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Sustainable Intelligent Transportation: Cooperative Systems and Vehicle Automation
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Sustainable Intelligent Transportation: Cooperative Systems and Vehicle Automation

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

Deadline for manuscript submissions: 30 June 2025 | Viewed by 5237

Special Issue Editors

Prof. Dr. Jia Hu

E-Mail Website
Guest Editor
College of Transportation Engineering, Tongji University, Shanghai 201804, China
Interests: vehicle–infrastructure cooperative decision making
Dr. Haoran Wang

E-Mail Website
Guest Editor
College of Transportation Engineering, Tongji University, Shanghai 201804, China
Interests: vehicle cooperative automation
Dr. Jintao Lai

E-Mail Website
Guest Editor
College of Transportation Engineering, Tongji University, Shanghai 201804, China
Interests: AV testing and simulation

Special Issue Information

Dear Colleagues,

Sustainability invites researchers and experts in the field of transportation to contribute to a Special Issue titled "Sustainable Intelligent Transportation: Cooperative Systems and Vehicle Automation." This Special Issue aims to explore the intersection of intelligent transportation, cooperative systems, and vehicle automation, with a strong focus on sustainability.

Intelligent transportation systems have revolutionized the way we move and interact with our transportation networks. These systems, driven by advanced technologies such as information technology, control technology, and computer technology, have significantly improved efficiency, safety, and reliability. However, with the pressing need to address environmental concerns and enhance sustainability in transportation, the concept of sustainable intelligent transportation has gained paramount importance.

Cooperative systems, which involve vehicles communicating and collaborating with each other and with infrastructure, hold great promise in improving transportation performance, reducing congestion, and enhancing safety. Additionally, vehicle automation technologies, including autonomous vehicles and driver assistance systems, have the potential to revolutionize transportation by reducing emissions, improving energy efficiency, and enhancing traffic flow.

This Special Issue aims to bring together researchers, practitioners, and experts from various disciplines to explore the latest advancements, challenges, and opportunities in sustainable intelligent transportation, with a specific focus on cooperative systems and vehicle automation. We welcome original research articles, reviews, and case studies covering a wide range of topics related to this theme, including but not limited to:

  • Cooperative systems for intelligent transportation;
  • Vehicle automation technologies and their impact on sustainability;
  • Intelligent transportation infrastructure and communication systems;
  • Energy-efficient routing and traffic management;
  • Sustainable mobility solutions and shared transportation services;
  • Intelligent transportation systems for smart cities;
  • Environmental impact assessment of intelligent transportation systems;
  • Policy and regulatory frameworks for sustainable intelligent transportation;
  • Human factors and user acceptance of cooperative systems and vehicle automation;
  • Safety and reliability of autonomous and cooperative vehicles.

We invite authors to submit their high-quality contributions to this Special issue. Manuscripts should adhere to the journal's guidelines for authors and will undergo a rigorous peer-review process. Accepted papers will be published in Sustainability, a reputable publication known for its commitment to advancing the field of transportation and sustainability.

Join us in shaping the future of sustainable intelligent transportation through cooperative systems and vehicle automation. We look forward to receiving your valuable contributions.

Prof. Dr. Jia Hu
Dr. Haoran Wang
Dr. Jintao Lai
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

  • sustainable transportation
  • cooperative system
  • vehicle automation
  • driver assistance
  • eco-driving
  • energy management

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Published Papers (4 papers)

