Article
Transportation Science & Technology
Gina Blazanin, Aupal Mondal, Katherine E. Asmussen, Chandra R. Bhat
Summary: Shared micromobility modes have become increasingly popular in urban transportation, and it is important to understand how individuals respond and who the likely users are. This study analyzes the first-use and use frequency of Escooter sharing systems (ESS) and Bike sharing systems (BSS) using psycho-social constructs, built environment attributes, and individual-level demographics. The results emphasize the importance of considering psycho-social attitudes and cognitive antecedents in understanding the adoption and use of these micromobility modes.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Ergonomics
Qingyu Ma, Hong Yang, Alan Mayhue, Yunlong Sun, Zhitong Huang, Yifang Ma
Summary: The emergence of shared electric scooter systems has introduced a new micro-mobility mode in urban areas worldwide, but has also raised safety concerns. Research shows that the interactions between e-scooter riding and environmental settings play a significant role in safety performance.
ACCIDENT ANALYSIS AND PREVENTION
(2021)
Article
Green & Sustainable Science & Technology
Nora Schelte, Semih Severengiz, Jaron Schuenemann, Sebastian Finke, Oskar Bauer, Matthias Metzen
Summary: Light electric vehicles, such as electric moped scooters, are considered a space efficient and eco-friendly alternative for urban mobility, but there is limited research on their environmental impact throughout the lifecycle. A study in Germany showed that e-moped sharing services have a similar environmental impact on global warming potential in terms of passenger kilometers as public transport, especially when long product lifetimes and efficient operation logistics are realized.
Article
Transportation
Hyunsoo Yun, Eui-Jin Kim, Seung Woo Ham, Dong-Kyu Kim
Summary: This article proposes a solution to the imbalance problem in e-scooter sharing services using deep reinforcement learning. By offering price incentives and alternative rental locations, the proposed algorithm efficiently reduces unmet demands and benefits both users and service providers.
JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Energy & Fuels
Paula Brezovec, Nina Hampl
Summary: Current trends suggest a decrease in the popularity of privately-owned cars due to the diffusion of mobility services like MaaS bundles. A study in Austria investigated consumer preferences for MaaS packages in suburban areas, showing that package price is the most important attribute impacting purchase intention. Participants in the study showed a preference for MaaS packages that included e-car sharing.
Article
Environmental Studies
Hyukseong Lee, Kwangho Baek, Jin-Hyuk Chung, Jinhee Kim
Summary: This study found that the intention to use e-scooter sharing service is affected by various factors, leading to two distinct groups: one preferring for commuting, and the other for last-mile trips. The first group tends to be younger, have higher income, and be less satisfied with current public transportation, while the second group shows opposite characteristics.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2021)
Article
Green & Sustainable Science & Technology
Theodora Sorkou, Panagiotis G. Tzouras, Katerina Koliou, Lambros Mitropoulos, Christos Karolemeas, Konstantinos Kepaptsoglou
Summary: This study investigates the willingness to use e-scooter sharing services, taking into account the road environment. It finds that the existence of roads with good pavement conditions and wide sidewalks significantly increases the willingness of respondents to use e-scooter sharing services. Surprisingly, pedestrianized zones and bike lanes have relatively little contribution.
Article
Economics
Jinghai Huo, Hongtai Yang, Chaojing Li, Rong Zheng, Linchuan Yang, Yi Wen
Summary: This study examined the usage characteristics and effects of the built environment on electric scooter sharing systems in five cities in the U.S. The temporal distributions of e-scooter ridership were similar across cities, with higher ridership in universities and urban centers. Results showed positive correlations between ESS trips and density-related factors, and negative correlations with population age and distance to city center.
JOURNAL OF TRANSPORT GEOGRAPHY
(2021)
Article
Green & Sustainable Science & Technology
Fei-Hui Huang
Summary: The study explores the adoption of scooter-sharing services by travelers using the unified theory of acceptance and use of technology, attitude, and user experience. Results show that habit, social influence, and environmental protections positively influence users' intentions towards shared scooters, while performance and effort expectancy have a negative impact on intention to use. Attitudes and UX do not directly affect intention to use, suggesting the need for design improvements and implications for service providers in the shared micro-mobility sector.
