توسعه مدل‌های منعطف کلان نگر پیش‌بینی فراوانی تصادفات با در نظرگیری وابستگی‌های فضایی و اثرات مشاهده نشده ناهمسان‌ساز: مطالعه موردی شهر مشهد

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد، گروه مهندسی عمران، دانشکده مهندسی، دانشگاه فردوسی مشهد، مشهد، ایران

2 استادیار، گروه مهندسی عمران، دانشکده مهندسی، دانشگاه فردوسی مشهد، مشهد ، ایران

3 استادیار، گروه ریاضی و آمار، دانشکده علوم پایه، دانشگاه نیشابور، نیشابور، ایران

چکیده

در راستای دستیابی به سیستم حمل‌ونقل ایمن و کاهش عواقب جبران‌ناپذیر ناشی از سوانح ترافیکی نیاز است تا موضوع ایمنی ترافیک در کنار سایر اهداف برنامه‌ریزی حمل‌ونقل مانند آلودگی هوا، اقتصادی-جمعیتی و غیره موردبررسی قرار گیرد. در سال‌های اخیر استفاده از مدل‌های آماری برای کمی سازی اثر پارامترهای برنامه‌ریزی حمل‌ونقل بر ایمنی ترافیک و به دنبال آن ایجاد ارتباط بین برنامه‌ریزی حمل‌ونقل و ایمنی ترافیک، موردتوجه برنامه­ریزان قرارگرفته است. هدف پژوهش حاضر، توسعه مدل‌های کلان نگر پیش‌بینی تصادفات است که در سطح کلان اثر طیفی از ویژگی‌های نواحی ترافیکی شهر مشهد را بر فراوانی تصادفات مدل می‌کند. بدین منظور، علاوه بر مدل پواسون که متداول‌ترین و پایه‌ای‌ترین مدل پیش‌بینی تصادفات است، مدل‌های پواسون-لگ‌نرمال  و اتورگرسیو شرطی نیز برای در نظر گرفتن اثر بیش پراکنشی اطلاعات و وابستگی‌های فضایی مورداستفاده قرارگرفته است. جهت مقایسه مدل‌های پیشنهادی از معیار اطلاع انحرافی (DIC) استفاده‌شده است. نتایج مقایسه مدل‌ها نشان می‌دهد که در نظر گرفتن اثرات مشاهده نشده ناهمسان‌ساز و وابستگی فضایی به ترتیب توسط مدل‌های پواسون-لگ‌نرمال  و اتورگرسیو شرطی به‌طور قابل‌توجهی عملکرد مدل‌ها را ارتقا می‌بخشد و مقدار معیار DIC را از 41/4623 در مدل پواسون به ترتیب به 82/2066 و 28/2055، کاهش می‌دهد. قابل‌ذکر است که مدل اتورگرسیو شرطی (BYM) بهترین عملکرد را دارا است (28/2055= DIC)، که اهمیت در نظر گرفتن وابستگی فضایی در مدل‌های پیش‌بینی تصادفات را در تصحیح تخمین و همچنین جایگزینی برای متغیرهای در نظر گرفته نشده، برجسته می‌سازد.

کلیدواژه‌ها

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