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Investigation of traffic accidents in Şişli district with geographic information systems

Year 2023, Volume: 6 Issue: 1, 31 - 50, 27.03.2023
https://doi.org/10.51513/jitsa.1215470

Abstract

Traffic accidents occurring are one of the most important issues that cause loss of life and property of the people. With the increasing population, the number of vehicles increasing in use creates traffic density. For this reason, studies aimed at reducing traffic accidents are of vital importance. In this study, a total of 3833 fatal and injured traffic accidents that occurred between 2010-2017 in Şişli district were analyzed with the help of geographical information systems and Kernel density method. In this study, various maps were created according to the accident type, time zone and the type of vehicles that had the most accident, and the locations of the accidents were examined. It is aimed to help reduce the number of possible accidents by taking necessary precautions in locations that are determined to be risky according to the accident intensities obtained. It has been observed that the accidents intensify differently according to the changing time zones, especially on the streets. In the study, it is also aimed to help the units that make traffic planning by making separator maps of the types of vehicles that have the most accidents on these streets, according to the accident types, days of the week and time zones.

Thanks

We would like to thank the General Directorate of Security for providing the data they have for the completion of this study. We would also like to thank the 100/2000 YÖK doctoral scholarship program.

References

  • Atalay, A. & Say, İ. (2022). Coğrafi bilgi sistemleri tabanlı bisiklet yolu güzergâhı araştırması. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 11(2), 356-362. https://doi.org/10.28948/ngumuh.1014733
  • Camkesen, N., & Bayrakdar, Z. (1999). Alan Analizi Yöntemi ile Kazaların Gerçek Nedenlerinin Saptanması. II. Transportation and Traffic Congress Book of Proceedings, Ankara. Available Online:https://docplayer.biz.tr/25379493-Ii-ulasim-ve-trafik-kongresi-sergisi-bildiriler-kitabi.html (accessed on: 02.12.2021).
  • Bil, M., Andrasik, R., & Janoska, Z. (2013). Identification of hazardous road locations of traffic accidents by means of kernel density estimation and cluster significance evaluation. Accident Analysis & Prevention, 55, 265-273. https://doi.org/10.1016/j.aap.2013.03.003.
  • Dereli, M. A., & Erdoğan, S. (2017). A new model for determining the traffic accident black spots using GIS-aided spatial statistical methods. Transportation Research Part A: Policy and Practice, 103, 106-117. https://doi.org/10.1016/j.tra.2017.05.031
  • Ersen, M., Büyüklü, A. H., & Taşabat, S. E. (2021). Analysis of Fatal and Injury Traffic Accidents in Istanbul Sarıyer District with Spatial Statistics Methods. Sustainability, 13(19), 11039. https://doi.org/10.3390/su131911039
  • Ersen, M., Büyüklü, A. H., & Taşabat, S. E. (2022). Data Mining as a Method for Comparison of Traffic Accidents in Şişli District of Istanbul. Journal of Contemporary Urban Affairs, 6(2), pp.113-141. https://doi.org/10.25034/ijcua.2022.v6n2-2
  • Erdogan, S., Yılmaz, İ., Baybura, T., & Gullu, M. (2008). Geographical information systems aided traffic accident analysis system case study: city of Afyonkarahisar. Accident Analysis & Prevention, 40, 174–181. https://doi.org/10.1016/j.aap.2007.05.004
  • Feng, M., Zheng, J., Ren, J., Hussain, A., Li, X., Xi, Y., & Liu, Q. (2019). Big data analytics and mining for effective visualization and trends forecasting of crime data. IEEE Access, 7, 106111-106123.
  • Karaman, E. (2013). İstanbulda Meydana Gelen Trafik Kazalarının Mekânsal Analizi. Master’s Thesis, Fatih University, Institute of Social Sciences, Department of Geography.
  • Kaygısız, Ö., Düzgün, H. Ş., Akın, S. and Çelik, Y. (2012). Coğrafi bilgi sistemleri kullanılarak trafik kazalarının mekânsal ve zamansal analizi. General Directorate of Security –Middle East Technical University, June, Ankara.
  • Khokale, R., & Ghate, A. (2017). Data Mining for Traffic Prediction and Analysis using Big Data. International Journal of Engineering Trends and Technology (IJETT), 48(3). https://doi.org/10.14445/22315381/IJETT-V48P227
  • Lin, L., Wang, Q., & Sadek, A. W. (2014). Data Mining and Complex Network Algorithms for Traffic Accident Analysis. Transportation Research Record, 2460, 128-136. https://doi.org/10.3141/2460-14
  • Mohaymany, A. S., Shahri, M., & Mirbagheri, B. (2013). GIS-based method for detecting high-crash-risk road segments using network kernel density estimation. Geo-spatial Information Science, 16(2), 113-119. https://doi.org/10.1080/10095020.2013.766396
  • Özmal, M. (2016). Kahramanmaraş Şehir Merkezinde Meydana Gelen Trafik Kazalarının Coğrafi Bilgi Sistemleri Kullanılarak İncelenmesi. Master’s Thesis, Kahramanmaraş Sütçü İmam University, Institute of Social Sciences, Department of Geography.
  • Saplıoğlu, M., & Karaşahin, M. (2006). Coğrafi Bilgi Sistemi yardımı ile Isparta ili kent içi trafik kaza analizi. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 12(3), 321-332. https://dergipark.org.tr/tr/pub/pajes/issue/20521/218519
  • Söylemezoğlu, T. (2006). Coğrafi Bilgi Sistemleri ile Trafik Kazalarının Analizi: Ankara Örneği. Master’s Thesis, Gazi University, Graduate School and of Natural Applied Sciences.
  • Thakali, L., Kwon, T. J., & Fu, L. (2015). Identification of crash hotspots using kernel density estimation and kriging methods: a comparison. Journal of Modern Transportation, 23, 93-106. https://doi.org/10.1007/s40534-015-0068-0
  • Tuncuk, M. (2004). Coğrafi Bilgi Sistemi yardımıyla trafik kaza analizi: Isparta örneği. Master’s Thesis, Süleyman Demirel University, Graduate School of Natural and Applied Sciences, Department of Civil Engineering.
  • Xie, Z., & Yan, J. (2008). Kernel Density Estimation of traffic accidents in a network space. Computers, Environment and Urban Systems, 32(5), 396-406. https://doi.org/10.1016/j.compenvurbsys.2008.05.001
  • Xie, Z., & Yan, J. (2013). Detecting traffic accident clusters with network kernel density estimation and local spatial statistics: an integrated approach. Journal of Transport Geography, 31, 64-71. https://doi.org/10.1016/j.jtrangeo.2013.05.009

