Article
Green & Sustainable Science & Technology
Hrvoje Vdovic, Jurica Babic, Vedran Podobnik
Summary: The transportation sector significantly contributes to greenhouse gas emissions, and with the help of technology and data science, we can understand driving patterns that impact eco-efficiency. This paper proposes a framework for collecting and enriching automotive data to support interdisciplinary studies in environmental sustainability, automotive engineering, behavioural science, telecommunications, and transportation science.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Physics, Multidisciplinary
Rene C. Batac, Michelle T. Cirunay
Summary: This article investigates the least accessible peripheral nodes in road networks, finding that paths between peripheral nodes are usually sinuous. Shorter paths are more likely to have a wide range of sinuosity values, while longer paths tend to be straighter. The article proposes a categorization method based on topological and spatial properties to determine the most inaccessible locations in the network. Such studies are important for managing and improving city transportation networks.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Environmental Sciences
Yang Gu, Bingfeng Si, Bushi Liu
Summary: This research focuses on road detection, integrating shallow machine-learning models and a hierarchical multifeature road image segmentation integration framework. By addressing key issues in feature processing and information extraction, the proposed model effectively improves segmentation accuracy and learning capabilities, showing potential for application in fields such as intelligent transportation and assisted driving.
Article
Computer Science, Interdisciplinary Applications
Rodrigo Silva-Lopez, Jack W. Baker, Alan Poulos
Summary: This study develops a neural network surrogate model to estimate the impact of bridge damage on traffic performance rapidly and accurately. A modified version of LIME is proposed as a strategy to minimize earthquakes' impact on the system. Testing on the San Francisco Bay Area road network shows that the neural network accurately predicts system performance with significantly reduced computation time, allowing decision-makers to evaluate the impact of retrofitting bridges quickly. Moreover, the proposed LIME-TI metric outperforms other indicators in improving network performance.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
(2022)
Article
Economics
Can Gokalp, Priyadarshan N. Patil, Stephen D. Boyles
Summary: The study focuses on identifying the repair sequence of road networks post natural disasters to minimize total travel time. A bidirectional search heuristic with customized strategies performed well on large-scale networks.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Environmental Sciences
Jose Angel Aranda, Carles Beneyto, Marti Sanchez-Juny, Ernest Blade
Summary: This document introduces a method based on hydraulic numerical simulation and the assessment of grate inlet efficiency using the Iber model, suitable for application according to the regulations of different countries. By controlling the hydraulic behavior of each grate inlet, sensitivity analyses of drainage performance can be conducted.
Article
Engineering, Civil
Muhammad Sajjad, Muhammad Irfan, Khan Muhammad, Javier Del Ser, Javier Sanchez-Medina, Sergey Andreev, Weiping Ding, Jong Weon Lee
Summary: The paper introduces a model car using monocular vision and scalar sensor for autonomous driving, equipped with a lightweight deep learning model. The use of economical hardware, such as Raspberry Pi, is investigated for deploying deep learning models, proposing an efficient and cost-effective approach. This designed system serves as a platform for developing economical technologies for autonomous vehicles in current intelligent transportation systems.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Guojiang Shen, Difeng Zhu, Jingjing Chen, Xiangjie Kong
Summary: With the development of intelligent transportation systems, clustering methods have gained significant attention for traffic pattern recognition in road networks. However, the complex relationships among different segments in road networks have been overlooked. To address this issue, this study proposes a clustering method for motif-based attributed road networks and demonstrates its superiority through experiments.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Environmental Sciences
Shi Qiu, Minzhe Fang, Qiang Yu, Teng Niu, Hongjun Liu, Fei Wang, Chenglong Xu, Mingsi Ai, Jieyu Zhang
Summary: By applying complex network theory and graph theory, we constructed a time-series Chinese forest ecological spatial network and studied the nature and carbon sequestration capacity of forest ecosystems. The results showed that while ecological restoration projects in western China had certain effects, the stability and carbon sequestration capacity of forest ecosystems were decreasing. Through correlation analysis, we found significant positive correlations between carbon sequestration capacity and closeness centrality, harmonic closeness centrality, clustering, and eigen centrality, and a significant negative correlation with betweeness centrality. Based on the Principal Components Analysis, we suggested strategies for enhancing plant carbon sequestration capacity.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Engineering, Electrical & Electronic
Halit Bugra Tulay, Can Emre Koksal
Summary: This paper introduces a traffic monitoring approach that utilizes machine learning techniques to process physical layer samples in vehicular communications. The feasibility of the approach is verified through extensive simulations and real-world experiments. The results show accurate predictions of service levels and estimation of vehicle numbers with low errors, indicating that the approach can be deployed alongside existing monitoring systems without additional infrastructure investment.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Correction
Engineering, Civil
Tao Jia, Penggao Yan
Summary: Tao Jia and Penggao Yan made equal contributions to this work.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Chemistry, Physical
Rajesh Haldhar, Dwarika Prasad, Indra Bahadur, Omar Dagdag, Savas Kaya, Dakeshwar Kumar Verma, Seong-Cheol Kim
Summary: The study demonstrated that the extract of S. surattense has a good inhibitory effect on the corrosion of low carbon steel, forming a protective film to reduce the degree of metal degradation. This protective coat was confirmed by SEM and AFM, while the molecular adhesion of the inhibitor was verified by UV-Vis spectroscopy.
