Communications - Scientific Letters of the University of Zilina 2024, 26(1):F13-F22 | DOI: 10.26552/com.C.2024.012

An Estimate of the Number of Accidents on Polish Highways Based on the Kind of Road

Piotr Gorzelańczyk ORCID...1, *, Przemysław Grobelny ORCID...2
1 Stanislaw Staszic State University of Applied Sciences in Pila, Pila, Poland
2 Jan Amos Komenski State University of Applied Sciences in Leszno, Leszno, Poland

A surprising number of people die on Polish highways every year. Despite the fact that number is decreasing year after year, it is still rather considerable. Due to the epidemic, the costs of the road accidents were significantly lowered, but they still remain fairly large. Understanding the roads where the majority of accidents happen and the anticipated number of accidents in the next years are necessary to lower this number. The purpose of the article was to forecast the number of accidents that would happen on Polish roads based on the kind of roads. To do this, annual accident statistics from the Police's statistics for the years 2001-2021 were reviewed, and a forecast for the years 2022-2031 was produced. It is clear that either the accident rate is increasing or it is steady. Predictions also suggest that a large increase in accidents on Polish roads may be expected given the current situation.

Keywords: road accident, road type, forecasting, exponential smoothing
Grants and funding:

The authors received no financial support for the research, authorship and/or publication of this article.

Conflicts of interest:

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Received: September 11, 2023; Accepted: November 27, 2023; Prepublished online: December 14, 2023; Published: January 8, 2024  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Gorzelańczyk, P., & Grobelny, P. (2024). An Estimate of the Number of Accidents on Polish Highways Based on the Kind of Road. Communications - Scientific Letters of the University of Zilina26(1), F13-22. doi: 10.26552/com.C.2024.012
Download citation