Şişli ilçesindeki trafik kazalarının coğrafi bilgi sistemleri ile incelenmesi

Year 2023, Volume: 6 Issue: 1, 31 - 50, 27.03.2023
https://doi.org/10.51513/jitsa.1215470

Abstract

Trafik kazaları, insanların can ve mal kaybına neden olan en önemli konulardan biridir. Artan nüfusla birlikte kullanımı artan araç sayısı beraberinde trafik yoğunluğunu meydana getirmektedir. Bu nedenle trafik kazalarını azaltmaya yönelik çalışmalar hayati önem taşımaktadır. Bu çalışmada Şişli ilçesindeki 2010-2017 yılları arasında meydana gelmiş toplam 3833 ölümlü ve yaralanmalı trafik kazası coğrafi bilgi sistemleri ve çekirdek yoğunluk yöntemi yardımıyla analiz edilmiştir. Bu çalışma ile kaza türü, saat dilimi ve en çok kaza yapan araç türlerine göre çeşitli haritalar oluşturularak kazaların oluş lokasyonları incelenmiştir. Elde edilen kaza yoğunluklarına göre riskli olduğu tespit edilen lokasyonlarda gerekli önlemler alınarak olabilecek kaza sayılarının azaltılmasında yardımcı olmak amaçlanmıştır. Özellikle caddelerde değişen saat dilimlerine göre kazaların farklı olarak yoğunlaştığı görülmüştür. Çalışmada ayrıca bu caddelerde en çok kaza yapan araç cinslerinin kaza oluş türleri, haftanın günleri ve saat dilimlerine göre ayrıştırıcı haritaları yapılarak trafik planlaması yapan birimlere yardımcı olunması amaçlanmıştır.

