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Sustainability
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Cooperative, Connected, and Automated Mobility (CCAM) toward Sustainability
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Cooperative, Connected, and Automated Mobility (CCAM) toward Sustainability

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

Deadline for manuscript submissions: 31 January 2025 | Viewed by 1502

Special Issue Editor

Dr. Georgios Spanos

E-Mail Website
Guest Editor
Information Technologies Institute, Center for Research and Technology Hellas, 6th Km Thessaloniki, 57001 Thessaloniki, Greece
Interests: artificial intelligence (AI) for CCAM; cybersecurity in autonomous vehicles

Special Issue Information

Dear Colleagues,

We are pleased to announce the launch of a new Special Issue of Sustainability entitled “Cooperative, Connected, and Automated Mobility (CCAM) toward Sustainability”.

Undoubtedly, the advent of automated mobility in contemporary society—in which the achievement of Sustainable Development Goals (SDGs) is of utmost importance—is expected to lead to radical changes in the urban transportation research field toward sustainable and environmentally friendly transportation. Public transportation in relation to urban mobility will definitely play a prominent role as we work toward attaining these SDGs, since it is considered the most environmentally friendly means of transportation, whereby a large number of passengers can be transported at once compared to transportation by private cars.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Intelligent services for CCAM;
  • Architecture of intelligent transportation systems;
  • CCAM for urban transportation sustainability;
  • CCAM communication;
  • Cybersecurity in autonomous and automated vehicles;
  • CCAM performance evaluation;
  • Business models for CCAM;
  • CCAM use cases;
  • Software solutions for CCAM management.

We look forward to receiving your contributions.

Dr. Georgios Spanos
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

  • CCAM
  • AI
  • 5G automotives
  • software
  • cybersecurity
  • statistical analysis
  • environmental footprint

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Published Papers (2 papers)

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Research

26 pages, 9758 KiB  
Article
An Optimal Road Network Extraction Methodology for an Autonomous Driving-Based Demand-Responsive Transit Service Considering Operational Design Domains
by Boram Woo, Donghoun Lee, Yoojin Chang, Sungjin Park and Sehyun Tak
Sustainability 2024, 16(20), 8819; https://doi.org/10.3390/su16208819 - 11 Oct 2024
Viewed by 525
Abstract
In addition to addressing the labor shortage due to an aging population, the transition to autonomous vehicle (AV)-based mobility services offers enhanced efficiency and operational flexibility for public transportation. However, much of the existing focus has been on improving AV safety without fully [...] Read more.
In addition to addressing the labor shortage due to an aging population, the transition to autonomous vehicle (AV)-based mobility services offers enhanced efficiency and operational flexibility for public transportation. However, much of the existing focus has been on improving AV safety without fully considering road conditions and real-world service demand. This study contributes to the literature by proposing a comprehensive framework for efficiently integrating AV-based mobility services at the network level, addressing these gaps. The framework analyzes and optimizes service networks by incorporating actual demand patterns, quantifying road segment difficulty from an AV perspective, and developing an optimization model based on these factors. The framework begins by quantifying the operational difficulty of road segments through an evaluation of Operational Design Domains (ODDs), providing a precise measure of AV suitability under varying road conditions. It then introduces a quantitative metric to assess operational feasibility, considering factors such as the service margin, costs, and safety risks. Using these metrics alongside Genetic Algorithms (GAs), the framework identifies an optimal service network that balances safety, efficiency, and profitability. By analyzing real-world data from different mobility services, such as taxis, Demand-Responsive Transport (DRT), and Special Transportation Services (STSs), this study highlights the need for service-specific strategies to optimize AV deployment. The findings show that optimal networks vary with demand patterns and road difficulty, demonstrating the importance of tailored network designs. This research provides a scalable, data-driven approach for integrating AV services into public transportation systems and lays the foundation for further improvements by incorporating dynamic factors and broader urban contexts. Full article
(This article belongs to the Special Issue Cooperative, Connected, and Automated Mobility (CCAM) toward Sustainability)
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21 pages, 4013 KiB  
Article
The Impacts of Centralized Control on Mixed Traffic Network Performance: A Strategic Games Analysis
by Areti Kotsi, Ioannis Politis and Evangelos Mitsakis
Sustainability 2024, 16(15), 6343; https://doi.org/10.3390/su16156343 - 24 Jul 2024
Cited by 1 | Viewed by 653
Abstract
Cooperative Intelligent Transport Systems (C-ITS) address contemporary transportation challenges, as Connected Vehicles (CVs) can play a pivotal role in enhancing efficiency and safety. The role of central governing authorities in shaping traffic management policies for CVs influences decision-making processes and system performance. In [...] Read more.
Cooperative Intelligent Transport Systems (C-ITS) address contemporary transportation challenges, as Connected Vehicles (CVs) can play a pivotal role in enhancing efficiency and safety. The role of central governing authorities in shaping traffic management policies for CVs influences decision-making processes and system performance. In this work, the role of central governing authorities in the traffic management of a mixed traffic network is examined, integrating System Optimum principles with game theory. More specifically, we introduce and develop a framework that models and analyses the strategic interactions between different stakeholders in a mixed traffic environment, considering central governing authorities with varying levels of control. The results indicate how the various levels of control of a central governing authority may have an impact on the network in terms of traffic measures. Through a strategic games analysis, the trade-offs associated with centralized control mechanisms are demonstrated and recommendations are offered for policymakers and practitioners to optimize traffic management strategies. Full article
(This article belongs to the Special Issue Cooperative, Connected, and Automated Mobility (CCAM) toward Sustainability)
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