دانلود مقاله ISI انگلیسی شماره 70554
ترجمه فارسی عنوان مقاله

پروتکل های روش نمونه گیری شبکه های Ad-Hoc وسایل نقلیه برای نظارت بر ترافیک و تشخیص حادثه در سیستم های حمل و نقل هوشمند

عنوان انگلیسی
Vehicular Ad-Hoc Networks sampling protocols for traffic monitoring and incident detection in Intelligent Transportation Systems
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
70554 2015 18 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Transportation Research Part C: Emerging Technologies, Volume 56, July 2015, Pages 177–194

ترجمه کلمات کلیدی
نظارت بر ترافیک وسایل نقلیه؛ VANET؛ تشخیص حادثه؛ الگوریتم های توزیع شده؛ مجموعه FCD؛ ارتباطات چند هاپ
کلمات کلیدی انگلیسی
Vehicular traffic monitoring; VANET; Incident detection; Distributed algorithms; FCD collection; Multi-hop communications
پیش نمایش مقاله
پیش نمایش مقاله  پروتکل های روش نمونه گیری شبکه های Ad-Hoc وسایل نقلیه برای نظارت بر ترافیک و تشخیص حادثه در سیستم های حمل و نقل هوشمند

چکیده انگلیسی

Vehicular Ad-Hoc Networks (VANETs) are an emerging technology soon to be brought to everyday life. Many Intelligent Transport Systems (ITS) services that are nowadays performed with expensive infrastructure, like reliable traffic monitoring and car accident detection, can be enhanced and even entirely provided through this technology. In this paper, we propose and assess how to use VANETs for collecting vehicular traffic measurements. We provide two VANET sampling protocols, named SAME and TOME, and we design and implement an application for one of them, to perform real time incident detection. The proposed framework is validated through simulations of both vehicular micro-mobility and communications on the 68 km highway that surrounds Rome, Italy. Vehicular traffic is generated based on a large real GPS traces set measured on the same highway, involving about ten thousand vehicles over many days. We show that the sampling monitoring protocol, SAME, collects data in few seconds with relative errors less than 10%, whereas the exhaustive protocol TOME allows almost fully accurate estimates within few tens of seconds. We also investigate the effect of a limited deployment of the VANET technology on board of vehicles. Both traffic monitoring and incident detection are shown to still be feasible with just 50% of equipped vehicles.