JOURNAL OF MOLECULAR LIQUIDS
(2021)
Article
Computer Science, Artificial Intelligence
Jicheng Chen, Siyou Tao, Siyu Teng, Yuanyuan Chen, Hui Zhang, Fei-Yue Wang
Summary: The Paris Agreement of 2016 established global standards for energy conservation and emission reduction, aiming to achieve carbon neutrality by 2050. However, conflicts between environmental protection, economic development, and social fairness hinder the development of sustainable transportation systems. The automotive industry expects widespread application of autonomous driving technology by 2050, which can provide a new solution to improve sustainability. Additionally, autonomous vehicles can enhance mobility for people with disabilities and seniors, as well as reduce transportation costs for the impoverished, thus improving transportation fairness in society. This letter summarizes the impact of autonomous driving technology on sustainable transportation systems from the perspectives of social fairness and economic responsibility, presenting the third part of the Distributed/Decentralized Hybrid Workshop on Sustainability for Transportation and Logistics (DHW-STL).
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
Article
Physics, Multidisciplinary
Anderson Andrei De Bona, Marcelo de Oliveira Rosa, Keiko Veronica Ono Fonseca, Ricardo Luders
Summary: This paper introduces a method to simplify public transportation networks and applies it to multiple real-world PTNs, revealing the effectiveness of the approach and the network characteristics it produces.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Jicheng Chen, Yongkang Zhang, Siyu Teng, Yuanyuan Chen, Hui Zhang, Fei-Yue Wang
Summary: Reducing vehicle exhaust pollution and energy consumption is crucial for improving the sustainability of social development. However, existing methods mainly focus on vehicle control, neglecting the overall traffic environment. This letter proposes energy-efficient and regenerative energy recovery schemes for sustainable intelligent transportation system using the ACP framework, aiming to enhance the sustainability of transportation system from an energy-efficient perspective.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
Article
Environmental Sciences
Stavros Sakellariou, Marc-Andre Parisien, Mike Flannigan, Xianli Wang, Bill de Groot, Stergios Tampekis, Fani Samara, Athanasios Sfougaris, Olga Christopoulou
SCIENCE OF THE TOTAL ENVIRONMENT
(2020)
Article
Chemistry, Analytical
Stavros Sakellariou, Pedro Cabral, Mario Caetano, Filiberto Pla, Marco Painho, Olga Christopoulou, Athanassios Sfougaris, Nicolas Dalezios, Christos Vasilakos
Article
Environmental Sciences
Apostolos Kantartzis, Chrisovalantis Malesios, Anastasia Stergiadou, Nikolas Theofanous, Stergios Tampekis, Garyfallos Arabatzis
Summary: Forest operations engineering is essential for managing forested areas and crucial for the development of mountainous economies. A decision-making web-tool can optimize forest operations and provide information for maintenance and damage prevention.
Review
Environmental Sciences
Stavros Sakellariou, Athanassios Sfougaris, Olga Christopoulou
Summary: Wildfires of high severity have significant impacts on natural and human environments, requiring specific strategies and techniques for mitigation. Geoinformatics-based techniques play a crucial role in integrated fire analysis, focusing on fire exposure, effects on resources, wildfire prevention and suppression, and monitoring of land use changes. Novel machine learning algorithms and technologies such as drones are expected to enhance the accuracy and efficiency of fire risk assessment and detection.
