شبیه سازی ماشین های خودران با استفاده از روش های یادگیری ماشین

نوع مقاله : علمی - پژوهشی

نویسندگان

1 دانشجوی دکتری حمل و نقل، گروه مهندسی عمران، واحد علوم و تحقیقات ، دانشگاه آزاد اسلامی، تبریز، ایران

2 استادیار، گروه مهندسی عمران، دانشکده فنی و مهندسی، دانشگاه آزاد اسلامی، واحد تبریز، ایران

3 استادیار، گروه مهندسی عمران، دانشکده فنی و مهندسی، دانشگاه محقق اردبیلی، اردبیل، ایران

4 دانشیار، گروه مهندسی کامپیوتر، دانشکده فنی و مهندسی، دانشگاه آزاد اسلامی، واحد تبریز، ایران

چکیده

افزایش جمعیت و گسترش شهرنشینی باعث افزایش ترافیک در شهرها، زمان و هزینه سفر، مصرف سوخت، آلودگی هوا و ... شده است. در چنین شرایطی، روش هایی لازم است که کارایی سیستم های حمل و نقل افزایش یابد. در این راستا، یکی از روش ­ها می ­تواند استفاده از ماشین­ های خودران باشد. این ماشین‌ها توجه محققین و صنایع را به خود جلب کرده ­اند به نحوی که بسیاری از کارشناسان حمل و نقل در حال حاضر بر روی توسعه‌ی این مفهوم کار می­ کنند.  این سیستم می ­تواند پایه ­ای برای رشد اقتصادی و توسعه کشورها باشد. در این مقاله، نقش ماشین ­های خودران در سیستم حمل و نقل مورد بحث قرار گرفته است. شاکله اصلی این تحقیق، استفاده از شبکه عصبی به عنوان یکی از روش ­های یادگیری ماشین است. وظیفه‌ی این قسمت، یادگیری سیستم و تصمیم ­گیری بر اساس حالت کنونی است. بدین منظور از ترکیب شبکه­ های عصبی Dense و Convolutional و شبیه­ ساز Udacity استفاده ‌شده است. این نحقیق نشان داد که این شبیه‌ساز می تواند موجب تسریع در فرآیند طراحی ماشین‌های خودران و پیاده ­سازی آ­ن ­ها شود. نتیجه به دست آمده نشانگر درصد مشابهت بالا بین ماشین کنترل شده توسط انسان و ماشین خودران حاصل از طرح پیاده­ سازی توسط شبیه ­ساز بود. 

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Simulation of Autonomous Vehicles by Using Machine Learning Methods

نویسندگان [English]

  • alireza hoveidafard 1
  • Sina Fard moradinia 2
  • Babak Golchin 3
  • Ali ghaffari 4
1 Ph.D. student in Transportation, Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tabriz, Iran
2 Assistant Professor, Department of Civil Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran
3 Assistant Professor, Department of Civil Engineering, University of Mohaghegh Ardabili, Ardabil, Iran
4 Associate Professor, Department of Computer Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran
چکیده [English]

Increasing population and urbanization have been caused many problems such as: increased traffic in cities, travel time, cost, fuel consumption, air pollution and so on. In the mentioned situation, some methods are needed to increase the safety and efficiency of the transportation system. In this regard, one of the programs that can be implemented to improve transportation is the use of Autonomous Vehicles. These vehicles have attracted the attention of researchers and industries, so that many transportation experts are currently working on this field. This system can act as the basis for economic growth and countries development. In the present study, the roles of AVs in transportation system have been discussed. The main structure of this project is neural network as one of the machine learning methods. The task of this section is to learn the system and make decisions based on the current condition.  Accordingly, the combinations of Dense and Convolutional neural networks and Udacity simulator have been used. It showed that the simulator can help to speed up the process and implementation of AVs. The results indicated that there is high similarity between human driving cars and AVs which are implemented by the Udacity simulator.

کلیدواژه‌ها [English]

  • Transportation System
  • Neural Network
  • Autonomous Vehicles
  • Machine Learning
  • Udacity Simulator
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