Development of models for assessing a driver's failure­free operation in a transportation system under conditions of traffic congestion

Authors

DOI:

https://doi.org/10.15587/1729-4061.2020.194449

Keywords:

driver failure-free operation, traffic accident, transport system, traffic jam, response time

Abstract

This paper has considered the task on determining a driver’s failure-free operation in the transportation system of a city taking into account traffic jams. A driver's time of stay in traffic jams leads to an increase in his/her psycho-emotional condition, an increase in the level of fatigue, and, therefore, to a decrease in failure-free operation. The level of a driver’s failure-free operation directly affects road safety. The driver’s failure-free operation within the elements of a transport system determines the probability of a traffic accident, which depends not only on the network parameters and traffic flows but, first of all, on the response time of the driver.

We have developed models for assessing a driver’s failure-free operation along the sections of a transport network and transport nodal points taking into account traffic jams. They have made it possible to assess the probability of a traffic accident for the average driver. The models take into consideration the impact of a traffic jam by changing the response time of a driver, which is a function of changing the level of fatigue.

To determine by how many times the probability of a traffic accident for the average driver along the sections of a transport network and in traffic nodes with a traffic jam exceeds the same probability along the same elements of the transport system without traffic jams, we considered the ratio of the probabilities.

The adequacy of the models has been verified by comparing the ratio of the probabilities of a traffic accident with the traffic jam along the sections of a transport network and without it to the corresponding ratio of the number of traffic accidents along the same sections of a transport network and at intersections.

The developed models that take into account traffic jams for assessing a driver’s failure-free operation along the elements of a transport network make it possible to compare and evaluate various project solutions to improve road safety

Author Biographies

Nizami Gyulyev, O. M. Beketov National University of Urban Economy in Kharkiv Marshala Bazhanova str., 17, Kharkiv, Ukraine, 61002

Doctor of Technical Sciences, Associate Professor

Department of Transport Systems and Logistics

Vitalii Voronko, O. M. Beketov National University of Urban Economy in Kharkiv Marshala Bazhanova str., 17, Kharkiv, Ukraine, 61002

Doctor of Technical Sciences, Professor

Department of Transport Systems and Logistic

Sergij Ostashevskiy, National Academy of the State Border Guard Service of Ukraine named after Bohdan Khmelnytskyi Shevchenka str., 46, Khmelnytskyi, Ukraine, 28001

Doctor of Technical Sciences, Associate Professor

Department of Vehicles and Special Cars

Denys Ponkratov, O. M. Beketov National University of Urban Economy in Kharkiv Marshala Bazhanova str., 17, Kharkiv, Ukraine, 61002

PhD, Associate Professor

Department of Transport System and Logistic

Sergij Psol, National Academy of the State Border Guard Service of Ukraine named after Bohdan Khmelnytskyi Shevchenka str., 46, Khmelnytskyi, Ukraine, 28001

PhD, Associate Professor

Department of Vehicles and Special Cars

Igor Bugayov, O. M. Beketov National University of Urban Economy in Kharkiv Marshala Bazhanova str., 17, Kharkiv, Ukraine, 61002

