Search Results (140)

Micromobility is a current and growing integrated transport mode that has its own regulations and requirements for riding. In this context, bicycle usage has been regulated years before. However, the coexistence with new micromobility vehicles, such as e-scooters, has generated the necessity of the development of additional regulatory frameworks. Administrators and technicians have been working for the last 7 years on this aspect. However, a proper evaluation from the user perspective has not been carried out. Thus, there is a need to identify whether micromobility users are aware of the regulations that they must comply with. This research has analyzed the users’ knowledge through a survey, a transport-typical data collection method, but used implicitly as an evaluation, where a score was obtained per user. As a result, the average score obtained was 4.5, reflecting an insufficient qualification. Additionally, statistically significant differences were found between the average score obtained between cyclists and personal mobility vehicle (PMV) users, as well as mean differences between age, micromobility vehicle, ownership, and holding a driver’s license. In conclusion, a new gap has been found in relation to micromobility users’ behavior that has to be addressed. Full article

This research investigates the core competency indicators required for battery electric vehicle (BEV) sales personnel to effectively contribute to the growth of the BEV industry and the transition toward sustainable mobility. As global efforts to reduce carbon emissions intensify, this study identifies the necessary competencies to equip BEV sales teams in navigating the complexities of BEV adoption. This study employs a structured Delphi methodology, gathering insights from a panel of 15 industry professionals, to define and validate key competency dimensions. These competencies are categorized into four main dimensions—professional knowledge, professional ability, professional attitude, and personal traits—and further subdivided into 20 sub-dimensions and 58 specific indicators. Essential competencies include technical expertise in BEV technology, communication skills, customer relationship management, sales techniques, and proficiency in after-sales services. The findings emphasize the significant role of continuous learning, work attitude, and the integration of digital tools in driving sales effectiveness and customer trust. Furthermore, the competency framework developed in this study aligns with the United Nations Sustainable Development Goals (SDGs), particularly SDG 9 (industry, innovation, and infrastructure), SDG 11 (sustainable cities and communities), and SDG 4 (quality education). The framework offers practical insights for recruitment, training, and performance evaluation, ensuring that BEV sales personnel are well-prepared to foster the widespread adoption of electric vehicles, thereby contributing to a sustainable and low-carbon future. Full article

Shared autonomous vehicles (SAVs) are emerging as a potential tool for sustainable transportation, yet their impact on travel behavior and environmental outcomes remains uncertain. This review evaluates the sustainability implications of SAV adoption, including its potential to reduce emissions through optimized fleet operations, enhance social equity by improving mobility access, and increase economic efficiency through resource-sharing models. This systematic literature review examines 107 articles from English and Chinese databases, focusing on SAVs’ effects on total travel demand, mode choice, and in-vehicle time use. Findings indicate that SAVs could increase vehicle miles traveled due to unoccupied relocation and new demand from previously underserved demographics, though advanced booking and dispatch systems may mitigate this increase. The study identifies 59 factors influencing SAV adoption, categorized as user-centric, contextual, and psycho-attitudinal. Analysis of in-vehicle time use shows varied activities, from productivity to leisure, with contradictory findings in the value of travel time (VOT) compared to conventional vehicles: while some studies report up to 34% lower VOT for SAVs due to multitasking opportunities, others find up to 29% higher VOT. Privacy and personal space emerge as important factors, with users showing a high willingness to pay to avoid additional passengers. The review highlights underexplored variables and methodological limitations in current research, including psychological influences and mode substitution dynamics. These insights inform policymakers and urban planners on how to integrate SAVs into sustainable transportation systems by mitigating their environmental impact, promoting equitable access, and ensuring alignment with smart urban planning strategies. Full article

The transition towards a sustainable mobility model encourages an increase in the use of soft modes of transport, and thus an increase in the number of vulnerable road users, especially in urban areas. In Spain, this group of users, comprising pedestrians, cyclists, users of personal mobility vehicles and motorcyclists, accounted for 62,258 victims in road accidents in 2023, 46% of the total, with 7258 dead or seriously injured representing 65.6% of the total. Different strategies to protect vulnerable road users, including communication campaigns, are regularly developed to increase safe travel behaviour. In this context, this study analyses the campaigns issued by the Directorate General of Traffic since 1960 aimed at vulnerable road users. Only 28 campaigns met the established inclusion criteria, representing 23.5% of the total. Thus, the period 2011–2024 has seen the lowest prevalence of this type of campaign, coinciding with a context characterised by the emergence of new forms of micro-mobility that are more sustainable but also more exposed to risks. Due to this complex environment, it is recommended to increase the prevalence of campaigns targeted at vulnerable users and to maximise their effectiveness using emerging technologies such as artificial intelligence and big data, and delivered through a combination of traditional and digital media. Full article

