Please use this identifier to cite or link to this item: http://ena.lp.edu.ua:8080/handle/ntb/51082
Title: Changing of the bus driver`s functional state in city conditions
Authors: Postranskyy, Taras
Vovk, Yuliya
Affiliation: Lviv Polytechnic National University
Bibliographic description (Ukraine): Postranskyy T. Changing of the bus driver`s functional state in city conditions / Taras Postranskyy, Yuliya Vovk // Transport Technologies. — Lviv : Lviv Politechnic Publishing House, 2020. — Vol 1. — No 1. — P. 12–21.
Bibliographic description (International): Postranskyy T. Changing of the bus driver`s functional state in city conditions / Taras Postranskyy, Yuliya Vovk // Transport Technologies. — Lviv : Lviv Politechnic Publishing House, 2020. — Vol 1. — No 1. — P. 12–21.
Is part of: Transport Technologies, 1 (1), 2020
Transport Technologies, 1 (1), 2020
Journal/Collection: Transport Technologies
Issue: 1
Issue Date: 26-Feb-2020
Publisher: Видавництво Львівської політехніки
Lviv Politechnic Publishing House
Place of the edition/event: Львів
Lviv
Keywords: stress index
heart rate variability
functional state
driving conditions
schedule of driver's work and rest
Number of pages: 10
Page range: 12-21
Start page: 12
End page: 21
Abstract: The functioning of a modern city is impossible without a proper mode of public transport and its network. Parameters of this transport system influence on the functionality of all supply chain links, training specialists, ensuring proper communication between parts of the city, the level of traffic safety, etc. At the same time, all these figures depend also on bus drivers and their work. This is due to the fact that this “human factor” influences on the proper functioning of the public transport system. It should be noted, that one of the indicators that allow analyzing the readiness of the driver to fulfill his direct professional duties is the functional state of his body. Analysis of this indicator allows creating appropriate recommendations for bus driver`s schedules of work and rest. According to this, managers can create such working conditions for drivers that will reduce the likelihood of erroneous actions. It will allow reducing the likelihood of road accidents. That`s why the importance of researching human as an operator in the transport process is increasing every year.
URI: http://ena.lp.edu.ua:8080/handle/ntb/51082
Copyright owner: © Національний університет “Львівська політехніка”, 2020
© Postranskyy T., Vovk Y., 2020
URL for reference material: https://zakon.rada.gov.ua/laws/show/z0811-10
References (Ukraine): 1. Bilous A. & Pivtorak G. (2017). Analiz metodiv vyboru kontrolnykh tochok marshrutu hromadskoho transportu dlia vyznachennia momentu korektsii rozkladu rukhu [Analysis of control point`s selection methods of public transport routes for the respective models of the bus schedule`s corrections]. Naukovo-vyrobnychyi zhurnal «Avtoshliakhovyk Ukrainy» [Scientific and Industrial Journal “The Avtoshliakhovyk Ukrayiny”], Volume 1–2 (249–250), 48 – 51. (in Ukrainian).
2. Joao Mendes-Moreira, Luis Moreira-Matias, Joao Gama & Jorge Freire de Sousa (2015). Validating the coverage of bus schedules: A Machine Learning approach. Journal “Information Sciences”, Volume 293. 299–313. doi: 10.1016/j.ins.2014.09.005 (in English).
3. Stepanov O. (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).
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).
5. 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).
6. Anund A., Ihlström J., Fors C., Kecklund G. & Filtness A. (2016). Factors associated with self-reported driver sleepiness and incidents in city bus drivers. Journal “Industrial Health”, Volume 54. Issue 4. 337–346. doi: 10.2486/indhealth.2015-0217 (in English).
7. Supriya Goel, Pradeep Tomar, & Gurjit Kaur. (2016). ECG feature extraction for stress recognition in automobile drivers. Electronic Journal of Biology, Volume 12 (2), 156-165 (in English).
8. Teresa Makowiec-Dąbrowska, Elżbieta Gadzicka, Jadwiga Siedlecka, Agata Szyjkowska, Piotr Viebig, Piotr Kozak & et al. (2019). Climate conditions and work-related fatigue among professional drivers. International Journal of Biometeorology, Volume 63, 121–1285 (in English).
9. Zuojin Li, Shengbo Eben Li, Renjie Li, & Jinliang Shi. (2017). Online detection of driver fatigue using steering wheel angles for real driving conditions. Sensors for Transportation, Volume 17 (3), 495. doi: 10.3390/s17030495 (in English).
10. Indresh Verma, Susmita Nath & Sougata Karmakar (2017). Research in Driver–Vehicle Interaction: Indian Scenario. Ergonomics in Caring for People. 353–361. doi: 10.1007/978-981-10-4980-4_43 (in English).
11. Kristian Čulik, Alica Kalasova & Simona Kubikova. (2017). Simulation as an Instrument for Research of Driver-vehicle Interaction. 18th International Scientific Conference – LOGI 2017 Volume 134. doi:10.1051/matecconf/201713400008 (in English).
12. 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).
13. Koichi Fujiwara, Erika Abe, Keisuke Kamata, Chikao Nakayama, Yoko Suzuki, Toshitaka Yamakawa & et al. (2018). Heart rate variability-based driver drowsiness detection and its validation with EEG. IEEE Transactions on Biomedical Engineering, Volume 66 (6), 1769–1778 (in English).
