Abstract: Designing optimal heritage tourism routes in secondary cities involves complex trade-offs between cultural richness, travel time, carbon emissions, spatial coherence, and group satisfaction. This study addresses the Personalized Group Trip Design Problem (PGTDP) under real-world constraints by proposing DRL–IMVO–GAN—a hybrid multi-objective optimization framework that integrates Deep Reinforcement Learning (DRL) for policy-guided initialization, an Improved Multiverse Optimizer (IMVO) for global search, and a Generative Adversarial Network (GAN) for local refinement and solution diversity. The model operates within a digital twin of Warin Chamrap’s old town, leveraging 92 POIs, congestion heatmaps, and behaviorally clustered tourist profiles. The proposed method was benchmarked against seven state-of-the-art techniques, including PSO + DRL, Genetic Algorithm with Multi-Neighborhood Search (Genetic + MNS), Dual-ACO, ALNS-ASP, and others. Results demonstrate that DRL–IMVO–GAN consistently dominates across key metrics. Under equal-objective weighting, it attained the highest heritage score (74.2), shortest travel time (21.3 minutes), and top satisfaction score (17.5 out of 18), along with the highest hypervolume (0.85) and Pareto Coverage Ratio (0.95). Beyond performance, the framework exhibits strong generalization in zero- and few-shot scenarios, adapting to unseen POIs, modified constraints, and new user profiles without retraining. These findings underscore the method’s robustness, behavioral coherence, and interpretability—positioning it as a scalable, intelligent decision-support tool for sustainable and user-centered cultural tourism planning in secondary cities.

Abstract: Wildlife strikes in aviation are among the most reported safety incidents. As such, strikes have become the fundamental unit of understanding of the risk posed by wildlife. However, with the management of wildlife strike risk shifting to a hazard management philosophy, this literature review considers the contention that current wildlife strike reporting systems are not suited to modern wildlife hazard management techniques. This review sourced academic literature from Web of Science (n=684) and, using bibliometric analysis software, identified relevant papers (n=257). Additional industry material completed the final catalogue (n=542). These papers were reviewed for their treatment and use of wildlife strikes with respect to modern risk and hazard management approaches. This analysis noted three potential challenges with current wildlife strike reporting systems, including the focus on collision events, the potential to introduce other adverse effects and the skewing of risk assessment results. The paper’s analysis was supplemented with a review of international standards and relevant national requirements and concludes that while academics and industry have adopted systemized safety and hazard management concepts and that international guidance material has been keeping pace, international standards, the foundation for many national reporting systems, remains decades behind.

Abstract: This study examines the annual carbon emission differences between privately owned electric vehicles (EVs) and internal combustion engine vehicles (ICEVs) through the development of a usage-phase life cycle assessment (LCA) model, with a focus on the synergistic effects of grid carbon intensity, driving intensity (e.g., annual mileage), and vehicle efficiency. Through scenario analyses and empirical case studies in four Chinese megacities, three key findings emerge: (1) Grid carbon intensity dominates EV emission advantages—EVs retain significant carbon reduction benefits in low-CEG regions even with doubled annual mileage, while high-energy-consuming EVs risk emission reversals in coal-dependent grids under intensive usage. (2) Higher annual mileage among EV owners (1.5–2 times ICEV baselines) accelerates carbon accumulation, particularly eroding per-kilometer emission advantages in fossil-fuel-reliant regions. (3) Vehicle energy efficiency heterogeneity is critical: compact, low-energy EVs (e.g., A0-class sedans/SUVs) maintain advantages across all scenarios, whereas high-energy models (e.g., C-class sedans/SUVs) may exceed ICEV emissions in high-CEG regions. The study proposes a differentiated policy framework emphasizing synergistic optimization of grid decarbonization, vehicle-class-specific management, and user behavior guidance to maximize EVs’ carbon reduction potential. These insights provide scientific foundations for refining EV adoption strategies and achieving sustainable transportation transitions.