References

  1. WHO Team. The global status on road safety [online] [accessed 2022-02-01]. ISBN 9789241565684. Available from: https://www.who.int/publications/i/item/9789241565684
  2. TAMBOURATZIS, T., SOULIOU, D., CHALIKIAS, M., GREGORIADES, A. Maximising accuracy and efficiency of traffic accident prediction combining information mining with computational intelligence approaches and decision trees. Journal of Artificial Intelligence and Soft Computing Research [online]. 2014, 4(1), p. 31-42 [accessed 2022-02-01]. eISSN 2449-6499. Available from: https://doi.org/10.2478/jaiscr-2014-0023 Go to original source...
  3. ZHU, L., LU, L., ZHANG, W., ZHAO, Y., SONG, M. Analysis of accident severity for curved roadways based on bayesian networks. Sustainability [online]. 2019, 11(8), 2223 [accessed 2022-02-01]. eISSN 2071-1050. Available from: https://doi.org/10.3390/su11082223 Go to original source...
  4. ARTEAGA, C., PAZ, A., PARK, J. Injury severity on traffic crashes: a text mining with an interpretable machine-learning approach. Safety Science [online]. 2020, 132, 104988 [accessed 2022-02-01]. ISSN 0925-7535, eISSN 1879-1042. Available from: https://doi.org/10.1016/j.ssci.2020.104988 Go to original source...
  5. YANG, Z. ZHANG, W., FENG J. Predicting multiple types of traffic accident severity with explanations: a multi-task deep learning framework. Safety Science [online]. 2022, 146, 105522 [accessed 2022-02-01]. ISSN 0925-7535, eISSN 1879-1042. Available from: https://doi.org/10.1016/j.ssci.2021.105522 Go to original source...
  6. GORZELANCZYK, P., PYSZEWSKA, D., KALINA, T., JURKOVIC, M. Analysis of road traffic safety in the Pila Poviat. Scientific Journal of Silesian University of Technology. Series Transport [online]. 2020, 107, p. 33-52 [accessed 2022-02-01]. ISSN 0209-3324, eISSN 2450-1549. Available from: https://doi.org/10.20858/sjsutst.2020.107.3 Go to original source...
  7. CHEN, C. Analysis and forecast of traffic accident big data. ITM Web of Conferences [online]. 2017, 12, 04029 [accessed 2022-02-01]. eISSN 2271-2097. Available from: https://doi.org/10.1051/itmconf/20171204029 Go to original source...
  8. KHALIQ, K. A., CHUGHTAI, O., SHAHWANI, A., QAYYUM, A., PANNEK, J. Road accidents detection, data collection and data analysis using V2X communication and edge/cloud computing. Electronics [online]. 2019, 8(8), 896 [accessed 2022-02-01]. eISSN 2079-9292. Available from: https://doi.org/10.3390/electronics8080896 Go to original source...
  9. RAJPUT, H., SOM, T., KAR, S. An automated vehicle license plate recognition system. Computer [online]. 2015, 48(8), p. 56-61 [accessed 2022-02-01]. ISSN 0018-9162, eISSN 1558-0814. Available from: https://doi.org/10.1109/MC.2015.244 Go to original source...
  10. ZHENG, Z., WANG, C., WANG, P., XIONG, Y., ZHANG, F., LV, Y. Framework for fusing traffic information from social and physical transportation data. PLoS One [online]. 2018, 13(8), e0201531 [accessed 2022-02-01]. eISSN 1932-6203. Available from: https://doi.org/10.1371/journal.pone.0201531 Go to original source...
  11. ABDULLAH, E., EMAM, A. Traffic accidents analyzer using big data. In: 2015 International Conference on Computational Science and Computational Intelligence CSCI 2015: proceedings [online]. IEEE. 2015 [accessed 2022-02-01]. eISBN 978-1-4673-9795-7, p. 392-397. Available from: https://doi.org/10.1109/CSCI.2015.187 Go to original source...
  12. VILACA, M., SILVA, N., COELHO, M. C. Statistical analysis of the occurrence and severity of crashes involving vulnerable road users. Transportation Research Procedia [online]. 2017, 27, p. 1113-1120 [accessed 2022-02-01]. ISSN 2352-1457, eISSN 2352-1465. Available from: https://doi.org/10.1016/j.trpro.2017.12.113 Go to original source...
  13. BAK, I., CHEBA, K., SZCZECINSKA, B. The statistical analysis of road traffic in cities of Poland. Transportation Research Procedia [online]. 2019, 39, p. 14-23 [accessed 2022-02-01]. ISSN 2352-1457, eISSN 2352-1465. Available from: https://doi.org/10.1016/j.trpro.2019.06.003 Go to original source...