Accidents involving electric wheelchairs are a growing concern, with users frequently encountering obstacles that lead to collisions, tipping, or loss of balance. These incidents underscore the need for advanced safety technologies tailored to electric wheelchair users. This research addresses this need by developing a driving assistance system to prevent accidents and enhance user safety. The system incorporates ultrasonic sensors and a front-facing camera to detect obstacles and provide real-time warnings. The proposed system operates independently of stable server communication and employs embedded hardware for fast object detection and environmental recognition, ensuring immediate guidance in various scenarios. In this research, we utilized the existing yolov8 model as is. But we attempted to improve performance by hardware acceleration of convolutional neural networks, supporting various layers such as convolution, deconvolution, pooling, batch normalization, and others. Thus, the YOLO model was accelerated during inference on the specialized hardware in our experiments. Performance was evaluated in diverse environments to assess its usability. Results demonstrated high accuracy in detecting obstacles and providing timely warnings. Leveraging hardware acceleration for YOLOv8 delivers faster, scalable, and robust object detection, making it a great platform for enhancing driving safety on edge and embedded devices. These findings provide a strong foundation for future advancements in safety assistance systems for electric wheelchairs and other mobility devices. Future research will focus on enhancing system performance and integrating additional features to create a safer environment for electric wheelchair users. Full article

This paper investigates the potential of a magnetic gear wireless power transfer (WPT) system for electric vehicle (EV) charging, with the advantages of low-frequency operation, low foreign object interference, low electromagnetic emissions, and high misalignment tolerance. The study explores the novel impact of Halbach arrays that enhance the flux density in desirable locations while decreasing the flux in undesirable locations, which provides the benefit of decreased foreign object attraction. The initial prototype results demonstrate that the Halbach system can transmit approximately 34.65 W with a transfer efficiency of 64% across a gap of 104 mm. The Halbach system is experimentally compared to a conventional magnet arrangement, which achieved a maximum power transfer of 88 W over 104 mm. The Halbach system is applied to a personal mobility EV to enable wireless charging at low frequency. The axial design of this WPT system has the unique benefit of a 360° radial coupling angle that maintains constant, near-maximum levels of power transfer and efficiency. This full circle coupling angle allows the personal EV to park in any direct vicinity of the charger and achieve the same level of charging given a certain distance. This study delivers important contributions to advancing a low-frequency wireless EV charging technology based on magnetic gears, that sets the stage for future innovations focused on optimizing efficiency, increasing safety, and simplifying the charging process. Full article

New healthcare management strategies aim to reduce in-person visits and patient hospitalization while ensuring patient safety. These strategies optimize resources, alleviate pressure on healthcare services, and decrease travel and mobility within healthcare environments. This research analyzes the environmental impact and sustainability associated with transportation and mobility in traditional hospital-based healthcare services, which have been relocated to bring healthcare closer to patients. This retrospective study utilizes data from two hospital centers spanning the years 2021 to 2023. The objective is to highlight the environmental benefits and sustainability of providing healthcare in the patient’s environment. The methodology employs life cycle analysis to compare three scenarios: traditional healthcare in hospitals, healthcare provided at the patient’s location through home hospitalization and medical consultations at nearby health centers, and healthcare professionals’ travel using electric vehicles. The results demonstrate that healthcare professionals traveling to the patient’s home or nearby health centers reduce environmental impact across all analyzed impact categories. Promoting home hospitalization, specialized consultations at local health centers, and primary care can effectively reduce unnecessary patient travel and minimize environmental impact, enhancing sustainability. Health policies should prioritize actions to reduce hospital visits, emphasizing prevention over disease treatment. Such practices would not only benefit patients but further promote sustainability and environmental protection. Full article