Abstract: This study recognizes the significance of young people as future consumers and industry decision-makers by examining their knowledge of and attitudes toward electric vehicles (EVs) in Bangladesh. People's awareness of and attitudes regarding electric cars (EVs) vary, according to preliminary findings from a poll of 102 participants. The study addresses the critical role of young people as future consumers and decision-makers by examining their knowledge and attitudes toward electric vehicles (EVs) in Bangladesh. Despite the global push for sustainability, awareness and acceptance of EVs in Bangladesh remain limited, partly due to a lack of targeted education campaigns. This underscores the need for targeted education campaigns. The study explores the relationship between acceptability and awareness of electric vehicles, identifying key factors influencing young people's perspectives. Beyond its scholarly significance, the research offers insights to industry stakeholders, educators, and legislators that will facilitate the development of tailored strategies to promote teenagers' use of electric vehicles. By encouraging optimistic and knowledgeable attitudes, this research aims to assist Bangladesh's transition to a greener, more sustainable future.

Abstract: The successful integration of autonomous vehicles (AVs) into society hinges on public acceptance, which is closely linked to trust. This study investigates the factors influencing initial trust and specific trust requirements for the acceptance of AVs among Spanish population. A national survey was conducted with 400 participants, selected to represent the demographic diversity of Spain. The survey assessed participants' prior experience with AVs, demographic characteristics, ethical concerns, and trust levels. The findings indicate that individuals with prior direct experience with AVs exhibit higher initial trust levels. Demographic variables such as age, gender, and education significantly influence trust requirements; notably, younger and higher-educated individuals demonstrate lower trust thresholds. Ethical concerns, including data privacy and algorithmic transparency, emerge as significant predictors of trust levels. When contextualized with international studies, these findings highlight unique cultural and regulatory influences on trust in AVs within Spain. These insights are crucial for policymakers and manufacturers aiming to enhance public trust promote the ethical development and public acceptance of AVs to facilitate the widespread adoption of AVs.

Abstract: The Department of Veterans Affairs (VA) transportation system plays an important role in ensuring access to transportation services for Veterans, particularly those in rural or underserved areas. However, concerns remain regarding the effectiveness of collaboration among the various VA transportation stakeholders. Persistent transportation challenges hinder Veterans' access to essential healthcare services and resources. Electric, Automated Ride-Sharing Services (ARSS) offer a promising opportunity to enhance transportation access, however their current limitations and the perspectives of VA transportation personnel must be considered. This study explored the current perspectives of the VA transportation system and assessed ARSS as an innovative and sustainable alternative through interviews with eight VA transportation stakeholders representing seven transportation sectors. Findings revealed the VA’s strengths, including personalized service, flexible accommodations, and collaborative care models, but also identified challenges, including limited funding, staff shortages, volunteer constraints, and restrictive eligibility criteria. The introduction of ARSS was identified as an opportunity to alleviate some of these constraints by reallocating human resources and improving access to essential services, although concerns remain regarding ARSS’s ability to accommodate Veterans with disabilities and address rural route complexities. Effective communication strategies and streamlined coordination were key recommendations for improving service delivery and expanding transportation access for Veterans.

Abstract: This paper explores the potential of e-cargo bikes as a personal transport mode in the UK, reporting on a series of surveys and trials. Our survey of 2,000 English adults indicated that while only 3% of adults were using an e-cargo bike at least once a month, 11% of non-users saw themselves as someone who might ride an e-cargo bike, rising to 20% in places with a strong cycling culture. Compared to non-users, e-cargo-bike users had similar levels of household car ownership, but were less likely to be frequent car users and more likely to undertake recommended amounts of physical activity. Trials were run in suburban areas of 3 UK cities. 49 households were loaned an e-cargo bike for a month in summer 2023, and 11 of these households borrowed bikes again the following winter. Summer trial households cycled approximately 8,000km (38-42km per household per week) with over 50% of the distance travelled replacing car use. Advantages of use included mental and physical health benefits and being able to cycle ‘as a family’. Issues identified as requiring policy attention included purchase costs, theft, negative perceptions of battery safety and lack of infrastructure. By Autumn 2024, 10 trial households had bought e-cargo bikes. The study demonstrated that for some people, at certain life stages, e-cargo bikes represent a realistic and desirable form of mobility, with the potential to reduce car use and associated emissions. E-cargo bikes can thus play in an important role in the transition to more sustainable mobility.

