تشخیص وضعیت لغزندگی جاده با استفاده از تصاویر دوربین‌های جاده‌ایی مبتنی بر شبکه‌های عصبی پیچشی و یادگیری انتقالی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناسی ارشد، دانشکده مهندسی مکانیک، دانشگاه علم و صنعت ایران، تهران، ایران

2 استاد، دانشکده مهندسی مکانیک، دانشگاه علم و صنعت ایران، تهران، ایران

3 استادیار، دانشکده مهندسی خودرو، دانشگاه علم و صنعت ایران، تهران، ایران

چکیده

تشخیص وضعیت لغزندگی سطح جاده امری مهم در راستای افزایش امنیت جاده و سرنشینان و همچنین توسعه خودروهای خودران و فناوری‌های مرتبط با آن است. در این راستا پژوهش‌های مختلفی با روش‌ها و حسگرهای متفاوت، با استفاده از داده‌های گوناگونی نظیر تصویر، صوت و فرکانس موج صورت گرفتهاست. این مقاله بدون استفاده از حسگرها و روش‌های پرهزینه تنها با استفاده از تصاویر دوربین‌های مداربسته موجود در جاده‌ها و بهره‌گیری از شبکه‌های عصبی پیچشی انجام شده است. ایده اصلی پژوهش جاری استفاده از رویکرد یادگیری انتقالی است. بنابراین در ابتدا اهمیت و مزایای استفاده از یادگیری انتقالی، در قالب آموزش شبکه‌ای با ساختار InceptionNetv3 بیان شده است. در مرحله بعد با استفاده از چارچوبی جدید به نام GFNet، شبکه عصبی پیچشی ResNet50 و شبکه عصبی بازگشتی با یکدیگر ترکیب و با استفاده از یادگیری انتقالی آموزش داده شده‌اند. درنهایت شبکه‌ای با توانایی تشخیص سطح جاده، در سه دسته خشک، خیس و برفی با دقتی بالغ ‌بر 96% به‌دست آمده است.

کلیدواژه‌ها


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دوره 10، شماره 2 - شماره پیاپی 38
شماره پیاپی 38، فصلنامه تابستان
مهر 1401
صفحه 105-116
  • تاریخ دریافت: 17 مرداد 1400
  • تاریخ بازنگری: 08 بهمن 1400
  • تاریخ پذیرش: 18 مرداد 1401
  • تاریخ انتشار: 01 مهر 1401