Article
Environmental Studies
Aoyong Li, Pengxiang Zhao, Xintao Liu, Ali Mansourian, Kay W. Axhausen, Xiaobo Qu
Summary: This research conducts a comparative study on e-scooter sharing mobility in 30 European cities, revealing the similarities and differences, as well as issues related to utilization efficiency and wasted electricity during idle time. The findings have practical implications for optimizing e-scooter sharing mobility services.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2022)
Article
Ergonomics
Narelle Haworth, Amy Schramm, Divera Twisk
Summary: The study found that illegal behaviors among shared e-scooter riders in inner-city Brisbane decreased from February to October 2019, while the usage of private e-scooters increased, suggesting an improvement in e-scooter safety.
ACCIDENT ANALYSIS AND PREVENTION
(2021)
Review
Transportation
Khashayar Kazemzadeh, Frances Sprei
Summary: Although electric scooters are gaining popularity, research on analyzing user experience is lacking. A preliminary framework for developing Level of Service (LOS) for e-scooters is proposed, highlighting the need for evaluation studies and considering the impact of e-scooters on other transportation modes. Future research should focus on the interaction between e-scooters and pedestrians.
TRAVEL BEHAVIOUR AND SOCIETY
(2022)
Article
Environmental Sciences
Mario Echeverria-Su, Esteffany Huamanraime-Maquin, Felix Israel Cabrera, Ian Vazquez-Rowe
Summary: Micro-mobility has increased in urban environments to reduce dependence on private vehicles. Electric micro-mobility alternatives are expected to have reduced environmental impacts, but this depends on the transport mode they replace. Urban areas in developing and emerging economies struggle to implement sustainable mobility programs at a city-wide level.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Economics
Hongtai Yang, Jinghai Huo, Yongxing Bao, Xuan Li, Linchuan Yang, Christopher R. Cherry
Summary: This study analyzes the impact of e-scooter sharing on bike sharing in Chicago, finding that the introduction of e-scooter sharing led to a decrease in overall bike sharing usage, especially among non-members and female members.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2021)
Article
Economics
Hongtai Yang, Rong Zheng, Xuan Li, Jinghai Huo, Linchuan Yang, Tong Zhu
Summary: This study explores the nonlinear and threshold effects of the built environment on ESS ridership in Los Angeles and identifies the most important variables in the built environment. The findings can help planners determine high-demand areas and design effective investment plans to promote micromobility.
JOURNAL OF TRANSPORT GEOGRAPHY
(2022)
Article
Metallurgy & Metallurgical Engineering
Mehdi Safari, Ricardo Alves de Sousa, Jalal Joudaki
Summary: In this study, the bending of mild steel tubes was investigated using a laser beam. The effects of six process parameters on the bending angles were examined. The results showed that increasing laser power, irradiation length, and number of irradiation passes, as well as reducing scanning speed and laser beam diameter, led to higher bending angles.
STEEL RESEARCH INTERNATIONAL
(2023)
Article
Education & Educational Research
Amar Kumar Behera, Ricardo Alves de Sousa, Valentin Oleksik, Jingyan Dong, Daniel Fritzen
Summary: This study captures student perceptions of the effectiveness of remote learning and assessment in two associated engineering disciplines, mechanical and industrial, during the COVID-19 pandemic in a cross-national study. A structured questionnaire was used to analyze student preferences and the results showed a strong preference for face-to-face teaching, especially in laboratory courses. In addition, students preferred remote live lectures over recorded ones. However, concerns were raised about group work and communication during remote learning.
EUROPEAN JOURNAL OF ENGINEERING EDUCATION
(2023)
Article
Materials Science, Multidisciplinary
Mehdi Safari, Seyed Mohammad Miralaa, Ricardo Alves de Sousa
Summary: This work experimentally studies the laser forming process of cylindrical surfaces. The effects of process parameters such as laser power, laser scanning scheme, and distance between irradiation lines on the radius of curvature of the laser-formed cylindrical surfaces are examined. The design of experiment (DOE) method based on the Box-Behnken algorithm is employed for investigations. Results indicate that increasing laser power decreases the radius of curvature of a laser-formed cylindrical surface. Additionally, the radius of curvature of the cylindrical surface increases with increasing scanning speed, while it decreases with increasing distance between irradiation lines.
Article
Materials Science, Multidisciplinary
Jaques Araripe Suris, Charles Chemale Yurgel, Ricardo Alves de Sousa
Summary: The hot forging process improves the mechanical properties of parts compared with casting or machining. Metal flow in forging leads to texture changes known as grain-flow orientation (GFO). This study investigated the influence of GFO on fatigue life using a rotational flexing fatigue test. Experimental results showed that forged samples with GFO in the main deformation direction exhibited higher fatigue life compared to other configurations.
