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Sustainability Implications of Emerging Transportation Technologies
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Sustainability Implications of Emerging Transportation Technologies

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Urban and Rural Development".

Deadline for manuscript submissions: closed (20 April 2023) | Viewed by 9853

Special Issue Editors

Dr. Yuche Chen

E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, University of South Carolina, Columbia, SC 29208, USA
Interests: transportation and sustainability; AI-augmented simulation and optimization of transportation and urban infrastructure systems
Special Issues, Collections and Topics in MDPI journals
Dr. Gurcan Comert

E-Mail Website
Guest Editor
Computer Science, Physics and Engineering Department, Benedict College, Columbia, SC 29204, USA
Interests: intelligent transportation systems; connected vehicles; urban air mobility; resilient transportation networks; and statistical modeling of different problems for traffic signals; freeway operations; air quality monitoring
Professor Jianyou Zhao

E-Mail Website
Guest Editor
School of Automobile, Chang’an University, Xi’an 710061, China
Interests: transportation planning; safety and logistics
Professor Zhongxiang Feng

E-Mail Website
Guest Editor
School of Automobile and Traffic Engineering, Hefei University of Technology, Hefei 230009, China
Interests: traffic safety; driving behavior; transportation planning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Worldwide, cities and regions have witnessed the development of novel transportation technologies and systems (e.g., electric vehicles, connected and autonomous vehicles, urban air mobility, ridesharing, on-demand ride services, etc.) in recent decades. While these novel technologies can improve the transportation system’s efficiency, they also have the potential to improve sustainability and mitigate anthropogenic impacts in the transportation system. However, the sustainability implications of novel technologies are not sufficiently studied in the literature. For example, connected and autonomous vehicles appear to reduce the driving burden and provide better vehicle coordination, but hey might also induce drivers to live further away from work and take longer commute distances. Additionally, ridesourcing (e.g., Uber/Lyft modes) and ridesharing (e.g., Uberpool modes) appear to reduce the cost of vehicle ownership. The reduced driving costs may induce more trips and spur excessive vehicle use. Therefore, these emerging technologies may not always have positive environmental impacts, and additional investigation is needed to comprehensively study their sustainability implications. In particular, the impact analysis is especially  complicated when it takes the perspective of the life cycle. Overall, more work is needed to refine our knowledge of the net effect of emerging transportation technologies on sustainability metrics.

This Special Issue aims to collect high-quality original research to comprehensively understand sustainability implications of emerging transportation technologies to inform transportation authorities and practitioners on how to plan, manage, and regulate the transportation system in the context of these new technologies to achieve sustainability goals.

Dr. Yuche Chen
Dr. Gurcan Comert
Professor Jianyou Zhao
Professor Zhongxiang Feng
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

  • emerging transportation technologies
  • connected and autonomous vehicles
  • urban air mobility
  • ridesourcing and ridesharing
  • sustainability impacts
  • life cycle analysis

Published Papers (4 papers)