References

  • Atalay, A. & Say, İ. (2022). Coğrafi bilgi sistemleri tabanlı bisiklet yolu güzergâhı araştırması. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 11(2), 356-362. https://doi.org/10.28948/ngumuh.1014733
  • Camkesen, N., & Bayrakdar, Z. (1999). Alan Analizi Yöntemi ile Kazaların Gerçek Nedenlerinin Saptanması. II. Transportation and Traffic Congress Book of Proceedings, Ankara. Available Online:https://docplayer.biz.tr/25379493-Ii-ulasim-ve-trafik-kongresi-sergisi-bildiriler-kitabi.html (accessed on: 02.12.2021).
  • Bil, M., Andrasik, R., & Janoska, Z. (2013). Identification of hazardous road locations of traffic accidents by means of kernel density estimation and cluster significance evaluation. Accident Analysis & Prevention, 55, 265-273. https://doi.org/10.1016/j.aap.2013.03.003.
  • Dereli, M. A., & Erdoğan, S. (2017). A new model for determining the traffic accident black spots using GIS-aided spatial statistical methods. Transportation Research Part A: Policy and Practice, 103, 106-117. https://doi.org/10.1016/j.tra.2017.05.031
  • Ersen, M., Büyüklü, A. H., & Taşabat, S. E. (2021). Analysis of Fatal and Injury Traffic Accidents in Istanbul Sarıyer District with Spatial Statistics Methods. Sustainability, 13(19), 11039. https://doi.org/10.3390/su131911039
  • Ersen, M., Büyüklü, A. H., & Taşabat, S. E. (2022). Data Mining as a Method for Comparison of Traffic Accidents in Şişli District of Istanbul. Journal of Contemporary Urban Affairs, 6(2), pp.113-141. https://doi.org/10.25034/ijcua.2022.v6n2-2
  • Erdogan, S., Yılmaz, İ., Baybura, T., & Gullu, M. (2008). Geographical information systems aided traffic accident analysis system case study: city of Afyonkarahisar. Accident Analysis & Prevention, 40, 174–181. https://doi.org/10.1016/j.aap.2007.05.004
  • Feng, M., Zheng, J., Ren, J., Hussain, A., Li, X., Xi, Y., & Liu, Q. (2019). Big data analytics and mining for effective visualization and trends forecasting of crime data. IEEE Access, 7, 106111-106123.
  • Karaman, E. (2013). İstanbulda Meydana Gelen Trafik Kazalarının Mekânsal Analizi. Master’s Thesis, Fatih University, Institute of Social Sciences, Department of Geography.
  • Kaygısız, Ö., Düzgün, H. Ş., Akın, S. and Çelik, Y. (2012). Coğrafi bilgi sistemleri kullanılarak trafik kazalarının mekânsal ve zamansal analizi. General Directorate of Security –Middle East Technical University, June, Ankara.
  • Khokale, R., & Ghate, A. (2017). Data Mining for Traffic Prediction and Analysis using Big Data. International Journal of Engineering Trends and Technology (IJETT), 48(3). https://doi.org/10.14445/22315381/IJETT-V48P227
  • Lin, L., Wang, Q., & Sadek, A. W. (2014). Data Mining and Complex Network Algorithms for Traffic Accident Analysis. Transportation Research Record, 2460, 128-136. https://doi.org/10.3141/2460-14
  • Mohaymany, A. S., Shahri, M., & Mirbagheri, B. (2013). GIS-based method for detecting high-crash-risk road segments using network kernel density estimation. Geo-spatial Information Science, 16(2), 113-119. https://doi.org/10.1080/10095020.2013.766396
  • Özmal, M. (2016). Kahramanmaraş Şehir Merkezinde Meydana Gelen Trafik Kazalarının Coğrafi Bilgi Sistemleri Kullanılarak İncelenmesi. Master’s Thesis, Kahramanmaraş Sütçü İmam University, Institute of Social Sciences, Department of Geography.
  • Saplıoğlu, M., & Karaşahin, M. (2006). Coğrafi Bilgi Sistemi yardımı ile Isparta ili kent içi trafik kaza analizi. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 12(3), 321-332. https://dergipark.org.tr/tr/pub/pajes/issue/20521/218519
  • Söylemezoğlu, T. (2006). Coğrafi Bilgi Sistemleri ile Trafik Kazalarının Analizi: Ankara Örneği. Master’s Thesis, Gazi University, Graduate School and of Natural Applied Sciences.
  • Thakali, L., Kwon, T. J., & Fu, L. (2015). Identification of crash hotspots using kernel density estimation and kriging methods: a comparison. Journal of Modern Transportation, 23, 93-106. https://doi.org/10.1007/s40534-015-0068-0
  • Tuncuk, M. (2004). Coğrafi Bilgi Sistemi yardımıyla trafik kaza analizi: Isparta örneği. Master’s Thesis, Süleyman Demirel University, Graduate School of Natural and Applied Sciences, Department of Civil Engineering.
  • Xie, Z., & Yan, J. (2008). Kernel Density Estimation of traffic accidents in a network space. Computers, Environment and Urban Systems, 32(5), 396-406. https://doi.org/10.1016/j.compenvurbsys.2008.05.001
  • Xie, Z., & Yan, J. (2013). Detecting traffic accident clusters with network kernel density estimation and local spatial statistics: an integrated approach. Journal of Transport Geography, 31, 64-71. https://doi.org/10.1016/j.jtrangeo.2013.05.009
There are 20 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Mert Ersen 0000-0001-5643-4690

Ali Hakan Büyüklü 0000-0002-4174-4538

Semra Erpolat Taşabat 0000-0001-6845-8278

Early Pub Date March 24, 2023
Publication Date March 27, 2023
Submission Date December 6, 2022
Acceptance Date February 3, 2023
Published in Issue Year 2023 Volume: 6 Issue: 1

Cite

APA Ersen, M., Büyüklü, A. H., & Erpolat Taşabat, S. (2023). Investigation of traffic accidents in Şişli district with geographic information systems. Akıllı Ulaşım Sistemleri Ve Uygulamaları Dergisi, 6(1), 31-50. https://doi.org/10.51513/jitsa.1215470