Abstract: Cycling is recognized as a key strategy for the transition to sustainable urban mobility and for improving public health, yet it remains a marginal mode of transport in many cities. In an effort to promote cycling, some places offer financial incentives to encourage people to use bicycles as a mode of transportation. However, these policies raise social justice concerns regarding who benefits from such policies and who does not. This paper explores the operationalization of a policy designed to promote cycling through finan- cial incentives, specifically by compensating individuals for cycled kilometers with public transport credits. The study incorporates a social justice-oriented design and emphasizes the importance of diversifying cycling demographics, integrating cycling with public transport, and leveraging data to support fair urban mobility. Grounded in transport, mobility, and data justice literature, we introduce policy design guidelines for social-justice-informed ‘pay for cycling’ financial incentives, bridging social science and data science. These guidelines are illustrated through a pilot project for São Paulo’s “Bike SP” program, which includes app development, participant selection, and data collection. The pilot project reveals demographic and socioeconomic inequalities in cycling within São Paulo. It also provides a model for similar policies in other cities. The findings highlight the need for inclusive participant selection criteria and the potential of financial incentive policies to generate valuable cycling data, foster a cycling community, and integrate with broader mobility and public health policies. We argue that such policies should be part of a comprehensive strategy for creating an inclusive mobility environment.

Abstract:

The implementation of carbon tax in the transportation sector aims to reduce carbon emissions and encourage the transition to sustainable mobility amidst increasing urbanization. In determining an effective carbon tax rate, economic, environmental, and social factors need to be considered, including the social cost of carbon, emission reduction target, economic impact, revenue for environmental programs, and social justice and equity. The social cost of carbon provides an estimate of the economic and social damage impacts of carbon emissions, so that the tax rate reflects comparable costs. The emission reduction target is consistent with national commitments and focuses on mitigating climate change in urban areas. The economic impact considers the effect of the carbon tax on energy prices, the competitiveness of the transportation sector, and the cost of living in Jakarta. Carbon tax revenues can be allocated to city environmental programs, such as the development of green transportation infrastructure and the integration of renewable energy. The social equity aspect ensures that this policy does not burden vulnerable groups and supports inclusiveness in access to transportation. In Jakarta, a carbon tax policy can facilitate the use of low-emission vehicles, accelerate the transition to public transportation and electric vehicles, and reduce dependence on fossil fuels. This approach is expected to create a more environmentally friendly urban transportation system, support the achievement of climate targets, and improve the overall quality of life in Jakarta.

Abstract:

Background: This study examines the impact of Mobile Phone Use (MPU) on Distracted Driving (DD) and the moderating role of Self-Regulation Skills (SRS) among drivers. With the increasing use of smartphones, distracted driving has become a critical issue, contributing to numerous road accidents. This research aims to explore how MPU affects DD and how SRS can mitigate these risks. Methods: A cross-sectional survey was conducted with 220 participants aged 15-58, including both professional and non-professional drivers. Data were collected through questionnaires measuring MPU frequency, self-regulation skills, and self-reported instances of DD. Statistical analyses, including regression and ANOVA, were used to test the hypotheses. Results: The findings show a significant positive relationship between MPU and DD, with a coefficient of -0.699 (p < 0.001). Self-regulation skills significantly moderated this relationship, reducing the impact of MPU on DD (coefficient = 0.304, p < 0.001). Differences in distraction levels were observed based on gender and vehicle type, with males and four-wheeler drivers exhibiting higher distraction rates. These findings highlight the importance of targeted therapies that account for demographic differences in distraction susceptibility. Conclusion: The study concludes that MPU is a key contributor to distracted driving, but strong self-regulation skills can help mitigate its negative effects. These results highlight the need for targeted awareness campaigns, self-regulation training, and stricter policies to enhance road safety. Ultimately, the study emphasizes the significance of improving self-regulation skills, conducting public awareness efforts, enforcing stronger policies to reduce MPU-related distractions, and improving road safety.