There are high expectations for autonomous personal mobility vehicles (PMVs) to support the mobility of older people. Autonomous navigation systems are being developed to assist mobility in public areas with mixed pedestrian traffic, such as airports and shopping malls. For autonomous navigation of PMVs, achieving both comfort and efficiency, even in crowded environments, is important. In this study, we focused on the characteristic of passenger tolerance, in which a passenger’s discomfort is relatively small concerning an approaching pedestrian. The objective was to propose an efficient autonomous navigation method without increasing passenger discomfort, considering the characteristics of passenger tolerance. First, the passenger tolerance characteristics were clarified through data analysis of a previous study’s dataset and a newly collected dataset. Next, a path-planning method considering the characteristics was proposed, and the proposed method was evaluated by numerical simulations. The evaluation results showed that the proposed method has a potential to achieve efficient autonomous navigation in crowded environments. Full article

Over the past few years, our traditional ground-based transportation system has encountered various challenges, including overuse, traffic congestion, growing urban populations, high infrastructure costs, and disorganization. Unmanned aerial vehicles, commonly referred to as drones, have significantly impacted aerial communication in both the academic and industrial sectors. Therefore, researchers and scientists from the aviation and automotive industries have collaborated to create an innovative air transport system that solves traditional transport problems. In the coming years, urban air mobility (UAM) is expected to become an emerging air transportation system that enables on-demand air travel. UAM is also anticipated to offer more environmentally friendly, cost-effective, and faster modes of transportation than ground-based alternatives. Owing to the unique characteristics of personal air vehicles, ensuring reliable communication and maintaining proper safety and security, air traffic management, collision detection, path planning, and highly accurate localization and navigation have become increasingly complex. This article provides an extensive literature review of recent technologies to address the challenges UAM faces. First, we present UAM communication requirements in terms of coverage, data rate, latency, spectrum efficiency, networking, and computing capabilities. Subsequently, we identify the potential key technological enablers to meet these requirements and overcome their challenges. Finally, we discuss open research issues, challenges, and future research directions for UAM deployment. Full article

There is growing international interest in assessing population exposure to radiofrequency electromagnetic fields, especially those generated by mobile-phone base stations. The work presented here is an experimental study in which we assess exposure to radiofrequency electromagnetic fields in a university environment, where there is a site with mobile-phone antennas and where a large number of people live on a daily basis. The data were collected with a personal exposure meter in two samplings, one walking at ground level and the other using an aerial vehicle at a height higher than the buildings. The geo-referenced electric-field data were subjected to a process in which a theoretical model was adjusted to the experimental variograms, and heat maps were obtained using kriging interpolation. The research carried out is of great relevance, since it provides detailed measurements of the electromagnetic radiation levels both at ground level and at significant heights, using innovative methodologies such as the use of drones. Furthermore, the results obtained allow for contextualizing the exposures in relation to international safety limits, highlighting the importance of rigorous monitoring in everyday environments. Full article

In the pursuit of sustainable mobility and the decarbonization of transport systems, public authorities are increasingly scrutinizing the impact of travel speed on emissions within both low-speed and high-speed environments. This study critically examines the evidence concerning emission impacts associated with speed limit changes in different traffic environments by conducting a systematic review of the literature in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 25 studies that met the eligibility criteria were assessed. The results reveal mixed evidence for reducing emissions through speed limit reductions in low-speed areas. However, emerging evidence suggests that reduced urban speeds may abate emissions through enhanced traffic flow and a shift in modal preferences away from personal vehicle use. Additionally, in urban areas, minor observed emission reduction per vehicle can add up to large overall reductions due to the high number of vehicles. In high-speed contexts, the evidence is much clearer, showing that reduced speed limits correlate with significant reductions in NOx, CO₂, and particulate matter emissions. The extent of these reductions is highly variable and contingent upon the specific speed limits or limit reductions, the local context, the vehicle type, and the baseline types and levels of pollutants. Notably, there is a lack of research on the effects of speed on emissions, especially in low- and middle-income countries (LMICs), highlighting a critical area for future investigation. The findings of this study underscore the potential environmental benefits of speed management policies and advocate for the promotion of smoother and less aggressive driving behavior to mitigate emissions and enhance sustainable mobility in both low-speed and high-speed settings. Full article