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Research

16 pages, 1195 KiB  
Article
Carbon Emission Reduction Assessment of Ships in the Grand Canal Network Based on Synthetic Weighting and Matter-Element Extension Model
by Zhengchun Sun, Sudong Xu and Jun Jiang
Sustainability 2025, 17(1), 349; https://doi.org/10.3390/su17010349 - 5 Jan 2025
Viewed by 918
Abstract
Vessel traffic is an important source of global greenhouse gas emissions. The carbon emissions from ships in the canal network are directly linked to the environmental performance of China’s inland waterway transportation, contributing to the achievement of global carbon reduction goals. Therefore, systematically [...] Read more.
Vessel traffic is an important source of global greenhouse gas emissions. The carbon emissions from ships in the canal network are directly linked to the environmental performance of China’s inland waterway transportation, contributing to the achievement of global carbon reduction goals. Therefore, systematically assessing the carbon emission reduction levels of ships in canal networks is essential to provide a robust foundation for developing more scientific and feasible emission reduction strategies. To address the limitations of current evaluations—which often focus on a single dimension and lack an objective, quantitative representation of the mechanisms driving carbon emission and their synergistic effects—this study took a comprehensive approach. First, considering the factors influencing ship carbon emissions and emission reduction strategies, an evaluation index system was developed. This system included 6 first-level indexes and 22 s-level indexes, covering aspects such as energy utilization, technical equipment, and economic benefits. Second, a novel combination of methods was used to construct an evaluation model. Qualitative weights, determined through the interval binary semantic method, were integrated with quantitative weights calculated using the CRITIC method. These were then combined and assigned using a game-theory-based comprehensive assignment method. The resulting evaluation model, built upon the theory of matter-element topology, represents a significant methodological innovation. Finally, the evaluation method was applied to the empirical analysis of ships operating in Jiangsu section of the Beijing–Hangzhou Grand Canal. This application demonstrated the model’s specificity and feasibility. The study’s findings provide valuable insights for improving carbon emission reduction levels for inland ships and advancing the sustainable development of the shipping industry. Full article
(This article belongs to the Special Issue Sustainable Intelligent Transportation: Cooperative Systems and Vehicle Automation)
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18 pages, 2193 KiB  
Article
Evaluation of Autonomous Driving Safety by Operational Design Domains (ODD) in Mixed Traffic
by Hoseon Kim, Jieun Ko, Cheol Oh and Seoungbum Kim
Sustainability 2024, 16(22), 9672; https://doi.org/10.3390/su16229672 - 6 Nov 2024
Viewed by 962
Abstract
This study derived effective driving behavior indicators to assess the driving safety of autonomous vehicles (AV). A variety of operation design domains (ODD) in urban road networks, which include intersections, illegal parking, bus stop, bicycle lanes, and pedestrian crossings, were taken into consideration [...] Read more.
This study derived effective driving behavior indicators to assess the driving safety of autonomous vehicles (AV). A variety of operation design domains (ODD) in urban road networks, which include intersections, illegal parking, bus stop, bicycle lanes, and pedestrian crossings, were taken into consideration in traffic simulation analyses. Both longitudinal and interaction driving indicators were investigated to identify the driving performance of AVs in terms of traffic safety in mixed traffic stream based on simulation experiments. As a result of identifying the appropriate evaluation indicator, time-varying stochastic volatility (VF) headway time was selected as a representative evaluation indicator for left turn and straight through signalized intersections among ODDs related to intersection types. VF headway time is suitable for evaluating driving ability by measuring the variation in driving safety in terms of interaction with the leading vehicle. In addition to ODDs associated with intersection type, U-turns, additional lane segments, illegal parking, bus stops, and merging lane have common characteristics that increase the likelihood of interactions with neighboring vehicles. The VF headway time for these ODDs was derived as driving safety in terms of interaction between vehicles. The results of this study would be valuable in establishing a guideline for driving performance evaluation of AVs. The study found that unsignalized left turns, signalized right turns, and roundabouts had the highest risk scores of 0.554, 0.525, and 0.501, respectively, indicating these as the most vulnerable ODDs for AVs. Additionally, intersection and mid-block crosswalks, as well as bicycle lanes, showed high risk scores due to frequent interactions with pedestrians and cyclists. These areas are particularly risky because they involve unpredictable movements from non-vehicular road users, which require AVs to make rapid adjustments in speed and trajectory. These findings provide a foundation for improving AV algorithms to enhance safety and establishing objective criteria for AV policy-making. Full article
