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Smart Transportation: Sustainable Design, Control and Management

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

Deadline for manuscript submissions: closed (15 August 2022) | Viewed by 8954

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Special Issue Editors

Dr. Mahyar Amirgholy

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Guest Editor

Department of Civil and Environmental Engineering, Kennesaw State University, Marietta, GA 30060, USA
Interests: cooperative control systems; smart transportation systems; urban network modeling; transportation economics; optimal traffic control; large-scale optimization
Special Issues, Collections and Topics in MDPI journals

Dr. Mehdi Nourinejad

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Guest Editor

Department of Civil Engineering, York University, Toronto, ON M3J 1P3, Canada
Interests: autonomous vehicles; mobility services; curbside management; ridesharing

Dr. Jidong J. Yang

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Guest Editor

College of Engineering, University of Georgia, Athens, GA 30602, USA
Interests: sustainable and resilient infrastructure systems; smart mobility systems; big data mining and analytics; deep learning methods and applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Technological advances in recent years have paved the way for the development of smart transportation systems. Artificial intelligence has made autonomous driving possible, and wireless communication has enabled automatic exchange of information between vehicles, infrastructure, and pedestrians. Navigation systems provide users with real-time information about traffic conditions, while smartphones allow travellers to choose their preferred mode of transport from a wide range of options, from shared micromobility to ridehailing modes. In addition to improvements in mobility and accessibility, advanced technologies also have an enormous potential for enhancing the sustainability of transportation systems. Exploiting the full potential of the advanced technologies also largely depends on upgrading archaic transportation infrastructure and legacy control systems, and developing novel management strategies in order to provide a sustainable design for transportation systems that are environmentally friendly, socially acceptable, and economically justifiable. In this Special Issue, we invite the submission of research papers that specifically address the potential of advanced and emerging technologies for enhancing the sustainability of transportation systems. The scope of this Special Issue is to cover state-of-the-art contributions on data curation and analysis, model development, policy design, and system management. Topics of interest with a general focus on smart and sustainable transportation include but are not limited to:

Social acceptance of smart transportation;
Travel behavior in smart cities;
Energy efficiency in connected/automated environments;
Cooperative traffic control for emission reduction;
Sustainable routing and carbon pricing;
Lane management and pricing;
Ride sourcing and autonomous driving;
Emerging micromobility and ridesharing services;
Public transportation and customized transit services;
Telecommunication and remote working;
Emerging business models and real-world applications.

Dr. Mahyar Amirgholy
Dr. Mehdi Nourinejad
Dr. Jidong J. Yang
Guest Editors

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

smart transportation
sustainable solution
system design
traffic control
demand management

Published Papers (2 papers)

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Research

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18 pages, 886 KiB

Open AccessArticle

Traffic Efficiency Models for Urban Traffic Management Using Mobile Crowd Sensing: A Survey

by Akbar Ali, Nasir Ayub, Muhammad Shiraz, Niamat Ullah, Abdullah Gani and Muhammad Ahsan Qureshi

Sustainability 2021, 13(23), 13068; https://doi.org/10.3390/su132313068 - 25 Nov 2021

Cited by 12 | Viewed by 3248

Abstract

The population is increasing rapidly, due to which the number of vehicles has increased, but the transportation system has not yet developed as development occurred in technologies. Currently, the lowest capacity and old infrastructure of roads do not support the amount of vehicles flow which cause traffic congestion. The purpose of this survey is to present the literature and propose such a realistic traffic efficiency model to collect vehicular traffic data without roadside sensor deployment and manage traffic dynamically. Today’s urban traffic congestion is one of the core problems to be solved by such a traffic management scheme. Due to traffic congestion, static control systems may stop emergency vehicles during congestion. In daily routine, there are two-time slots in which the traffic is at peak level, which causes traffic congestion to occur in an urban transportation environment. Traffic congestion mostly occurs in peak hours from 8 a.m. to 10 a.m. when people go to offices and students go to educational institutes and when they come back home from 4 p.m. to 8 p.m. The main purpose of this survey is to provide a taxonomy of different traffic management schemes for avoiding traffic congestion. The available literature categorized and classified traffic congestion in urban areas by devising a taxonomy based on the model type, sensor technology, data gathering techniques, selected road infrastructure, traffic flow model, and result verification approaches. Consider the existing urban traffic management schemes to avoid congestion and to provide an alternate path, and lay the foundation for further research based on the IoT using a Mobile crowd sensing-based traffic congestion control model. Mobile crowdsensing has attracted increasing attention in traffic prediction. In mobile crowdsensing, the vehicular traffic data are collected at a very low cost without any special sensor network infrastructure deployment. Mobile crowdsensing is very popular because it can transmit information faster, collect vehicle traffic data at a very low cost by using motorists’ smartphone or GPS vehicular embedded sensor, and it is easy to install, requires no special network deployment, has less maintenance, is compact, and is cheaper compared to other network options. Full article

(This article belongs to the Special Issue Smart Transportation: Sustainable Design, Control and Management)

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Review

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19 pages, 917 KiB

Open AccessReview

A Comprehensive Review of Path Planning for Agricultural Ground Robots

by Suprava Chakraborty, Devaraj Elangovan, Padma Lakshmi Govindarajan, Mohamed F. ELnaggar, Mohammed M. Alrashed and Salah Kamel

Sustainability 2022, 14(15), 9156; https://doi.org/10.3390/su14159156 - 26 Jul 2022

Cited by 24 | Viewed by 4466

Abstract

The population of the world is predicted to reach nine billion by 2050, implying that agricultural output must continue to rise. To deal with population expansion, agricultural chores must be mechanized and automated. Over the last decade, ground robots have been developed for a variety of agricultural applications, with autonomous and safe navigation being one of the most difficult hurdles in this development. When a mobile platform moves autonomously, it must perform a variety of tasks, including localization, route planning, motion control, and mapping, which is a critical stage in autonomous operations. This research examines several agricultural applications as well as the path planning approach used. The purpose of this study is to investigate the current literature on path/trajectory planning aspects of ground robots in agriculture using a systematic literature review technique, to contribute to the goal of contributing new information in the field. Coverage route planning appears to be less advanced in agriculture than point-to-point path routing, according to the finding, which is due to the fact that covering activities are usually required for agricultural applications, but precision agriculture necessitates point-to-point navigation. In the recent era, precision agriculture is getting more attention. The conclusion presented here demonstrates that both field coverage and point-to-point navigation have been applied successfully in path planning for agricultural robots. Full article

(This article belongs to the Special Issue Smart Transportation: Sustainable Design, Control and Management)

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