Assistant

Department of Transport Systems and Logistics

References

  1. Lobanov, E. M. (1980). Proektirovanie dorog i organizatsiya dvizheniya s uchetom psihofiziologii voditelya. Moscow: Transport, 311.
  2. Gyulyev, N. U., Dolya, V. K., Bichev, M. S. (2013). Effect of changes in the functional state of the driver on road safety. Eastern-European Journal of Enterprise Technologies, 3 (3 (63)), 67–69. Available at: http://journals.uran.ua/eejet/article/view/14742/12520
  3. Rotenberg, R. V. (1986). Osnovy nadezhnosti sistemy voditel' – avtomobil' – doroga – sreda. Moskva: Mashinostroenie, 216.
  4. Qi, W., Pei, Y., Song, M., Bie, Y. (2013). Pattern Analysis of Driver’s “Pressure-State-Response” in Traffic Congestion. Discrete Dynamics in Nature and Society, 2013, 1–11. doi: https://doi.org/10.1155/2013/853845
  5. Li, F., Yao, X., Jiang, L., Li, Y. (2014). Driving anger in China: Psychometric properties of the Driving Anger Scale (DAS) and its relationship with aggressive driving. Personality and Individual Differences, 68, 130–135. doi: https://doi.org/10.1016/j.paid.2014.04.018
  6. Stephens, A. N., Trawley, S. L., Madigan, R., Groeger, J. A. (2012). Drivers Display Anger-Congruent Attention to Potential Traffic Hazards. Applied Cognitive Psychology, 27 (2), 178–189. doi: https://doi.org/10.1002/acp.2894
  7. Arnott, R. (2013). A bathtub model of downtown traffic congestion. Journal of Urban Economics, 76, 110–121. doi: https://doi.org/10.1016/j.jue.2013.01.001
  8. Long, K., Lin, Q., Gu, J., Wu, W., Han, L. D. (2018). Exploring Traffic Congestion on Urban Expressways Considering Drivers’ Unreasonable Behavior at Merge/Diverge Sections in China. Sustainability, 10 (12), 4359. doi: https://doi.org/10.3390/su10124359
  9. Zhu, J., Dai, Q., Deng, Y., Zhang, A., Zhang, Y., Zhang, S. (2018). Indirect Damage of Urban Flooding: Investigation of Flood-Induced Traffic Congestion Using Dynamic Modeling. Water, 10 (5), 622. doi: https://doi.org/10.3390/w10050622
  10. Mfinanga, D., Fungo, E. (2013). Impact of Incidents on Traffic Congestion in Dar es Salaam City. International Journal of Transportation Science and Technology, 2 (2), 95–108. doi: https://doi.org/10.1260/2046-0430.2.2.95
  11. Gyulyev, N. U. (2011). Effect of idle time in the car traffic jam on the functional state of the driver. Eastern-European Journal of Enterprise Technologies, 1 (10 (49)), 50–52. Available at: http://journals.uran.ua/eejet/article/view/2465/2266
  12. Ito, T., Kaneyasu, R. (2017). Predicting traffic congestion using driver behavior. Procedia Computer Science, 112, 1288–1297. doi: https://doi.org/10.1016/j.procs.2017.08.090
  13. Chin, S.-M., Hu, P. S., Davidson, D. (2011). Making the Traffic Operations Case for Congestion Pricing: Operational Impacts of Congestion Pricing. doi: https://doi.org/10.2172/1048704
  14. Gyulyev, N., Lobashov, O., Prasolenko, O., Burko, D. (2018). Research of Changing the Driver's Reaction Time in the Traffic Jam. International Journal of Engineering & Technology, 7 (4.3), 308. doi: https://doi.org/10.14419/ijet.v7i4.3.19811
  15. Bitkina, O. V., Kim, J., Park, J., Park, J., Kim, H. K. (2019). Identifying Traffic Context Using Driving Stress: A Longitudinal Preliminary Case Study. Sensors, 19 (9), 2152. doi: https://doi.org/10.3390/s19092152
  16. Gyulyev, N., Lobashov, O., Prasolenko, O., Bugayov, I. (2019). Modeling the effect of traffic jam on driver’s level of fatigue. SHS Web of Conferences, 67, 04005. doi: https://doi.org/10.1051/shsconf/20196704005
  17. Nguyen-Phuoc, D. Q., Currie, G., De Gruyter, C., Kim, I., Young, W. (2018). Modelling the net traffic congestion impact of bus operations in Melbourne. Transportation Research Part A: Policy and Practice, 117, 1–12. doi: https://doi.org/10.1016/j.tra.2018.08.005
  18. Xu, Y., Zhang, D., Chowdhury, A. J. K. (2018). Urban road traffic flow control under incidental congestion as a function of accident duration. Open Physics, 16 (1), 1085–1093. doi: https://doi.org/10.1515/phys-2018-0129
  19. Prasolenko, O., Burko, D., Tolmachov, I., Gyulyev, N., Galkin, A., Lobashov, O. (2019). Creating safer routing for urban freight transportation. Transportation Research Procedia, 39, 417–427. doi: https://doi.org/10.1016/j.trpro.2019.06.044
  20. Gao, J., Davis, G. A. (2017). Using naturalistic driving study data to investigate the impact of driver distraction on driver's brake reaction time in freeway rear-end events in car-following situation. Journal of Safety Research, 63, 195–204. doi: https://doi.org/10.1016/j.jsr.2017.10.012
  21. Gyulyev, N., Dolya, C. (2017). The issue of probability of traffic road accident on the elements of the transport network. American Journal Of Social Science Research, 3 (5), 17–24. Available at: https://pdfs.semanticscholar.org/fcc2/e99fc6a2cc4432f18886e2b24f5c5e885c30.pdf?_ga=2.28737204.907443567.1580978969-1908018850.1550590803
  22. Olhov, V. S., Lubentsov, A. V. (2017). Choice of reaction time on danger of the driver who operates the car, moving with exceeding of the established restriction on the traverse speed. Theory and Practice of Forensic Science and Criminalistics, 17, 307–312. doi: https://doi.org/10.32353/khrife.2017.38
  23. Sheu, J.-B., Wu, H.-J. (2015). Driver perception uncertainty in perceived relative speed and reaction time in car following – A quantum optical flow perspective. Transportation Research Part B: Methodological, 80, 257–274. doi: https://doi.org/10.1016/j.trb.2015.07.017
  24. Kim, T., Zhang, H. M. (2011). Interrelations of Reaction Time, Driver Sensitivity, and Time Headway in Congested Traffic. Transportation Research Record: Journal of the Transportation Research Board, 2249 (1), 52–61. doi: https://doi.org/10.3141/2249-08
  25. Dolia, V. K., Enhlezi, I. P., Pakhno, O. S. (2011). Shchodo vyznachennia vplyvu parametriv transportnykh potokiv ta dorozhnikh umov na ymovirnist vynyknennia DTP na diliankakh dorohy. Visnik Donetskoi Akademiyi Avtomobilnoho Transportu, 3, 29–33.
  26. Gyulyev, N., Dolya, V., Ohrimenko, A. (2015). Researching of influence of driver state on its reaction time in traffic congestion. Komunalne hospodarstvo mist, 121, 60–64.
  27. Gyulyev, N. U., Dolya, V. K. (2012). O zavisimosti vremeni reaktsii voditelya ot izmeneniya ego funktsional'nogo sostoyaniya. Visnyk Natsionalnoho Tekhnichnoho Universytetu «KhPI», 26, 47–50.
  28. Mitropol'skiy, A. K. (1971). Tehnika statisticheskih vichisleniy. Moscow: Nauka, 576.
  29. Baevskiy, P. M. (1979). Prognozirovanie sostoyaniy na grani normy i patologii. Moscow: Meditsina, 298.

Downloads

Published

2020-02-29

How to Cite

Gyulyev, N., Voronko, V., Ostashevskiy, S., Ponkratov, D., Psol, S., & Bugayov, I. (2020). Development of models for assessing a driver’s failure­free operation in a transportation system under conditions of traffic congestion. Eastern-European Journal of Enterprise Technologies, 1(3 (103), 24–38. https://doi.org/10.15587/1729-4061.2020.194449

Issue

Section

Control processes