14. Afonin M.O. (2019). The improvement of technological processes of dangerous goods transportation considering human factor. Candidate’s thesis. Lviv: LPNU (in Ukrainian).
15. Hiuliev N. U. (2016). Liudskyi faktor i dorozhni zatory [Human factor and traffic congestion]. Kharkiv: O.M. Beketov NUUE (in Ukrainian).
16. Liujiang Kang, Shukai Chen, Layko, & Qiang Meng. (2019). Bus and driver scheduling with mealtime windows for a single public bus route. Transportation Research Part C: Emerging Technologies, Volume 101, 145–160. doi: 10.1016/j.trc.2019.02.005 (in English).
17. Pro zatverdzhennia Polozhennia pro robochyi chas i chas vidpochynku vodiiv kolisnykh transportnykh zasobiv [On approval of the Regulation on the working time and rest time of wheeled vehicles` driver]. Retrieved from https://zakon.rada.gov.ua/laws/show/z0811-10 (in Ukrainian).
References (International): 1. Bilous A. & Pivtorak G. (2017). Analiz metodiv vyboru kontrolnykh tochok marshrutu hromadskoho transportu dlia vyznachennia momentu korektsii rozkladu rukhu [Analysis of control point`s selection methods of public transport routes for the respective models of the bus schedule`s corrections]. Naukovo-vyrobnychyi zhurnal "Avtoshliakhovyk Ukrainy" [Scientific and Industrial Journal "The Avtoshliakhovyk Ukrayiny"], Volume 1–2 (249–250), 48 – 51. (in Ukrainian).
2. Joao Mendes-Moreira, Luis Moreira-Matias, Joao Gama & Jorge Freire de Sousa (2015). Validating the coverage of bus schedules: A Machine Learning approach. Journal "Information Sciences", Volume 293. 299–313. doi: 10.1016/j.ins.2014.09.005 (in English).
3. Stepanov O. (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).
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).
5. 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).
6. Anund A., Ihlström J., Fors C., Kecklund G. & Filtness A. (2016). Factors associated with self-reported driver sleepiness and incidents in city bus drivers. Journal "Industrial Health", Volume 54. Issue 4. 337–346. doi: 10.2486/indhealth.2015-0217 (in English).
7. Supriya Goel, Pradeep Tomar, & Gurjit Kaur. (2016). ECG feature extraction for stress recognition in automobile drivers. Electronic Journal of Biology, Volume 12 (2), 156-165 (in English).
8. Teresa Makowiec-Dąbrowska, Elżbieta Gadzicka, Jadwiga Siedlecka, Agata Szyjkowska, Piotr Viebig, Piotr Kozak & et al. (2019). Climate conditions and work-related fatigue among professional drivers. International Journal of Biometeorology, Volume 63, 121–1285 (in English).
9. Zuojin Li, Shengbo Eben Li, Renjie Li, & Jinliang Shi. (2017). Online detection of driver fatigue using steering wheel angles for real driving conditions. Sensors for Transportation, Volume 17 (3), 495. doi: 10.3390/s17030495 (in English).
10. Indresh Verma, Susmita Nath & Sougata Karmakar (2017). Research in Driver–Vehicle Interaction: Indian Scenario. Ergonomics in Caring for People. 353–361. doi: 10.1007/978-981-10-4980-4_43 (in English).
11. Kristian Čulik, Alica Kalasova & Simona Kubikova. (2017). Simulation as an Instrument for Research of Driver-vehicle Interaction. 18th International Scientific Conference – LOGI 2017 Volume 134. doi:10.1051/matecconf/201713400008 (in English).
12. 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).
13. Koichi Fujiwara, Erika Abe, Keisuke Kamata, Chikao Nakayama, Yoko Suzuki, Toshitaka Yamakawa & et al. (2018). Heart rate variability-based driver drowsiness detection and its validation with EEG. IEEE Transactions on Biomedical Engineering, Volume 66 (6), 1769–1778 (in English).
14. Afonin M.O. (2019). The improvement of technological processes of dangerous goods transportation considering human factor. Candidate’s thesis. Lviv: LPNU (in Ukrainian).
15. Hiuliev N. U. (2016). Liudskyi faktor i dorozhni zatory [Human factor and traffic congestion]. Kharkiv: O.M. Beketov NUUE (in Ukrainian).
16. Liujiang Kang, Shukai Chen, Layko, & Qiang Meng. (2019). Bus and driver scheduling with mealtime windows for a single public bus route. Transportation Research Part C: Emerging Technologies, Volume 101, 145–160. doi: 10.1016/j.trc.2019.02.005 (in English).
17. Pro zatverdzhennia Polozhennia pro robochyi chas i chas vidpochynku vodiiv kolisnykh transportnykh zasobiv [On approval of the Regulation on the working time and rest time of wheeled vehicles` driver]. Retrieved from https://zakon.rada.gov.ua/laws/show/z0811-10 (in Ukrainian).
Content type: Article
Appears in Collections:Transport Technologies. – 2020. – Vol. 1, No. 1



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