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
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [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]