  14. CHAND, A., JAYESH, S., BHASI, A. B. Road traffic accidents: an overview of data sources, analysis techniques and contributing factors. Materials Today: Proceedings [online]. 2021, 47(15), p. 5135-5141 [accessed 2022-02-01]. eISSN 2214-7853. Available from: https://doi.org/10.1016/j.matpr.2021.05.415 Go to original source...
  15. HELGASON, A. Fractional integration methods and short time series: evidence from asimulation study. Political Analysis [online]. 2016, 24(1), p. 59-68 [accessed 2022-02-01]. ISSN 1047-1987, eISSN 1476-4989. Available from: https://doi.org/10.1093/pan/mpv026 Go to original source...
  16. LAVRENZ, S., VLAHOGIANNI, E., GKRITZA, K., KE, Y. Time series modeling in traffic safetyresearch. Accident Analysis and Prevention [online]. 2018, 117, p. 368-380 [accessed 2022-02-01]. ISSN 0001-4575, eISSN 1879-2057. Available from: https://doi.org/10.1016/j.aap.2017.11.030 Go to original source...
  17. Forecasting based on time series (in Polish) [online] [accessed 2022-02-01]. Available from: http://pis.rezolwenta.eu.org/Materialy/PiS-W-5.pdf
  18. SUNNY, C. M., NITHYA, S., SINSHI, K. S., VINODINI, V. M. D., LAKSHMI, A. K. G., ANJANA, S., MANOJKUMAR, T. K. Forecasting of road accident in Kerala: a case study. In: 2018 International Conference on Data Science and Engineering ICDSE: proceedings [online] [accessed 2022-02-01]. IEEE. 2018. eISBN 978-1-5386-4855-1. Available from: https://doi.org/10.1109/ICDSE.2018.8527825 Go to original source...
  19. PROCHAZKA, J. CAMAJ, M. Modelling the number of road accidents of uninsured drivers and their severity. In: International Academic Conferences 5408040, International Institute of Social and Economic Sciences: proceedings. 2017 [online] [accessed 2022-02-01]. Available from https://ideas.repec.org/p/sek/iacpro/5408040.html
  20. SZMUKSTA-ZAWADZKA, M., ZAWADZKI, J. Forecasting on the basis of Holt-Winters models for complete and incomplete data / O prognozowaniu na podstawie modeli Holta-Wintersa dla pelnych i niepelnych danych (in Polish). Econometrics / Ekonometria [online]. 2009, 24(38), p. 85-99. [accessed 2022-02-01]. ISSN 1507-3866. Available from: https://www.dbc.wroc.pl/dlibra/doccontent?id=15648
  21. Al-MADANI, H. M. N. Global road fatality trends'estimations based on country-wise microlevel data. Accident Analysis and Prevention [online]. 2018, 111, p. 297-310 [accessed 2022-02-01]. ISSN 0001-4575, eISSN 1879-2057. Available from: https://doi.org/10.1016/j.aap.2017.11.035 Go to original source...
  22. MONEDEROA, B. D., GIL-ALANAA, L. A., MARTINEZAA, M. C. V. Road accidents in Spain: Are they persistent? IATSS Research [online]. 2021, 45(3), p. 317-325 [accessed 2022-02-01]. ISSN 0386-1112, eISSN 0386-1112. Available from: https://doi.org/10.1016/j.iatssr.2021.01.002 Go to original source...
  23. WOJCIK, A. Autoregressive vector models as a response to the critique of multi-equation structural econometric models / Modele wektorowo-autoregresyjne jako odpowiedz na krytyke strukturalnych wielorownaniowych modeli ekonometrycznych (in Polish). Economic Studies / Studia Ekonomiczne [online]. 2014, 193, p. 112-128 [accessed 2022-02-01]. ISSN 2083-8611. Available from: https://cejsh.icm.edu.pl/cejsh/element/bwmeta1.element.desklight-538707d9-40cd-471b-a022-6190a01eb76f
  24. PILATOWSKA, M. The choice of the order of autoregression depending on the parameters of the generating model / Wybor rzedu autoregresji w zaleznosci od parametrow modelu generujacego (in Polish). Econometrics / Ekonometria [online]. 2012, 4(38), p. 16-35 [accessed 2022-02-01]. ISSN 1507-3866. Available from: https://dbc.wroc.pl/Content/22753/Pilatowska_Wybor_Rzedu_Autoregresji_w_Zale%C5%BCnosci_Od_Parametrow.pdf
  25. MAMCZUR, M. Machine learning. How does linear regression work? And is it worth using? / Jak dziala regresja liniowa? I czy warto ja stosowac? (in Polish) [online] [accessed 2022-02-01]. Available from: https://miroslawmamczur.pl/jak-dziala-regresja-liniowa-i-czy-warto-ja-stosowac/
