Analysis of Pedestrian-Vehicle Crashes Using Artificial Learning Methods: City of Sakarya Case Study

Zeliha Cagla Kuyumcu;Suhrab Ahadi;Hakan Aslan

doi:10.33793/acperpro.04.02.54

The Academic Perspective Procedia publishes Academic Platform symposiums papers as three volumes in a year. DOI number is given to all of our papers.
Publisher : Academic Perspective

Journal DOI : 10.33793/acperpro
Journal eISSN : 2667-5862

Year :2021, Volume 4, Issue 2, Pages: 221-230

06.11.2021

Analysis of Pedestrian-Vehicle Crashes Using Artificial Learning Methods: City of Sakarya Case Study

Zeliha Cagla Kuyumcu;Suhrab Ahadi;Hakan Aslan

https://doi.org/10.33793/acperpro.04.02.54

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Abstract

The lives of approximately 1.3 million people are cut short every year as a result of road traffic crashes. Between 20 and 50 million people suffer non-fatal injuries, with many incurring a disability as a result of their injury. The risk of dying in a road traffic crash is more than 3 times higher in low-income countries than in high-income countries [1]. In Turkey, 18% of traffic accidents was related to pedestrian-vehicle collisions in urban roads in 2020. In addition, 20% of death toll caused by accidents is pedestrians in 2020 [2]. This study deals with the some of classifiers to forecast the number of injuries as a result of traffic accidents. The classifiers performance ratios were also examined.

Keywords: traffic accidents, pedestrian crashes, data mining algorithms

References

[1] https://www.who.int/news-room/fact-sheets/detail/road-traffic-injuries
[2] Traffic Accidents Summary, General Directorate of Highways-Republic of Turkey.
[3] NHTSA_pedestrian_aug2013_9718.pdf. (t.y.). United States Department of Transportation. Geliş tarihi 05 Kasım 2021, gönderen https://www.nhtsa.gov/sites/nhtsa.gov/files/documents/s1n_pedestrian_aug2013_9718.pdf
[4] Krishnaveni, S., & Hemalatha, M. (2011). A Perspective Analysis of Traffic Accident using Data Mining Techniques. International Journal of Computer Applications, 23(7), 40-48. https://doi.org/10.5120/2896-3788
[5] AlKheder, S., AlRukaibi, F., & Aiash, A. (2020). Risk analysis of traffic accidents’ severities: An application of three data mining models. ISA Transactions, 106, 213-220. https://doi.org/10.1016/j.isatra.2020.06.018

Cite

@article{acperproISHAD2021ID54, author={Kuyumcu, Zeliha Cagla and Ahadi, Suhrab and , Hakan Aslan}, title={Analysis of Pedestrian-Vehicle Crashes Using Artificial Learning Methods: City of Sakarya Case Study}, journal={Academic Perspective Procedia}, eissn={2667-5862}, volume={4}, year=2021, pages={221-230}}
Kuyumcu, Z. , Ahadi, S. , , H.. (2021). Analysis of Pedestrian-Vehicle Crashes Using Artificial Learning Methods: City of Sakarya Case Study. Academic Perspective Procedia, 4 (2), 221-230. DOI: 10.33793/acperpro.04.02.54
%0 Academic Perspective Procedia (ACPERPRO) Analysis of Pedestrian-Vehicle Crashes Using Artificial Learning Methods: City of Sakarya Case Study% A Zeliha Cagla Kuyumcu , Suhrab Ahadi , Hakan Aslan % T Analysis of Pedestrian-Vehicle Crashes Using Artificial Learning Methods: City of Sakarya Case Study% D 11/6/2021% J Academic Perspective Procedia (ACPERPRO)% P 221-230% V 4% N 2% R doi: 10.33793/acperpro.04.02.54% U 10.33793/acperpro.04.02.54

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