Review
Biology
Gustavo P. Carmo, Jeroen Grigioni, Fabio A. O. Fernandes, Ricardo J. Alves de Sousa
Summary: This article aims to provide readers with a concise description of the main contributions in the field of traumatic brain injuries and neurodegenerative outcomes for women, especially related to chronic traumatic encephalopathy. It also reviews the numerical models created to address these issues and discusses the use (or lack of use) of sex-specific validation experiments. The article highlights the importance of considering sex differences in both direct injuries and the conditions that precede and follow traumatic events.
Article
Computer Science, Interdisciplinary Applications
Gustavo P. Carmo, Mateusz Dymek, Mariusz Ptak, Ricardo J. Alves-de-Sousa, Fabio A. O. Fernandes
Summary: Traumatic brain injuries are a major cause of death and disability worldwide. Finite element head models have been developed to understand the forces and interactions in the human head, offering a cost-effective and ethical alternative to experimental tests. The female finite element head model (FeFEHM) can provide insights into injury mechanisms and neurodegenerative diseases.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2023)
Article
Engineering, Biomedical
Afonso J. C. Silva, Ricardo J. Alves de Sousa, Fabio A. O. Fernandes, Mariusz Ptak, Mateusz Dymek, Marco P. L. Parente
Summary: The aim of this research is to create a finite element model that accurately represents the female cervical spine in order to better understand its mechanics and develop treatments or preventative measures. This study builds upon a previous research where a model was created from CT scans of a 46-year-old female and simulated a functioning spinal unit for validation. The reduced model was validated using experimental data from cadaveric specimens assessing the range of motion of different cervical segments in various movements.
JOURNAL OF THE MECHANICAL BEHAVIOR OF BIOMEDICAL MATERIALS
(2023)
Article
Chemistry, Physical
Maria Kuranska, Mariusz Ptak, Elzbieta Malewska, Aleksander Prociak, Mateusz Barczewski, Mateusz Dymek, Fabio A. O. Fernandes, Ricardo Alves de Sousa, Krzysztof Polaczek, Karolina Studniarz, Katarzyna Uram
Summary: Renewable materials are naturally replenished and can be reused materials, such as bamboo, cork, hemp, and recycled plastic. Using renewable components reduces dependence on petrochemical resources and waste. Adopting these materials in various industries can lead to a more sustainable future and decrease the carbon footprint.
Article
Materials Science, Multidisciplinary
Nijenthan Rajendran, Charles Chemale Yurgel, Wojciech Z. Z. Misiolek, Ricardo Alves de Sousa
Summary: The study focuses on developing a new forging process for a wind turbine pinion shaft, using Deform 3D software for near-net-shape forming. The Finite Element Method is used to create a process model for the existing hot forging process, and new die designs are proposed based on simulation results and compared to the actual process. The new designs show improvements in terms of cavity filling and grain flow orientation.
Article
Ergonomics
Mariusz Ptak, Johannes Wilhelm, Marek Sawicki, Mateusz Dymek, Fabio A. O. Fernandes, Helmuth Kristen, Emma Garatea
Summary: The paper discusses a significant accident type involving children in bicycle seats - the bicycle fall over. This type of accident often occurs at low speeds and even when the bicycle is stationary, usually due to a momentary lack of attention from the accompanying adult. The study emphasizes the potential life-threatening head trauma and highlights the importance of considering neck bending injuries in safety assessments.
JOURNAL OF SAFETY RESEARCH
(2023)
Article
Engineering, Civil
Mariusz Ptak, Mateusz Dymek, Marek Sawicki, Fabio A. O. Fernandes, Maciej Wnuk, Johannes Wilhelm, Monika Ratajczak, Daria Witkowska, Artur Kwiatkowski, Blazej Pozniak, Konrad Kubicki, Marta Tikhomirov, Adam Druszcz, Leszek Chybowski
Summary: An advanced head model of a 28-year-old has been developed, accurately representing the geometry and material properties of the brain and other tissues, as well as simulating pressurized bridging veins and cerebrospinal fluid. The model's credibility is supported by physical material testing and numerical analysis. This model aims to establish a benchmark in finite element head modelling and provide new insights into injury mechanisms.