  26. BISWAS, A. A., MIA, J., MAJUMDER, A. Forecasting the number of road accidents and casualties using random forest regression in the context of Bangladesh. In: 2019 10th International Conference on Computing, Communication and Networking Technologies ICCCNT: proceedings [online] [accessed 2022-02-01]. IEEE. 2019. eISBN 978-1-5386-5906-9. Available from: https://doi.org/10.1109/ICCCNT45670.2019.8944500 Go to original source...
  27. Random forest / Las losowy (in Polish) [online] [accessed 2022-02-01]. Available from: https://pl.wikipedia.org/wiki/Las_losowy
  28. FIJOREK, K., MROZ, K., NIEDZIELA, K., FIJOREK, D. Forecasting electricity prices on the day-ahead market using data mining methods / Prognozowanie cen energii elektrycznej na rynku dnia nastepnego metodami data mining (in Polish). Rynek Energii / Energy Market [online]. 2010, 6, p. 46-50 [accessed 2022-02-01]. ISSN 1425-5960. Available from: https://www.cire.pl/pliki/2/prognozowanie_cen_rdn.pdf
  29. CHUDY-LASKOWSKA, K. PISULA, T. Forecastof road accidents in Poland / Prognozowanie liczby wypadkow drogowych na Podkarpaciu (in Polish). Logistyka / Logistics. 2015, 4, p. 2782-2796. ISSN 1231-5478.
  30. KASHPRUK, N. Comparative research of statistical models and soft computing for identification of time series and forecasting [online] [accessed 2022-02-01]. Ph.D. dissertation. Opole: Opole University of Technology, 2010. Available from: https://dbc.wroc.pl/Content/108023/Praca%20Doktorska_%20Nataliia%20Kashpruk_popr.pdf
  31. PROCHAZKA, J., FLIMMEL, S., CAMAJ, M., BASTA, M. Modelling the number of road accidents [online]. In: 20th International Scientific Conference AMSE Applications of Mathematics and Statistics in Economics 2017: proceedings [online] [accessed 2022-02-01]. 2017. p. 355-364. Available from: https://doi.org/10.15611/amse.2017.20.29 Go to original source...
  32. DUTTA, B., BARMAN, M. P., PATOWARY, A. N. Application of Arima model for forecasting road accident deaths in India. International Journal of Agricultural and Statistical Sciences [online]. 2020, 16(2), p. 607-615 [accessed 2022-02-01]. ISSN 0973-1903, e-ISSN 0976-3392. Available from: https://connectjournals.com/03899.2020.16.607
  33. KARLAFTIS, M., VLAHOGIANNI, E. Memory properties and fractional integration in trans-portation time-series. Transportation Research Part C Emerging Technologies [online]. 2009, 17(4), p. 444-453 [accessed 2022-02-01]. ISSN 0968-090X, eISSN 1879-2359. Available from: https://doi.org/10.1016/j.trc.2009.03.001 Go to original source...
  34. LOBEJKO, S. Time series analysis and forecasting with SAS / Analiza i prognozowanie szeregow czasowych z programem SAS (in Polish). Warsaw: Main Business School in Warsaw, 2015. ISBN 978-83-7378-958-6.
  35. CHUDY-LASKOWSKA, K., PISULA, T. Forecast of the number of road accidents in Poland / Prognoza liczby wypadkow drogowych w Polsce (in Polish). Logistyka / Logistics. 2014, 6, p. 2710-2722. ISSN 1231-5478.
  36. GREGORCZYK, A., SWARCEWICZ, M. Analysis of variance in a repeated measures design to determine the effects of factors affecting linuron residues in soil / Analiza wariancji w ukladzie powtarzanych pomiarow do okreslenia efektow czynnikow wplywajacych na pozostalosci linuronu w glebie (in Polish). Polish Journal of Agronomy [online]. 2012, 11, p. 15-20 [accessed 2022-02-01]. ISSN 2081-2787. Available from: https://www.iung.pl/PJA/wydane/11/PJA11_3.pdf
  37. WROBEL, M. S. Application of neural fuzzy systems in chemistry / Zastosowanie neuronowych systemow rozmytych w chemii (in Polish) [online] [accessed 2022-02-01]. Ph.D. thesis. Katowice: University of Silesia, 2011. Available from:https://rebus.us.edu.pl/bitstream/20.500.12128/5266/1/Wrobel_Zastosowanie_neuronowych_systemow.pdf
  38. Data mining techniques - StatSoft (in Polish) [online] [accessed 2022-02-01]. Available from: https://www.statsoft.pl/textbook/stathome_stat.html?https%3A%2F%2Fwww.statsoft.pl%2Ftextbook%2Fstdatmin.html