Transportation Network Companies (TNCs) play a prominent role in mobility within cities across the globe. However, their activity has impacts on vehicle miles traveled (VMT) and greenhouse gas (GHG) emissions. This study quantifies the change in personal vehicle ownership and total miles driven by TNC drivers in three metropolitan areas: San Francisco, CA; Los Angeles, CA; and Washington, D.C. The data sources for this analysis comprise two surveys, one for TNC passengers (N = 8630) and one for TNC drivers (N = 5034), in addition to data provided by the TNC operators Uber and Lyft. The passenger survey was deployed within the three metropolitan areas in July and August 2016, while the driver survey was deployed from October to November 2016. The TNC operator data corresponded with these time frames and informed the distance driven by vehicles, passenger frequency of use, and fleet level fuel economies. The data from these sources were analyzed to estimate the impact of TNCs on travel behavior, personal vehicle ownership and associated VMT changes, as well as the VMT of TNCs, including app-off driving. These impacts were scaled to the population level and collectively evaluated to determine the net impacts of TNCs on VMT and GHG emissions using fuel economy factors. The results showed that the presence of TNCs led to a net increase of 234 and 242 miles per passenger per year, respectively, in Los Angeles and San Francisco, while yielding a net decrease of 83 miles per passenger per year in Washington, D.C. A sensitivity analysis evaluating net VMT change resulting from vehicle activity and key behavioral impacts revealed the conditions under which TNCs can contribute to transportation sustainability goals. Full article

Shared mobility (SM) services are transitioning from the introduction stage to the growth stage, driven by the growth of the sharing economy, the promotion of smart cities, the diverse personal transportation modes, and the development of autonomous driving technologies. SM services, such as car sharing, car-hailing, shared bikes, and e-scooters, have emerged as solutions to address issues related to carbon neutrality and traffic congestion in densely populated areas. The purpose of this study is to investigate potential disparities in user perception and satisfaction among groups with or without driving experience when using SM services—through hypothesis testing using the two-proportion Z-test. Subsequently, a satisfaction analysis is conducted. This research creates foundational data for future SM services. The survey targeted 1041 residents living in Seoul, Gyeonggi Province, and Incheon, and was conducted over two weeks in March 2020. This study aims to derive associations between two groups using SM—those with and without driving experience. The results indicate that car sharing and bike sharing showed significant differences in user patterns based on driving experience, whereas e-scooters and car-hailing did not exhibit significant differences. This contradicts the assumption that people without a driver’s license would use SM more frequently. Moreover, the results of each SM’s analysis show different usage patterns and satisfaction between driver’s license holders and nonholders. This study will serve as foundational data for researching strategies to reduce personal car ownership through the promotion of public transportation and SM services. Furthermore, it can be a basis for suggesting policy recommendations to facilitate future mobility systems. Full article

The growing demand for personal mobility is leading to an increase in vehicle use, which is in turn contributing to higher carbon emissions. It is widely acknowledged that emission-free electric vehicles (EVs) will play a pivotal role in the decarbonization process, particularly in the decarbonization of transport systems. The objective of this paper was to present the trends in demand for electric vehicles (EVs) in Poland, together with the identification of market shocks and an assessment of the programs supporting electromobility. The number of imported and domestically purchased new and used electric vehicle (BEV) registrations was analyzed using the TRAMO-SEATS and ARIMA-X-12 seasonal adjustment methods. The rise in sales of electric vehicles in Poland was driven by the government’s electromobility support programs and alterations to tax legislation, with no discernible seasonal impact. The number of registrations in Poland increased significantly, exhibiting an upward trajectory. However, this growth is constrained by the inadequate number of charging stations, which are primarily powered by electricity derived from coal. Consequently, while the development of electromobility in Poland is evident, the decarbonization process remains a challenge. Full article

This systematic review paper examines the current integration of artificial intelligence into energy management systems for electric vehicles. Using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology, 46 highly relevant articles were systematically identified from extensive literature research. Recent advancements in artificial intelligence, including machine learning, deep learning, and genetic algorithms, have been analyzed for their impact on improving electric vehicle performance, energy efficiency, and range. This study highlights significant advancements in energy management optimization, route planning, energy demand forecasting, and real-time adaptation to driving conditions through advanced control algorithms. Additionally, this paper explores artificial intelligence’s role in diagnosing faults, predictive maintenance of electric propulsion systems and batteries, and personalized driving experiences based on driver preferences and environmental factors. Furthermore, the integration of artificial intelligence into addressing security and cybersecurity threats in electric vehicles’ energy management systems is discussed. The findings underscore artificial intelligence’s potential to foster innovation and efficiency in sustainable mobility, emphasizing the need for further research to overcome current challenges and optimize practical applications. Full article