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Large-Scale Traffic Monitoring by Remote Sensing

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Urban Remote Sensing".

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 2535

Special Issue Editor


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Guest Editor
Regione Umbria (the Regional Government of Umbria), 06121 Perugia, Italy
Interests: statistical signal processing; sensor fusion; detection and estimation theory; positioning; traffic flow; intelligent transportation system; sustainable energy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The recent pandemic requires a rethinking of our cities. The topic of Large-Scale Traffic Monitoring by Remote Sensing plays an essential role in the smart city, for the authorities' choices. The sensor systems also include service providers for various applications, such as traffic management, traffic analysis, location-based services (LBS), and so on. The application field concerns localization, autonomous vehicles, Internet of things applications, vehicle traffic flow, and so on. Due to the large variety of technologies and standards involved, sensor systems typically need to account for several communication channel models, bandwidths, sampling rates, and asynchronicity of the recorded data. In this Special Issue of Remote Sensing, we solicit paper submissions of original works addressing fundamentals, supporting technologies, and technical issues on Large-Scale Traffic Monitoring for localization, tracking, and mapping traffic flow. The topics cover the design and analysis of the sensors systems but also concern the scope of application. This Special Issue of Remote Sensing aims at publishing novel results on the most recent developments in Large-Scale Traffic Monitoring. 

Dr. Guido De Angelis
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Advanced simultaneous localization, tracking, and mapping
  • Autonomous car
  • Cooperative and cloud simultaneous localization and mapping (SLAM)
  • Cooperative localization and distributed systems
  • Location based service
  • Localization methods for the Internet of things
  • Mobility models for tracking
  • Security and privacy issues
  • Smart city
  • Theoretical traffic flow
  • V2x communications
  • Vehicle Ad Hoc Networks (VANETs)
  • Sensors

Published Papers (1 paper)

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Research

18 pages, 10384 KiB  
Article
A RFID-Integrated Framework for Tag Anti-Collision in UAV-Aided VANETs
by Yixin He, Dawei Wang, Fanghui Huang, Yufei Zhang, Ruonan Zhang and Xiaohong Yan
Remote Sens. 2021, 13(22), 4500; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13224500 - 09 Nov 2021
Cited by 6 | Viewed by 2060
Abstract
In this paper, we investigate tags in anti-collision applications of radio frequency identification (RFID) technology in unmanned aerial vehicle (UAV)-aided vehicular ad hoc networks (VANETs). The integration of RFID technology in UAV-aided VANETs can provide reliable traffic-related services for vehicles. However, multiple tags’ [...] Read more.
In this paper, we investigate tags in anti-collision applications of radio frequency identification (RFID) technology in unmanned aerial vehicle (UAV)-aided vehicular ad hoc networks (VANETs). The integration of RFID technology in UAV-aided VANETs can provide reliable traffic-related services for vehicles. However, multiple tags’ simultaneous responses to a reader mounted on a UAV, denoted as tag collision, gravely affect the correct tag detection on each vehicle. Therefore, in order to decrease the collision probability and improve the throughput, we propose a multi-frequency tag identification method. In the proposed scheme, we devise a tag grouping method based on adaptive power control to make the reader dynamically match the optimal frame length. Based on the above matching results, we introduce a tag estimation method using the optimal weight to improve the accuracy of tag estimation. We theoretically analyze the closed-form expression of the security outage probability expression. Finally, our simulation results demonstrate that the proposed tag anti-collision scheme achieved significant performance superiority in terms of the throughput and identification time slots. Full article
(This article belongs to the Special Issue Large-Scale Traffic Monitoring by Remote Sensing)
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