traffic flows and directions of their solution: abstracts of reports of the III All-Ukrainian scientific-theoretical conference] (pp. 129-132). (in Ukrainian)
6. Kantowitz, B. H., Hanowski R. J., & Kantowitz S. C. (2020). Driver reliability requirements for traffic advisory information. Ergonomics and safety of intelligent driver interfaces (pp. 1-22). (in English) https://doi.org/10.1201/9781003064107
7. Buendia, R., Forcolin, F., Karlsson, J., Arne Sjöqvist, B., Anund, A., & Candefjord, S. (2019). Deriving heart rate variability indices from cardiac monitoring - An indicator of driver sleepiness. Traffic injury prevention, Volume 20(3), 249-254. doi: 10.1080/15389588.2018.1548766 (in English) https://doi.org/10.1080/15389588.2018.1548766
8. Hiuliev, N., Lobashov, O., Shkabara, O., & Doroshenko, A. (2018). Shchodo vplyvu temperamentu vodiia na chas yoho reaktsii u dorozhnomu zatori [Regarding the influence of the driver's temperament on the time of his reaction in traffic jams]. Komunalne hospodarstvo mist. [Municipal economy of cities], Volume 140, 86-90. (in Ukrainian)
9. Gorelik, S., Grudinin, V., Lecshinskiy, V., & Khaskelberg, E. (2020). Method for assessing the influence of psychophysical state of drivers on control safety based on monitoring of vehicle movement parameters. Transportation research procedia, Volume 50, 152-159. doi: 10.1016/j.trpro.2020.10.019 (in English) https://doi.org/10.1016/j.trpro.2020.10.019
10. Studer, L., Paglino, V., Gandini, P., Stelitano, A., Triboli, U., Gallo, F., & Andreoni, G. (2018). Analysis of the relationship between road accidents and psychophysical state of drivers through wearable devices. Applied Sciences, Volume 8(8), 1230. doi: 10.3390/app8081230 (in English) https://doi.org/10.3390/app8081230
11. Lin, Wang, Hong, Wang, & Xin, Jiang. (2017). A new method to detect driver fatigue based on EMG and ECG collected by portable non-contact sensors. Promet – Traffic&Transportation, Volume 29, 479 – 488. doi: 10.7307/ptt.v29i5.2244 (in English) https://doi.org/10.7307/ptt.v29i5.2244
12. Murugan, S., Selvaraj, J., & Sahayadhas, A. (2020). Detection and analysis: driver state with electrocardiogram (ECG). Physical and engineering sciences in medicine, Volume 43(2), 525-537. doi: 10.1007/s13246-020-00853-8 (in English) https://doi.org/10.1007/s13246-020-00853-8
13. Lisun, Yu. B., & Uhlev, Ye. I. (2020). Variabelnist sertsevoho rytmu, vykorystannia ta metody analizu [Heart rate variability, use and methods of analysis]. Pain, anaesthesia & intensive care, Volume 4 (93), 83-89. doi: 10.25284/2519-2078.4(93).2020.220693 (in Ukrainian) https://doi.org/10.25284/2519-2078.4(93).2020.220693
14. Afonin, M. O. (2019). Vdoskonalennia tekhnolohichnykh protsesiv perevezennia nebezpechnykh vantazhiv z vrakhuvanniam faktora liudyny [The improvement of technological processes of dangerous goods transportation considering human factor]. Candidate’s thesis. Lviv: LPNU (in Ukrainian).
15. Barvinska, K., & Hrutsyn, О. (2020). Doslidzhennia zatrymky transportnoho potokuna nerehulovanykh perekhrestiakh z obmezhenoiu shvydkistiu [Investigation of transport flow delay at unsignalized intersections with limited speed]. Rozvytok transportu [Transport development], Volume 1 (6), 80-91. doi: 10.33082/td.2020.1-6.07 (in Ukrainian) https://doi.org/10.33082/td.2020.1-6.07
16. Lobashov, O. O., & Prasolenko, O. V. (2018). Vplyv kharakterystyk dorozhnoho rukhu na funktsionalnyi stan vodiia [Influence of traffic characteristics on the functional state of the driver]. Komunalne hospodarstvo mist. [Municipal economy of cities], Volume 7, 40-45. (in Ukrainian) https://doi.org/10.33042/2522-1809-2018-7-146-40-45
17. Gyulyev, N., & Dolia, C. (2017). The issue of probability of traffic road accident on the elements of the transport network. American Journal of Social Science Research, Volume 3(5), 17-24. (in English)
18. Furman, O. (2017). Hardware and software for road users functional state research. In Litteris et Artibus (pp. 287-288). (in English)
19. Karty vysoty [Altitude maps]. Retrieved from https://qrz.pp.ua/vysota (in Ukrainian).