A Novel Approach to Analysis of Road Accidents Using the Trend Analysis and IPTA Method: A Case Study of Kosovo

Authors

DOI:

https://doi.org/10.7250/bjrbe.2022-17.576

Keywords:

IPTA method, Kosovo, road accidents, traffic, trend analysis

Abstract

Road accidents in Kosovo cause more than 100 deaths each year and about EUR 40 million in property damage. The paper presents an accident prediction model that relates accident frequency to various contributory factors and is developed using trend analysis and the Innovative Polygon Trend Analysis method. In addition, the study investigates road traffic accidents using a novel methodology to compare the different modes and other parameters. The presented research also discusses the road safety in Kosovo, which is a Republic with relatively low economic growth based on GDP per capita, a young population, an increase in the number of vehicles per capita, and an increase in the number of road accidents, but a decline in the number of deaths from road accidents in recent years.

References

Ali, R., Kuriqi A., Abubaker Sh., & Kisi, O. (2019). Long-term trends and seasonality detection of the observed flow in Yangtze river using Mann-Kendall and Sen’s innovative trend method. Water, 11(9), Article 1855. https://doi.org/10.3390/w11091855

Assi, K., Rahman, M. S., Mansoor, U., & Ratrout, N. (2020). Predicting crash injury severity with machine learning algorithm synergized with clustering technique: A promising protocol. International Journal Environmental Research and Public Health, 17, Article 5497. https://doi.org/10.3390/ijerph17155497

Ceribasi, G., & Ceyhunlu, I. A. (2021). Analysis of total monthly precipitation of Susurluk Basin in Turkey using innovative polygon trend analysis method. Journal of Water and Climate Change, 12(5), 1532–1543. https://doi.org/10.2166/wcc.2020.253

Deublein, M., Schubert, M., Adey, T. B., Köhler, J., & Faber, H. M. (2013). Prediction of road accidents: A Bayesian hierarchical approach. Accident Analysis & Prevention, 51, 274–291. https://doi.org/10.1016/j.aap.2012.11.019

Dominique, L., & Fred, M. (2010). The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives. Transportation Research Part A: Policy and Practice, 44(5), 291–305. https://doi.org/10.1016/j.tra.2010.02.001

ICMM. (2022, April 13). Infrastruktura. The Independent Commission for Mines and Minerals. https://kosovo-mining.org/kosova/infrastruktura/acces

KAS. (2021a, April 13). Statistical yearbook of the republic of Kosovo. Kosovo Agency of Statistics. https://ask.rks-gov.net/media/5641/vjetari-2020-final-per-web-ang.pdf

KAS. (2021b, April 13). Transport statistics of the republic of Kosovo. Kosovo Agency of Statistics. https://ask.rks-gov.net/media/6639/transport-statistics-q4-2021.pdf

KP. (2021, October 05). Infrastruktura. Kosovo Police Accident Reports. https://kosovo-mining.org/kosova/infrastruktura

Li, Zh., Liu, P., Wang, W., & Xu, Ch. (2012). Using support vector machine models for crash injury severity analysis. Accident Analysis & Prevention, 45, 478–486. https://doi.org/10.1016/j.aap.2011.08.016

NAO. (2019, October 16). Performance audit report road traffic safety. National Audit Office of Republic of Kosovo. http://www.zka-rks.org/wp-content/ uploads/2019/12/Raporti-Auditimit-Siguria-ne-trafik-eng.pdf

Naseer, A., Nour, K. M., & Alkazemi, Y. B. (2020). Towards deep learning based traffic accident analysis. 2020 10th Annual Computing and Communication Workshop and Conference (CCWC), USA, 0817–0820. https://doi.org/10.1109/CCWC47524.2020.9031235

MI. (2015a, October 16). Road safety strategy and action plan for Kosovo 2016–2022. Ministry of Infrastructure of the Republic of Kosovo. https:// www.mit-ks.net/repository/docs/2015_11_05_091915_road_safety_ strategy_20102015.pdf

MI. (2015b). Sectorial strategy and multimodal transport 2015-2025 and the action plan for 5 years. Ministry of Infrastructure of the Republic of Kosovo. https://kryeministri.rks-gov.net/en/blog/sectorial-strategy-and-multim-odal-transport-2015-2025-and-the-action-plan-for-5-years-07-09-2016/

Moghaddam, R. F., Afandizadeh, Sh., & Ziyadi, M. (2010). Prediction of accident severity using artificial neural networks. International Journal of Civil Engineering, 9(1), 41–49. http://ijce.iust.ac.ir/article-1-544-en.pdf

Şen, S., Şişman, E., & Dabanli, I. (2019). Innovative polygon trend analysis (IPTA) and applications. Journal of Hydrology, 575, 202–210. https://doi.org/10.1016/j.jhydrol.2019.05.028

Sohn, Y. S., & Shin, H. (2001). Pattern recognition for road traffic accident severity in Korea. Ergonomics, 44(1), 107–117. https://doi.org/10.1080/00140130120928

WHO. (2004). World report on road traffic injury prevention. World Health Organisation. http://apps.who.int/iris/bitstream/handle/10665/42871/9241562609. pdf?sequence=1

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Published

23.12.2022

How to Cite

Mazrekaj, R., Đurin, B., Shala, A., Lajqi, S., & Alamatian, E. (2022). A Novel Approach to Analysis of Road Accidents Using the Trend Analysis and IPTA Method: A Case Study of Kosovo. The Baltic Journal of Road and Bridge Engineering, 17(4), 1-17. https://doi.org/10.7250/bjrbe.2022-17.576