منوی کاربری
  • پشتیبانی: ۴۲۲۷۳۷۸۱ - ۰۴۱
  • سبد خرید

دانلود رایگان مقاله انگلیسی الگوریتم کلونی مورچه با اینترنت وسایل نقلیه برای سیستم کنترل ترافیک هوشمند - الزویر 2018

عنوان فارسی
الگوریتم بهینه سازی کلونی مورچه با اینترنت وسایل نقلیه برای سیستم کنترل ترافیک هوشمند
عنوان انگلیسی
Ant colony optimization algorithm with Internet of Vehicles for intelligent traffic control system
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
23
سال انتشار
2018
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
نوع مقاله
ISI
نوع نگارش
مقالات پژوهشی (تحقیقاتی)
رفرنس
دارد
پایگاه
اسکوپوس
کد محصول
E10120
رشته های مرتبط با این مقاله
مهندسی کامپیوتر
گرایش های مرتبط با این مقاله
الگوریتم ها و محاسبات
مجله
شبکه های کامپیوتری - Computer Networks
دانشگاه
School of Information Technology and Engineering - VIT University - Vellore - India
کلمات کلیدی
اینترنت وسایل نقلیه؛ کنترل ترافیک موثر؛ انتخاب کوتاهترین مسیر؛ الگوریتم Dijkstra؛ الگوریتم Kruskal؛ الگوریتم Prim
doi یا شناسه دیجیتال
https://doi.org/10.1016/j.comnet.2018.07.001
۰.۰ (بدون امتیاز)
امتیاز دهید
چکیده

Abstract


Vehicles present on the Internet of Vehicles (IoV) can communicate with each other in order to determine the status of the road and vehicle in real time. These parameters are used to estimate the average speed and identify the optimal route to reach the destination. However, the government traffic departments are unable to use these valuable traffic data and thus more traffic jam, congestion and road accident occurs. In order to overcome this issue, this paper proposes an effective traffic control system with the help of IoV technology. The proposed method is demonstrated in the study are of Vellore district, Tamil Nadu, India. The street maps are segmented into number small number of distinct maps. Ant colony algorithm is applied to each map in order to find the optimal route. In addition, Fuzzy logic based traffic intensity calculation function is proposed in this paper to model the heavy traffic. The proposed IoV based route selection method is compared with the existing shortest path selection algorithms such as Dijikstra algorithm, Kruskal’s algorithm and Prim’s algorithm. The experimental results proved the good performance of the proposed IoV based route selection method.

نتیجه گیری

Conclusion


This paper proposed a novel IoV based traffic management method to prevent heavy traffic formation and accidents. The proposed method is demonstrated on the study are of Vellore district, Tamil Nadu, India. The street maps are segmented into number small number of distinct maps. Ant colony algorithm is applied on each map in order to find the optimal route. In addition, Fuzzy logic based traffic intensity calculation function is proposed in this paper to model the heavy traffic. The future work of this paper is to use the proposed IoV based traffic management method for a continuous health monitoring system.


بدون دیدگاه