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Sustainability
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Transport Sustainability and Smart Cities
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Transport Sustainability and Smart Cities

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 6469

Special Issue Editor

Dr. Saeed Asadi Bagloee

E-Mail Website
Guest Editor
Department of Transport Engineering, The University of Melbourne, Parkville VIC 3010, Australia
Interests: large scale optimization; transport planning; connected and autonomous vehicles; machine learning

Special Issue Information

Resources are limited, global warming is on the rise, and traffic congestion is widespread, all of which necessitate the development of a sustainable transportation system. Advanced communication technologies, electric vehicle (EV), blockchain, data science, 5G, better optimization techniques, and the emergence of connected and autonomous vehicles (CAV) can all be used to promote sustainability in the transportation. This Special Issue will explore the importance of modern technologies and concepts in communication, AI, and software/hardware in promoting sustainable transport as one of the main pillars of smart cities.

The main focus of this Special Issue is on transport substantiality in the modern era of communication, 5G, CAV, AI, EV, and blockchain. Hence, the purpose is to bring sustainability to the top of the agenda of researchers and policy-makers, highlighting the duty of the current generation to leave the planet livable and in better shape for the next generation, a goal that modern technologies have made easier.

The scope of the Special Issue covers the following:

  • To what extent can blockchain technology be applied in transport substantiality concerns?
  • What does the future of EV hold, in terms of lithium batteries and the range anxiety?
  • Can alternative fuel (like hydrogen) be a reality soon and how?
  • What lessons can we draw from CAV related to transport substantiality?
  • What opportunities can 5G technology bring to transport sustainability?
  • Data analytic, AI, and ML as the operating systems of sustainable smart cities
  • New transport modeling, such as predictive modeling in sustainable transport and traffic control
  • Disruptive transport policies such as no-car zones in promoting sustainability
  • Mobility as a service as a new dimension of substantiality
  • Mobile apps for transport sustainability
  • Smart freight and drone delivery

Dr. Saeed Asadi Bagloee
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. Sustainability 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 2400 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

  • blockchain
  • smart sustainability
  • machine learning
  • 5G
  • connected and autonomous vehicle CAV
  • electric vehicle
  • alternative fuel
  • drone delivery

Published Papers (2 papers)

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Research

24 pages, 10017 KiB  
Article
Incorporating Drone and AI to Empower Smart Journalism via Optimizing a Propagation Model
by Faris A. Almalki, Maha Aljohani, Merfat Algethami and Ben Othman Soufiene
Sustainability 2022, 14(7), 3758; https://doi.org/10.3390/su14073758 - 22 Mar 2022
Cited by 9 | Viewed by 3403
Abstract
In the recent digital age, information and communication technologies are rapidly contributing to remodel the media and journalism. Numerous technologies can be utilized by the media industry to capture news or events, taking footage and pictures of a breaking news. Technology and the [...] Read more.
In the recent digital age, information and communication technologies are rapidly contributing to remodel the media and journalism. Numerous technologies can be utilized by the media industry to capture news or events, taking footage and pictures of a breaking news. Technology and the media are interwoven, and neither can be detached from contemporary society in most nations. Unsurprisingly, technology has affected how and where information is shared. Nowadays, it is impractical to discuss media and the methods in which societies communicate without addressing the rapidity of technology change. Thus, the aerial journalism term has emerged, which refers to the ability of creating and conveying media content in a timely and efficient fashion. This work aims to integrate a drone with AI to empower aerial journalism via training a neural network to obtain an accurate channel using the NN-RBFN approach. The proposed work can enhance aerial media missions including investigative reporting (e.g., humanitarian crises), footage of news events (e.g., man-made and/or natural disasters), and livestreams for short-term, large-scale events (e.g., Olympic Games). In our digital media era, such a smart journalism approach would help to become far more sustainable and an eco-efficient process. Both MATLAB and 3D Remcom Wireless Insite tools have been used to carry out the simulation work. Simulated results indicate that the proposed NN-RBFN managed to obtain an accurate channel propagation model in a 3D scenario with a high accuracy rate reaching 99%. The proposed framework also could offer various media and journalism services (e.g., high data rate, wider coverage footprint) in timely and cost-effective manners in both normal scenarios or even in hard-to-reach zones and/or short-term, large-scale events. Full article
(This article belongs to the Special Issue Transport Sustainability and Smart Cities)
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17 pages, 13114 KiB  
Article
Shared Automated Mobility with Demand-Side Cooperation: A Proof-of-Concept Microsimulation Study
by Lei Zhu, Zhouqiao Zhao and Guoyuan Wu
Sustainability 2021, 13(5), 2483; https://doi.org/10.3390/su13052483 - 25 Feb 2021
Cited by 6 | Viewed by 2283
Abstract
Most existing shared automated mobility (SAM) services assume the door-to-door manner, i.e., the pickup and drop-off (PUDO) locations are the places requested by the customers (or demand-side). While some mobility services offer more affordable riding costs in exchange for a little walking effort [...] Read more.
Most existing shared automated mobility (SAM) services assume the door-to-door manner, i.e., the pickup and drop-off (PUDO) locations are the places requested by the customers (or demand-side). While some mobility services offer more affordable riding costs in exchange for a little walking effort from customers, their rationales and induced impacts (in terms of mobility and sustainability) from the system perspective are not clear. This study proposes a demand-side cooperative shared automated mobility (DC-SAM) service framework, aiming to fill this knowledge gap and to assess the mobility and sustainability impacts. The optimal ride matching problem is formulated and solved in an online manner through a micro-simulation model, Simulation of Urban Mobility (SUMO). The objective is to maximize the profit (considering both the revenue and cost) of the proposed SAM service, considering the constraints in seat capacities of shared automated vehicles (SAVs) and comfortable walking distance from the perspective of customers. A case study on a portion of a New York City (NYC) network with a pre-defined fleet size demonstrated the efficacy and promise of the proposed system. The results show that the proposed DC-SAM service can not only significantly reduce the SAV’s operating costs in terms of vehicle-miles traveled (VMT), vehicle-hours traveled (VHT), and vehicle energy consumption (VEC) by up to 53, 46 and 51%, respectively, but can also considerably improve the customer service by 30 and 56%, with regard to customer waiting time (CWT) and trip detour factor (TDF), compared to a heuristic service model. In addition, the demand-side cooperation strategy can bring about additional system-wide mobility and sustainability benefits in the range of 4–10%. Full article
(This article belongs to the Special Issue Transport Sustainability and Smart Cities)
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