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Sensors
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Autonomous Transportation and Smart Cities
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Autonomous Transportation and Smart Cities

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (20 January 2023) | Viewed by 4576

Special Issue Editor

Prof. Dr. Hossam A. Gaber

E-Mail Website
Guest Editor
Department of Energy and Nuclear Engineering, Faculty of Engineering and Applied Science, Ontario Tech University, Oshawa, ON L1G 0C5, Canada
Interests: esilient smart energy grid and micro-energy grid planning, control, and protection; advanced plasma generation and applications in fusion energy; advanced safety and control systems for nuclear power plants; safety engineering, fault diagnosis, and real-time simulation; risk-based energy conservation; smart green buildings; process systems engineering of the energy and nuclear facilities and oil and gas production plants
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

World is moving towards autonomous transportation to achieve better mobility, increase profit of infrastructures, and reduce greenhouse gas emissions and risks. It will also enhance serviceability offerings in smart cities. This special issue will publish papers that reflect research and innovation in the area of autonomous transportation in smart cities, that include, but limited to, the following main topics: technology development and deployment of Connected and Autonomous Vehicles (CAV); infrastructure changes; vehicle technology aspects; modeling and simulation; use cases and performance evaluation; assessment of control strategies; accessibility features in autonomous transportation; interactions with infrastructures; human factors and interactions; computational intelligence, learning, and reasoning with data analytics; communications and cybersecurity systems; planning and management of autonomous transportation and mobility; interactions with robots and drones; and smart city planning. 

Prof. Dr. Hossam A. Gaber
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. Sensors 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 2600 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

  • connected and autonomous vehicles
  • transportation infrastructures
  • CAV
  • communication
  • cybersecurity
  • robotics
  • deep learning
  • smart cities
  • CAV test platform
  • robot-assisted CAV
  • CAV modeling and simulation
  • CAV deployment
  • V2V
  • V2I
  • V2X

Published Papers (1 paper)

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Review

24 pages, 19518 KiB  
Review
A Review on Technologies for Localisation and Navigation in Autonomous Railway Maintenance Systems
by Masoumeh Rahimi, Haochen Liu, Isidro Durazo Cardenas, Andrew Starr, Amanda Hall and Robert Anderson
Sensors 2022, 22(11), 4185; https://doi.org/10.3390/s22114185 - 31 May 2022
Cited by 5 | Viewed by 3970
Abstract
Smart maintenance is essential to achieving a safe and reliable railway, but traditional maintenance deployment is costly and heavily human-involved. Ineffective job execution or failure in preventive maintenance can lead to railway service disruption and unsafe operations. The deployment of robotic and autonomous [...] Read more.
Smart maintenance is essential to achieving a safe and reliable railway, but traditional maintenance deployment is costly and heavily human-involved. Ineffective job execution or failure in preventive maintenance can lead to railway service disruption and unsafe operations. The deployment of robotic and autonomous systems was proposed to conduct these maintenance tasks with higher accuracy and reliability. In order for these systems to be capable of detecting rail flaws along millions of mileages they must register their location with higher accuracy. A prerequisite of an autonomous vehicle is its possessing a high degree of accuracy in terms of its positional awareness. This paper first reviews the importance and demands of preventive maintenance in railway networks and the related techniques. Furthermore, this paper investigates the strategies, techniques, architecture, and references used by different systems to resolve the location along the railway network. Additionally, this paper discusses the advantages and applicability of on-board-based and infrastructure-based sensing, respectively. Finally, this paper analyses the uncertainties which contribute to a vehicle’s position error and influence on positioning accuracy and reliability with corresponding technique solutions. This study therefore provides an overall direction for the development of further autonomous track-based system designs and methods to deal with the challenges faced in the railway network. Full article
(This article belongs to the Special Issue Autonomous Transportation and Smart Cities)
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