ARCHIVES OF CIVIL AND MECHANICAL ENGINEERING
(2023)
Article
Crystallography
Fabio A. O. Fernandes, Jose J. M. Goncalves, Antonio B. Pereira
Summary: This study investigates the laser weldability between dissimilar non-ferrous metallic materials and evaluates the quality of welds. The results show that the strength of the welded samples is close to the base material, but there are microporosities and cracks near the heat-affected zone.
Article
Ergonomics
Narelle Haworth
Summary: Close passes by motor vehicles pose threats to the safety and comfort of bicycle riders. Governments in many countries have implemented laws to ensure a minimum distance between vehicles and cyclists during overtaking. This paper discusses the evaluation of a two-year trial in Queensland, Australia, which aimed to understand the circumstances and reasons behind close passes. The study used video observations and experimental studies to gather data and analyze crash causation.
ACCIDENT ANALYSIS AND PREVENTION
(2024)
Article
Ergonomics
Ziluo Xiong, Suren Chen
Summary: Road vehicles are prone to single-vehicle crashes (SVCs) under complex road geometry and bad weather conditions, posing a significant threat to traffic safety and mobility. Researchers have developed a novel multi-fidelity approach that balances simulation accuracy and efficiency for reliable risk assessment of SVCs. By using a high-fidelity transient dynamic vehicle model and a low-fidelity simplified physics-based vehicle model, the proposed approach provides accurate and efficient reliability evaluation of SVCs.
ACCIDENT ANALYSIS AND PREVENTION
(2024)
Article
Ergonomics
Ziqian Zhang, Haojie Li, Gang Ren
Summary: This study introduces a novel encoder-decoder framework that utilizes multi-source data to predict the severity of jaywalking violations. The experimental results show that the proposed model outperforms classical models and the incorporation of background information significantly enhances the model's performance.
ACCIDENT ANALYSIS AND PREVENTION
(2024)
Article
Ergonomics
Zihang Wei, Subasish Das, Yue Wu, Zihao Li, Yunlong Zhang
Summary: In traditional roadway crash studies, cross-sectional modeling methods have limitations when dealing with highly time-varying variables related to weather conditions and speed variation. This study employs the distributed lag model (DLM) and the distributed lag nonlinear model (DLNM) to investigate the lagged impacts of weather and speed variation factors on segment crash risk. The results demonstrate coherent and interpretable lagged impact patterns, emphasizing the need for considering time-series effects in future crash modeling research.
ACCIDENT ANALYSIS AND PREVENTION
(2024)
Article
Ergonomics
Petya Ventsislavova, Thom Baguley, Josceline Antonio, Daniel Byrne
Summary: The use of e-scooters is increasing rapidly, but it comes with potential dangers such as collisions and illegal riding behavior. Research shows that e-scooter riders tend to be younger and more prone to engage in illegal riding behavior compared to non-users. Knowledge of current regulations related to e-scooters is limited, especially in areas like parking, speeding, and designated infrastructure. Targeted interventions and educational campaigns are necessary to improve riders' understanding of regulations and promote safer riding practices.
ACCIDENT ANALYSIS AND PREVENTION
(2024)
Article
Ergonomics
Song Wang, Zhixia Li, Yi Wang, Wenjing Zhao, Tangzhi Liu
Summary: This study quantitatively reveals the reasons behind changes in AV acceptance after experiencing automated driving and objectively validates that safety is the primary factor influencing AV acceptance.
ACCIDENT ANALYSIS AND PREVENTION
(2024)
Article
Ergonomics
Qian Liu, Xuesong Wang, Shikun Liu, Chunjun Yu, Yi Glaser
Summary: Intersections are high-risk locations for autonomous vehicles (AVs). Analyzing the pre-crash scenarios and contributing factors of AV crashes at intersections using the association rule method revealed that rear-end and lane change crashes were the most frequently occurring scenarios for AVs. The main contributing factors of these scenarios were identified, such as the location outside the intersection, traffic signal control, autonomous engaged mode, mixed-use or public land, and weekdays. Inadequate stop and deceleration decisions by the AV's automated driving system (ADS) and insufficient collision avoidance decisions in lane change crashes were important causes of these AV crashes.