POLISH JOURNAL OF ENVIRONMENTAL STUDIES
(2021)
Article
Geosciences, Multidisciplinary
Stavros Sakellariou, Athanassios Sfougaris, Olga Christopoulou, Stergios Tampekis
Summary: This study evaluates the wildfire risk of a fire-prone region in Greece by simulating burn probability and fire intensity, with a focus on the predicted loss to resources such as electricity networks, mixed forests, residential buildings, and assets. The results show that resources at high risk are located near dense flammable material, leading to increased fire intensity and burn probability.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2022)
Article
Geosciences, Multidisciplinary
Stavros Sakellariou, George Sfoungaris, Olga Christopoulou
Summary: This study aims to optimize the spatial distribution of fire resources in the Chalkidiki Prefecture of northern Greece by considering geographical features and optimization techniques. The integration of geographical features through the Analytical Hierarchy Process and terrain analysis helps determine the most suitable locations for watchtowers. The results provide four differentiated location options based on forest coverage and the number of watchtowers.
INTERNATIONAL JOURNAL OF DISASTER RISK SCIENCE
(2022)
Article
Geosciences, Multidisciplinary
Stavros Sakellariou, Athanassios Sfougaris, Olga Christopoulou, Stergios Tampekis
Summary: Wildfires are increasing in frequency and severity worldwide due to climate change. This study focuses on developing specific territorial measures to enhance spatial resilience to wildfires in the fire-prone region of Chalkidiki Prefecture in northern Greece. The measures aim to improve resistance to wildfires and adapt strategies to wildfire management based on an estimation of burn probability, including anthropogenic factors.
INTERNATIONAL JOURNAL OF DISASTER RISK SCIENCE
(2023)
Article
Agriculture, Multidisciplinary
Stavros Sakellariou, Athanassios Sfougaris, Olga Christopoulou, Nicolas Dalezios, Fani Samara
Summary: This study investigates the land use changes in a highly touristic region, identifying forest to cropland transformation and mild urban expansion as the primary changes.
INTERNATIONAL JOURNAL OF SUSTAINABLE AGRICULTURAL MANAGEMENT AND INFORMATICS
(2021)
Review
Geosciences, Multidisciplinary
Panagiotis T. Nastos, Nicolas R. Dalezios, Ioannis N. Faraslis, Kostas Mitrakopoulos, Anna Blanta, Marios Spiliotopoulos, Stavros Sakellariou, Pantelis Sidiropoulos, Ana M. Tarquis
Summary: Risk assessment involves risk identification, estimation, and evaluation, but lacks feedback on all risk assessment activities, hindering the reduction of environmental hazards. It requires building a database of historical hazard information and effects, considering social consequences and cost-benefit analysis.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
(2021)
Article
Water Resources
Pantelis Sidiropoulos, Nicolas R. Dalezios, Athanasios Loukas, Nikitas Mylopoulos, Marios Spiliotopoulos, Ioannis N. Faraslis, Nikos Alpanakis, Stavros Sakellariou
Summary: This paper presents a methodological procedure for quantitatively classifying desertification severity over a watershed with degraded groundwater resources, utilizing assessments of drought, erosion potential, groundwater levels, and water quality components. The combination of these factors leads to the final mapping of desertification severity classification.
Article
Environmental Sciences
M. Papageorgiou, E. Beriatos, O. Christopoulou, M-N Duquenne, D. Kallioras, S. Sakellariou, Th Kostopoulou, A. Sfougaris, E. Mente, I Karapanagiotidis, S. S. Kyvelou, E. Tzannatos, K. Kanellopoulou, A. Papachatzi
EURO-MEDITERRANEAN JOURNAL FOR ENVIRONMENTAL INTEGRATION
(2020)
Article
Environmental Studies
Stavros Sakellariou, Fani Samara, Stergios Tampekis, Athanasios Sfougaris, Olga Christopoulou
ENVIRONMENTAL HAZARDS-HUMAN AND POLICY DIMENSIONS
(2020)