شناسایی و اولویت بندی قطعات حادثه خیز مبتنی بر تئوری موجک و روش علت گرا

نوع مقاله : مقاله پژوهشی

نویسندگان

1 عضو هیئت علمی دانشکده مهندسی عمران، دانشگاه ارومیه

2 دانشجوی دکتری، گروه مهندسی عمران، دانشگاه صنعتی شاهرود

3 فارغ التحصیل کارشناسی ارشد، گروه مهندسی عمران، دانشگاه ارومیه

چکیده

قطعات حادثه خیز نقش مؤثری را در وقوع و تعداد تصادفات جاده ای دارند و اثرات اجتماعی و محیطی منفی بر عملکرد سیستم حمل و نقل می‌گذارند. بنابراین شناسایی و اولویت بندی قطعات حادثه خیز نقش مهمی را در راستای کاهش تصادفات، هزینه‌ها و بهبود سطح ایمنی جاده ها ایفا می‌کنند. با توجه به اهمیت تعیین مقاطع حادثه خیز، استفاده از روش‌های قطعه بندی پویا و اولویت بندی آن‌ها مبتنی بر تئوری موجک و روش علت گرا از اهداف اصلی این پژوهش است. در پایان، نتایج حاصل از روش‌های قطعه بندی و تئوری سیگنال موجکی در محور کرمانشاه - اسالم آباد غرب نشان داد که قطعات حادثه خیز بر اساس تراکم تصادفات رخ داده به صورت عمومی و محلی طبقه بندی می‌شوند. سپس، با بهره گیری از روش اولویت بندی علت گرا بر اساس فرآیند سلسله مراتبی در قطعات عمومی و محلی این نتیجه به دست آمد که قطعه S2 در فاصله ۵/۲ تا 5/1۱ کیلومتری از ابتدای مسیر در اولویت بالاتر قرار دارد؛ در حالی که قطعه S3 در فاصله 5/۷ تا 5/10 کیلومتری از ابتدای مسیر در اولویت پایین تر بهبود وضعیت ایمنی جاده‌ای است. این پژوهش در آینده نیز ممکن است به محققین در راستای بررسی بیشتر ترکیب توابع ریاضی با روش‌های هوش مصنوعی، روش‌های استدلال منطقی، روش‌های الگوریتم ماشین یادگیری به منظور قطعه بندی قطعات حادثه خیز به عنوان روش‌های قطعه بندی پویا کمک کند

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Identification and Prioritization of Accident-prone Segments Based on Wavelet Theory and Cause-oriented Method

نویسندگان [English]

  • Hamid shirmohammadi 1
  • Farhad hadadi 2
  • Saba Samadi 3
1 Faculty of Civil Engineering, Urmia University, Urmia
2 PhD student, Faculty of Civil Engineering, Shahrood University of Technology, Iran
3 M.S.c. graduated, Faculty of Civil Engineering, Urmia Uiversity
چکیده [English]

Accident-prone segments have a significant role in the occurrence and the number of road accidents. They impose negatively social and environmental effects on the performance of the transport system. Thus, identification and prioritization of these segments play positively a role in reducing accidents, costs, and improvement of safety level on roads. Due to the importance of determining the accident-prone segments, the aim of this study is to use dynamic segmentation and prioritization methods including wavelet theory and cause-oriented methods. Therefore, results from the segmentation and wavelet signal theory on the Kermanshah-West Islamabad Road indicated that accident-prone segments are classified as main and local segments. Then, the cause-oriented prioritization method based on the analytical hierarchy process method for main and local segments showed that the S2 section, which ranges from about 2.5 km to 11.5 km from the beginning of the road is in the higher priority. However, the S3 section which ranges from about 7.5 km to 10.5 km from the beginning of the road is the lower priority of the improvement of road safety. In the future, this paper may help researchers in order to examine a combination of arithmetic functions with artificial intelligence methods, logical reason methods, and SVM (Support Vector Machines) algorithm for segmentation accident-prone segments as dynamic segmentation methods.

کلیدواژه‌ها [English]

  • Accident-prone segments
  • road accidents
  • dynamic segmentation
  • wavelet theory
  • Cause-oriented prioritization
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