  39. KUMAR, S., VISWANADHAM, V., BHARATHI, B. Analysis of road accident. IOP Conference Series Materials Science and Engineering [online]. 2019, 590(1), 012029 [accessed 2022-02-01]. ISSN 1757-899X. Available from: https://doi.org/10.1088/1757-899X/590/1/012029 Go to original source...
  40. Top advantages and disadvantages of Hadoop 3 - DataFlair [online] [accessed 2022-02-01]. Available from: https://data-flair.training/blogs/advantages-and-disadvantages-of-hadoop/
  41. PERCZAK, G., FISZEDER, P. GARCH model - using additional information on minimum and maximum prices / Model GARCH - wykorzystanie dodatkowych informacji o cenach minimalnych i maksymalnych (in Polish). Bank and Credit[online]. 2014, 2, p. 105-131 [accessed 2022-02-01]. ISSN 0137-5520. Available from: https://www.bankandcredit.nbp.pl/content/2014/02/bik_02_2014_02_art.pdf
  42. MCILROY, R. C., PLANT, K. A., HOQUE, M. S., WU, J., KOKWARO, G. O., NAM, V. H., STANTON N. A. Who is responsible for global road safety? A cross-cultural comparison ofactor maps. Accident Analysis and Prevention [online]. 2019, 122, p. 8-18 [accessed 2022-02-01]. ISSN 0001-4575, eISSN 1879-2057. Available from: https://doi.org/10.1016/j.aap.2018.09.011 Go to original source...
  43. MUCK, J. Econometrics. Modeling of time series. Stationary. Unit root tests. ARDL models. Co-integration / Ekonometria. Modelowanie szeregow czasowych. Stacjonarnosc. Testy pierwiastka jednostkowego. Modele ARDL. Kointegracja (in Polish) [online] [accessed 2022-02-01]. Available from: http://web.sgh.waw.pl/~jmuck/Ekonometria/EkonometriaPrezentacja5.pdf
  44. PATIL, D., FRANKLIN, R., DESHMUKH, S., PILLAI, S., NASHIPUDIMATH, M. Analysis of road accidents using data mining techniques. International Research Journal of Engineering and Technology. 2020, 7(5), p. 6859-6862 [accessed 2022-02-01]. ISSN 2395-0072, eISSN 2395-0056. Available from: https://www.irjet.net/archives/V7/i5/IRJET-V7I51291.pdf
  45. LI, L, SHRESTHA, S., HU, G. Analysis of road traffic fatal accidents using data mining techniques. In: 2017 IEEE 15th International Conference on Software Engineering Research, Management and Applications SERA: proceedings [online] [accessed 2022-02-01]. IEEE. 2017. eISBN 978-1-5090-5756-6, p. 363-370. Available from: https://doi.org/10.1109/SERA.2017.7965753 Go to original source...
  46. MARCINKOWSKA, J. Statistical methods and data mining in assessing the occurrence of syncope in the group of narrow-QRS tachycardia (AVNRT and AVRT) [online] [accessed 2022-02-01]. Dissertation for the degree of Doctor of Medical Sciences. Medical Poznan: University of Karol Marcinkowski in Poznan, 2015. Available from: http://www.wbc.poznan.pl/Content/373785/index.pdf
  47. SEBEGO, M., NAUMANN, R. B., RUDD, R. A., VOETSCH, K., DELLINGER, A. M., NDLOVU, C. The impact of alcohol and road traffic policies on crash rates in Botswana, 2004-2011: a time-series analysis. Accident Analysis and Prevention [online]. 2008, 70, p. 33-39 [accessed 2022-02-01]. ISSN 0001-4575, eISSN 1879-2057. Available from: https://doi.org/10.1016/j.aap.2014.02.017 Go to original source...
  48. BLOOMFIELD, P. An exponential model in the spectrum of a scalar time series. Biometrika [online]. 1973, 60(2), p. 217-226 [accessed 2022-02-01]. eISSN 1464-3510. Available from: https://doi.org/10.2307/2334533 Go to original source...
  49. GORZELANCZYK, P. Change in the mobility of polish residents during the Covid-19 pandemic. Communications - Scientific letters of the University of Zilina [online]. 2022, 24(3), p. A100-A111 [accessed 2022-02-01]. Available from: https://doi.org/10.26552/com.C.2022.3.A100-A111 Go to original source...
  50. Statistic road accident / Polacy czuja sie bardzo bezpiecznie - Statystyka (in Polish) [online] [accessed 2022-02-01]. Available from: https://statystyka.policja.pl/

This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.