پژوهشنامه حمل و نقل

پژوهشنامه حمل و نقل

ارائه مدل ترکیبی به منظور پیش‌بینی تصادفات شهری بر اساس پارامترهای ساختار مکانی شبکه معابر (رویکرد مطالعه موردی)

نوع مقاله : مقاله پژوهشی

نویسنده
دانش آموخته کارشناسی ارشد، گروه مهندسی نقشه‌برداری و اطلاعات مکانی، دانشکده مهندسی‌، دانشگاه تهران، تهران، ایران
10.22034/tri.2021.234253.2778
چکیده
امروزه ایمنی جاده‌ای یکی از دغدغه‌های بزرگ مهندسان ترافیک است، زیرا تصادفات اثرات زیادی روی زندگی مردم داشته‌اند. بنابراین پیش‌بینی قطعات حادثه‌خیز شبکه معابر جهت جلوگیری از وقوع تصادفات آتی و بهبود ایمنی ترافیک بسیار حائز اهمیت است. یکی از مهم‌ترین عواملی که باعث بروز تصادفات می‌شود، ساختار مکانی شبکه معابر است. ساختار مکانی شبکه معابر مرتبط با آرایش و چیدمان اجزای شبکه معابر است که به عنوان یک قید مکانی بر جریانات شهری بسیار تأثیرگذار است. نوآوری تحقیق حاضر ارائه یک رویکرد ترکیبی جدید جهت تعیین پارامترهای ساختار مکانی مؤثر در پیش‌بینی قطعات حادثه‌خیز (منطقه سه شهر تهران) است. در این راستا از ترکیب رگرسیون وزن‌دار مکانی (کرنل‌های نمایی و مربع دوگانه) و الگوریتم بهینه‌سازی ازدحام ذرات گسسته استفاده گردید. روش ترکیبی پیشنهادی مناسب برای مسائل رگرسیون مکانی است، زیرا این روش با دو خواص منحصر به فرد داده‌های مکانی یعنی خودهمبستگی مکانی و ناایستایی مکانی سازگار است. بهترین مقدار تابع برازش (1-R2) برای کرنل‌های نمایی و مربع دوگانه به ترتیب 0.064 و 0.003 به دست آمد. هم‌چنین مشخص شد که پارامترهای ساختار مکانی تأثیر قابل توجهی بر پیش‌بینی قطعات حادثه‌خیز در منطقه موردمطالعه دارند.
کلیدواژه‌ها
موضوعات

عنوان مقاله English

Presenting an integrated model for predicting urban accidents based on spatial structure parameters of the road network (case study approach)

نویسنده English

Seyed Ahmad Eslami Nezhad
M.Sc., Grad., Department of surveying and Geomatics Engineering, College of Engineering, University of Tehran, Tehran, Iran.
چکیده English

Today, road safety is a great concern for traffic engineers, because accidents have imposed extensive impacts on the quality of people’s life. Therefore, it is very important to predict accident-prone sections of the road network to prevent future accidents and improve traffic safety. One of the most important factors that cause accidents is the spatial structure of the road network. The spatial structure of the road network is related to the arrangement and layout of the road network components, which as a spatial constraint is very influential on urban flows. The novelty of this study is to present a new combination approach to determine the effective spatial structure parameters in predicting accident-prone sections (District 3 of Tehran city). In this regard, the combination of geographically weighted regression (exponential and bi-square kernels) and binary particle swarm optimization algorithm was used. The recommended combination method is suitable for spatial regression problems, because it is compatible with two unique properties of spatial data, i.e. spatial autocorrelation and spatial non-stationarity. The best value of the fitness function (1-R2) for exponential and bi-square kernels was obtained 0.064 and 0.003, respectively. It also found that spatial structure parameters had a significant impact on predicting accident-prone sections in the study area.

کلیدواژه‌ها English

Binary Particle Swarm Optimization
Geographically Weighted Regression
Spatial Structure
Road Network
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