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Research

17 pages, 1856 KiB  
Article
Sustainable Internet of Vehicles System: A Task Offloading Strategy Based on Improved Genetic Algorithm
by Kun Wang, Xiaofeng Wang and Xuan Liu
Sustainability 2023, 15(9), 7506; https://doi.org/10.3390/su15097506 - 04 May 2023
Cited by 2 | Viewed by 1204
Abstract
“Smart transportation” promotes urban sustainable development. The Internet of Vehicles (IoV) refers to a network with huge interaction, which comprises location, speed, route information, and other information about vehicles. To address the problems that the existing task scheduling models and strategies are mostly [...] Read more.
“Smart transportation” promotes urban sustainable development. The Internet of Vehicles (IoV) refers to a network with huge interaction, which comprises location, speed, route information, and other information about vehicles. To address the problems that the existing task scheduling models and strategies are mostly single and the reasonable allocation of tasks is not considered in these strategies, leading to the low completion rate of unloading, a task offloading with improved genetic algorithm (GA) is proposed. At first, with division in communication and calculation models, a system utility function maximization model is objectively conducted. The problem is solved by improved GA to obtain the scheme of optimal task offloading. As GA, in the traditional sense, inclines to a local optimum, the model herein introduces a Halton sequence for uniform initial population distribution. Additionally, the authors also adapt improved GA for the problem model and global optimal solution guarantee, thus improving the rate of task completion. Finally, the proposed method is proven through empirical study in view of scenario building. The experimental demonstration of the proposed strategy based on the built scenario shows that the task calculation completion rate is not less than 75%, and when the vehicle terminal is 70, the high-priority task completion rate also reaches 90%, which can realize reasonable allocation of computing resources and ensure the successful unloading of tasks. Full article
(This article belongs to the Special Issue Sustainability Implications of Emerging Transportation Technologies)
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27 pages, 2211 KiB  
Article
The Role of Multimodal Transportation in Ensuring Sustainable Territorial Development: Review of Risks and Prospects
by Irina Makarova, Azhar Serikkaliyeva, Larysa Gubacheva, Eduard Mukhametdinov, Polina Buyvol, Aleksandr Barinov, Vladimir Shepelev and Gulnaz Mavlyautdinova
Sustainability 2023, 15(7), 6309; https://doi.org/10.3390/su15076309 - 06 Apr 2023
Viewed by 4061
Abstract
The Russian Arctic development is an investment direction, which is planned through a system of so-called “support zones” of various development degrees, it is a priority for Russia and can have a positive effect. Since integrated territorial development is associated with significant cargo [...] Read more.
The Russian Arctic development is an investment direction, which is planned through a system of so-called “support zones” of various development degrees, it is a priority for Russia and can have a positive effect. Since integrated territorial development is associated with significant cargo flows of raw materials, materials and goods, logistics chains will include various transport modes, which will lead to the development of infrastructure (including the construction and reconstruction of seaports, the network of the railways and roads expansion) and the emergence of new international transport corridors (ITCs). A scientifically based solution to the problems of constructing a delivery route, including the location of transshipment points, logistics terminals and the rolling stock selection, will ensure the sustainable territories development through which ITCs pass. However, these tasks, which constitute the activity of organizing multimodal transportation, are associated with various types of risks, the successful solution of which, in this case, depends on the sustainable territorial development of these territories. Therefore, the research objective is to establish the relationship between the development of transport networks and the development of the Arctic region, the designation of possible prospects for the development of both multimodal transportation as a whole as a strategic event, and the contribution of each kind of transport, as well as the risks of creating and using international transport corridors, including cumulative impact on the environment. As a result of the literature analysis, we have considered the causes and consequences of the improper planning of supply chains and infrastructure, then we have indicated the role of new transport corridors in the development of territories. We have built a tree of problems in order to systematize risk situations and identify root causes and consequences. A method for calculating the cargo delivery time is proposed, taking into account the multimodality of logistics chains as well as measures that help reduce risks. Full article
(This article belongs to the Special Issue Sustainability Implications of Emerging Transportation Technologies)
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21 pages, 3530 KiB  
Article
Cloud-Based Collaborative Road-Damage Monitoring with Deep Learning and Smartphones
by Akshatha Ramesh, Dhananjay Nikam, Venkat Narayanan Balachandran, Longxiang Guo, Rongyao Wang, Leo Hu, Gurcan Comert and Yunyi Jia
Sustainability 2022, 14(14), 8682; https://doi.org/10.3390/su14148682 - 15 Jul 2022
Cited by 8 | Viewed by 2235
Abstract
Road damage such as potholes and cracks may reduce ride comfort and traffic safety. This influence can be prevented by regular, proper monitoring and maintenance of roads. Traditional methods and existing methods of surveying are very time-consuming, expensive, require a lot of human [...] Read more.
Road damage such as potholes and cracks may reduce ride comfort and traffic safety. This influence can be prevented by regular, proper monitoring and maintenance of roads. Traditional methods and existing methods of surveying are very time-consuming, expensive, require a lot of human effort, and, thus, cannot be conducted frequently. A more efficient and cost-effective process is required to augment profilometer and traditional road-condition recognition systems. In this study, we propose deep-learning methods using smartphone data to devise a cost-effective and ad-hoc approach. Information from sensors on smartphones such as motion sensors and cameras are harnessed to detect road damage using deep-learning algorithms. In order to give heuristic and accurate information about the road damage, we used a cloud-based collaborative approach to fuse all the data and update a map frequently with these road-surface conditions. During the experiment, the deep-learning models achieved good prediction accuracy on our dataset, and the cloud-based fusion approach was able to group and merge the detections from different vehicles. Full article
(This article belongs to the Special Issue Sustainability Implications of Emerging Transportation Technologies)
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13 pages, 2734 KiB  
Article
Estimating Bounds of Aerodynamic, Mass, and Auxiliary Load Impacts on Autonomous Vehicles: A Powertrain Simulation Approach
by Yuche Chen, Ruixiao Sun and Xuanke Wu
Sustainability 2021, 13(22), 12405; https://doi.org/10.3390/su132212405 - 10 Nov 2021
Cited by 3 | Viewed by 1356
Abstract
Vehicle automation requires new onboard sensors, communication equipment, and/or data processing units, and may encourage modifications to existing onboard components (such as the steering wheel). These changes impact the vehicle’s mass, auxiliary load, coefficient of drag, and frontal area, which then change vehicle [...] Read more.
Vehicle automation requires new onboard sensors, communication equipment, and/or data processing units, and may encourage modifications to existing onboard components (such as the steering wheel). These changes impact the vehicle’s mass, auxiliary load, coefficient of drag, and frontal area, which then change vehicle performance. This paper uses the powertrain simulation model FASTSim to quantify the impact of autonomy-related design changes on a vehicle’s fuel consumption. Levels 0, 2, and 5 autonomous vehicles are modeled for two battery-electric vehicles (2017 Chevrolet Bolt and 2017 Nissan Leaf) and a gasoline powered vehicle (2017 Toyota Corolla). Additionally, a level 5 vehicle is divided into pessimistic and optimistic scenarios which assume different electronic equipment integration format. The results show that 4–8% reductions in energy economy can be achieved in a L5 optimistic scenario and an 10–15% increase in energy economy will be the result in a L5 pessimistic scenario. When looking at impacts on different power demand sources, inertial power is the major power demand in urban driving conditions and aerodynamic power demand is the major demand in highway driving conditions. Full article
(This article belongs to the Special Issue Sustainability Implications of Emerging Transportation Technologies)
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