(This article belongs to the Special Issue Sustainable Intelligent Transportation: Cooperative Systems and Vehicle Automation)
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20 pages, 3598 KiB  
Article
Dynamic Multi-Function Lane Management for Connected and Automated Vehicles Considering Bus Priority
by Zhen Zhang, Lingfei Rong, Zhiquan Xie and Xiaoguang Yang
Sustainability 2024, 16(18), 8078; https://doi.org/10.3390/su16188078 - 15 Sep 2024
Viewed by 1300
Abstract
Bus lanes are commonly implemented to ensure absolute priority for buses at signalized intersections. However, while prioritizing buses, existing bus lane management strategies often exacerbate traffic demand imbalances among lanes. To address this issue, this paper proposes a dynamic Multi-Function Lane (MFL) management [...] Read more.
Bus lanes are commonly implemented to ensure absolute priority for buses at signalized intersections. However, while prioritizing buses, existing bus lane management strategies often exacerbate traffic demand imbalances among lanes. To address this issue, this paper proposes a dynamic Multi-Function Lane (MFL) management strategy. The proposed strategy transforms traditional bus lanes into Multi-Function Lanes (MFLs) that permit access to Connected and Automated Vehicles (CAVs). By fully utilizing the idle right-of-way of the MFL, the proposed strategy can achieve traffic efficiency improvement. To evaluate the proposed strategy, some experiments are conducted under various demand levels and CAV penetration rates. The results reveal that the proposed strategy (i) improves the traffic intensity balance degree by up to 52.9 under high demand levels; (ii) reduces delay by up to 80.56% and stops by up to 89.35% with the increase in demand level and CAV penetration rate; (iii) guarantees absolute bus priority under various demand levels and CAV penetration rates. The proposed strategy performs well even when CAV penetration is low. This indicates that the proposed strategy has the potential for real-world application. Full article
(This article belongs to the Special Issue Sustainable Intelligent Transportation: Cooperative Systems and Vehicle Automation)
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28 pages, 3620 KiB  
Article
Smart Insertion Strategies for Sustainable Operation of Shared Autonomous Vehicles
by Sapan Tiwari, Neema Nassir and Patricia Sauri Lavieri
Sustainability 2024, 16(12), 5175; https://doi.org/10.3390/su16125175 - 18 Jun 2024
Cited by 1 | Viewed by 1386
Abstract
As shared autonomous vehicles (SAV) emerge as an economical and feasible mode of transportation in modern cities, effective optimization models are essential to simulate their service. Traditional optimization approaches, based on first-come-first-served principles, often result in sub-optimal outcomes and, more notably, can impact [...] Read more.
As shared autonomous vehicles (SAV) emerge as an economical and feasible mode of transportation in modern cities, effective optimization models are essential to simulate their service. Traditional optimization approaches, based on first-come-first-served principles, often result in sub-optimal outcomes and, more notably, can impact public transport (PT) operations by creating unnecessary competition. This study introduces four insertion strategies within the MATSim model of the Melbourne Metropolitan Area, addressing these challenges. Two strategies optimize SAV operations by considering overall network costs, and the other two make insertion decisions based on the available PT service in the network. The findings show that strategic insertions of the requests can significantly enhance SAV service quality by improving the vehicle load and decreasing vehicle and empty kilometers traveled per ride. The analysis indicates that these strategies are particularly effective for smaller fleet sizes, leading to an increased number of served rides and a more equitable distribution of wait times across the network, reflected in an improved Gini Index. The findings suggest that prioritization-based insertions significantly enhance service quality by prioritizing users with limited access to PT, ensuring that those with fewer PT options are served first, and encouraging a more integrated and sustainable urban transportation system. Full article
(This article belongs to the Special Issue Sustainable Intelligent Transportation: Cooperative Systems and Vehicle Automation)
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