ACCIDENT ANALYSIS AND PREVENTION
(2024)
Article
Ergonomics
Tao Wang, Ying-En Ge, Yongjie Wang, Wenqiang Chen
Summary: This paper introduces a method to simulate the propagation patterns of conflict risk on freeways, which can help prevent traffic accidents and improve the deployment of advanced vehicle technologies. By introducing a conflict risk index and a spatio-temporal transformer network, it is possible to effectively simulate the propagation patterns of conflict risk. Experimental results show that the model based on proportion of stopping distance exhibits robust performance, while the model based on deceleration rate more distinctly delineates spatio-temporal conflict risk heterogeneity.
ACCIDENT ANALYSIS AND PREVENTION
(2024)
Article
Ergonomics
Min Deng, Aaron Gluck, Yijin Zhao, Da Li, Carol C. Menassa, Vineet R. Kamat, Julian Brinkley
Summary: This paper analyzes the effects of takeover behaviors on common physiological indicators of drivers, including brain signals, skin conductance level, and heart rate. The results show that performing secondary tasks prior to takeover activities can decrease drivers' engagement, while higher task difficulty and traffic density can increase drivers' mental workload and heart rate. Moreover, a fake takeover alert can also affect drivers' physiological indicators. The paper also discusses the correlation between physiological data, takeover scenarios, and vehicle data, emphasizing the importance of data standardization or normalization for estimating takeover readiness.
ACCIDENT ANALYSIS AND PREVENTION
(2024)
Article
Ergonomics
Dongyu Wu, Yingheng Zhang, Qiaojun Xiang
Summary: Machine learning models, such as random forests, have been widely used in the field of road safety. However, the traditional RF algorithm fails to capture spatial variability. To address this, a modified algorithm called geographically weighted random forest (GWRF) is employed. The results from analyzing London data show that GWRF outperforms RF and GWR, and is not affected by multicollinearity.
ACCIDENT ANALYSIS AND PREVENTION
(2024)
Article
Ergonomics
Tanveer Ahmed, Asif Mahmud, Vikash V. Gayah
Summary: This study uses the propensity score potential outcome framework to investigate the impact of rumble strips on crashes on horizontal curves. The findings suggest that centerline rumble strips reduce sideswipe and head-on crashes but increase run off the road and hit fixed object crashes. Shoulder rumble strips, either alone or in combination with centerline rumble strips, decrease crash frequencies for most types except sideswipe and head-on crashes.
ACCIDENT ANALYSIS AND PREVENTION
(2024)
Article
Ergonomics
Ryan Miller, Timothy Brown, Rose Schmitt, Gary Gaffney, Gary Milavetz
Summary: This study investigated the changes in driving performance following cannabis use, and found that self-reported readiness to drive and previous cannabis use experience can predict some of these changes. However, readiness to drive does not fully explain the observed degradation in performance.
ACCIDENT ANALYSIS AND PREVENTION
(2024)
Article
Ergonomics
Kang Jiang, Yanting Liu, Zhenhua Yu, Zhipeng Huang
Summary: This study investigated the effects of smartwatch usage on children's street-crossing behavior and visual strategies. The results showed that children wearing smartwatches crossed the street more slowly and had a narrower visual search range compared to children without smartwatches. Distraction tasks performed on the smartwatch also affected children's crossing behavior and increased the risk of collision.
ACCIDENT ANALYSIS AND PREVENTION
(2024)
Article
Ergonomics
Yongjie Wang, Yuqi Jia, Wenqiang Chen, Tao Wang, Airen Zhang
Summary: This study explores the safe spaces maintained by pedestrians and e-bicyclists when crossing streets. Using drone footage, the researchers found that e-bicyclists maintain semi-elliptical safe spaces while pedestrians maintain semi-circular safe spaces, with the sizes of these spaces increasing in proportion to relative speeds. The findings bridge an empirical gap in the existing literature and have practical implications for urban planning, traffic management, and the safety of vulnerable road users.
ACCIDENT ANALYSIS AND PREVENTION
(2024)
Review
Ergonomics
Yasir Ali, Fizza Hussain, Md Mazharul Haque
Summary: Accurately modeling crashes and predicting their occurrence and severities are crucial for effective road safety management strategies. This review paper systematically examines machine learning studies on crash modeling, highlighting gaps and future research needs. The review emphasizes the importance of understanding state-of-the-art machine learning-based crash prediction models and leveraging big data to improve our understanding of crash mechanisms.
ACCIDENT ANALYSIS AND PREVENTION
(2024)