Identification of Accident-Prone Points on the Ilam-Homail-Kermanshah Route Using Spatial Information System and Fuzzy AHP Method

Document Type : Original Article

Authors
1 M.Sc., Grad., Technical and Engineering Faculty, Institute of Civil and Development Higher Education, Hamedan, Iran.
2 Assistant Professor, Assistant Professor, Department of Civil Engineering, Faculty of Technology and Engineering, Razi University, Kermanshah‌, Iran‌.
3 Assistant Professor, Faculty member of Hamadan Higher Education Institute of Civil Engineering and Development, Hamedan, Iran.
Abstract
According to available statistics, every year thousands of people in Iran die or become disabled due to road accidents, which is considered a national disaster.the purpose of this article is to prioritize the accident-prone points of the Ilam-Hamil-Kermanshah axis and provide a solution for its improvement. In the upcoming research, the parameters involved in this axis, such as the number of accidents, road conditions, traffic, etc., are examined and the route is prioritized based on these parameters. The data of the Ilam-Hamil-Kermanshah route was obtained from the traffic council of Ilam province, and then 12 accident-prone points were analyzed based on 8 criteria. After designing the questionnaire, 44 experts were asked to rate the decision matrices, and then weights and maps and charts were prepared for each of the criteria based on fuzzy AHP. Then the final weight of the options was calculated and the priority of accident-prone points with very high risk, high risk, medium risk and low risk was done. According to the fuzzy AHP prioritization, the accident-prone points with a very high risk are Qalandar parking lot, Tang Qir, Azadi tunnel, and environmental bend, and the high-risk accident point is Imamzadeh Hasan intersection. The accident-prone points with medium risk are the one-way intersections of Sarablah, Bankul, the intersection of Siahkhor and Karim Hasteh villages, and the intersections of Cheshme Khazane village, Lalabad intersection, and Karzan intersection are low-risk accident-prone points.
Keywords

-حاجی حسینلو، منصور و قیاسی، ایمان اله (1391). مکانیابی و اولویت­بندی نقاط حادثه­خیز تصادفات عابرین پیاده در شبکه­های درون شهری با استفاده از GIS (مطالعه موردی شهر تهران)، یازدهمین کنفرانس مهندسی حمل و نقل و ترافیک ایران.  
-حجازی، سیدجعفر و شاه ولی، رضا (1394). شناسایی نقاط حادثه خیز جهت مکانیابی استقرار امداد و نجات جاده­ای محورهای اصلی استان خوزستان، چهاردهمین کنفرانس بین المللی مهندسی حمل و نقل و ترافیک.
خلیلی، مرتضی، مستوفیان، بهاره، و قاسمی، طیبه (1392). شناسایی، بررسی و تحلیل نقاط حادثه‌خیز در راه‌های برون‌شهری با استفاده از نرم‌افزارهای ExpertChoice, GIS و ارائه راهکارهای پیشنهادی (مطالعه موردی محورهای منتهی به شهر مشهد). سیزدهمین کنفرانس بین المللی مهندسی حمل و نقل و ترافیک.
-شفابخش، غلامعلی، علیزاده، حسنا و اکبری، مهدی (1390). شناسایی و اولویت بندی معیارهای مؤثر در اولویت بندی نقاط حادثه خیز با استفاده از تکنیک DEMATEL.
-Abi-Char, H. K. a. P. E. (2019). A New Fuzzy-TOPSIS Based Risk Decision Making Framework for Dangerous Good Transportation IEEE, 21st International Conference on High Performance Computing and Communications, Zhangjiajie, China.
-Adeliyi, T., Oluwadele, D., Igwe, K., & Aroba, O. (2023). Analysis of Road Traffic Accidents Severity Using a Pruned Tree-Based Model. Int. J. Transp. Dev. Integr, 7(2), 131-138.
doi.org/ 10.18280/ijtdi.070208
-Al-Aamri, A. K., Hornby, G., Zhang, L.-C., Al-Maniri, A. A., & Padmadas, S. S. (2021). Mapping road traffic crash hotspots using GIS-based methods: A case study of Muscat Governorate in the Sultanate of Oman. Spatial Statistics, 42, 100458.
-Alfarraj, O., Baihan, A., & Baihan, M. (2015). Design and Development of a Smart Sensing Kit for the Detection of Accident Location Using Smartphone. Sensor Letters, 13. doi.org/10.1166/sl.2015.3444
-Chang, S.-H., Lin, C.-Y., Fung, C. P., Hwang, J. R., & Doong, J.L. (2008). Driving performance assessment: Effects of traffic accident location and alarm content. Accident Analysis & Prevention, 40(5), 1637-1643. doi.org/10.1016/j.aap.2008.05.003
-Gutierrez-Osorio, C., & Pedraza, C. (2020). Modern data sources and techniques for analysis and forecast of road accidents:
A review. Journal of Traffic and Transportation Engineering (English Edition), 7(4), 432-446.
-Josef, M. (2009). Identification of Accident Location by Use of GPS and Possibilities of its Application 4th IRTAD Conference, Seoul.
-Maduako, I., Ebinne, E., Uzodinma, V., Okolie, C., & Chiemelu, E. (2022). Computing traffic accident high-risk locations using graph analytics. Spatial Information Research, 30(4), 497-511.
-Shahzad, M. (2020). Review of road accident analysis using GIS technique. International Journal of Injury Control and Safety Promotion, 27(4), 472-481.
-Sun, R., Zhang, C., Xiang, Y., Hou, L., & Wang, B. (2022). Identification Method for Crash-Prone Sections of Mountain Highway under Complex Weather Conditions. Sustainability, 14(22), 15181.
-Wong, D. K. Y., Pitfield, D. E., Caves, R. E., & Appleyard, A. J. (2009). The development of a more risk-sensitive and flexible airport safety area strategy: Part II. Accident location analysis and airport risk assessment case studies.
Safety Science, 47(7), 913-924.
-Zheng, H., Zhang, Y., Zhao, J., Liu, J., & Zeng, Q. (2018). Applications of Fuzzy Multicriteria Decision Making to Complex Engineering Problems. Advances in Fuzzy Systems, 1-3. doi.org/10.1155/2018/4536234