Abstract:

Ports and waterways are integral components of the maritime transport system, facilitating global trade and logistics. Governments, ports, and service providers levy charges on vessels for the use of fairways, port access, and associated services. This study analyzes the port and fairway fee strategies of seven major Baltic Sea ports across four countries: Estonia (Tallinn and Sillamäe), Latvia (Riga and Ventspils), Finland (Helsinki and HaminaKotka), and Sweden (Stockholm). The analysis evaluates the application of general port pricing principles in these ports' strategies. The findings reveal that port fees are predominantly value-based, with tariff rates varying by vessel type and cargo. However, no uniform structure exists for fairway fees. Notably, incorporating environmental components into fairway fee calculations emerges as a promising mechanism to promote sustainability in maritime transport. By incentivizing the adoption of environmentally friendly vessels through differentiated fee structures, ports and policymakers can accelerate the transition toward greener shipping practices. This study highlights the role of economic instruments in advancing environmental objectives and emphasizes the need for a harmonized, sustainability-driven approach to fairway and port pricing in the Baltic Sea region.

Abstract: Autonomous ride-sharing services (ARSS) offer promise in enhancing transportation, improving access for underserved populations, and addressing road safety by mitigating human error. However, their development and adoption are influenced by complex interplay of policies, implementation strategies, technological performance, and market penetration. This scoping review examined the evolving ARSS landscape in the US through literature published between 2018 and 2023. The review included 22 studies, capturing some national policies while no federal regulations related to ARSS were identified. The review predominantly covered market penetration, with few studies addressing performance and one study on implementation strategies. Findings were framed using the socio-ecological model. At the individual level, factors such as safety, affordability, and accessibility influence market penetration of ARSS. At the relational level, trust-building interactions, including the role of safety operators, emerged as key to addressing mobility concerns. At the community level, the findings indicate the need for technological improvements, public infrastructure investment, and education initiatives to enhance ARSS performance and implementation. At the societal level, the review did not include all existing policies in the US, requiring further investigation. These findings provide insights for researchers, transportation planners, and policymakers, guiding the development of evidence-based strategies to foster a sustainable transportation future.

Abstract: Transportation is often cited by Veterans, including minority groups, people with disabilities, and residents of rural areas, as a significant barrier to accessing healthcare. Autonomous shuttles (AS) offer a potential solution, yet limited research has explored Veterans' experiences with this technology. This study qualitatively investigated Veterans’ lived experiences with AS through focus groups, enrolling participants aged 18+ from Gainesville, The Villages, and Lake Nona, Florida. Via a directed content analysis, six key themes were identified: Perceived Benefits, Safety, Experience with Autonomous Vehicles (AV), AS Experience, AV Adoption, and Perception Change. Among 26 participants (aged 30–85; 77% men; 88% urban residents), prominent themes included Safety (n = 161), Perceived Benefits (n = 153), and AS Experience (n = 118), with predominantly positive counts in all themes except AS Experience. Participants acknowledged safety advantages and multitasking potential of AS over human-operated vehicles while recommending improvements to the shuttle’s slow speed, availability and convenience. While the AS ride was positively received overall, some participants noted issues with comfort and braking, emphasizing the need for further technological enhancements. Real-world exposure to AS appeared to influence acceptance positively, offering insights for policymakers and industry stakeholders aiming to optimize AS deployment for mobility-vulnerable Veterans.

Abstract: Artificial Intelligence, Big Data and the Internet of Things ( IoT ) have been in constant development within various fields of study for their application, especially within Traffic Management Systems and sustainable urban transport, the above was born with the need to reduce, mitigate and control large traffic flows, polluting emissions from vehicles, long travel times and traffic accidents that occur within cities, especially cities in underdeveloped countries, such as the Latin American zone. It is important to generate development strategies that consider a multidimensional and long-term perspective, the success of urban development requires strategic governance and the construction of public projects and the construction of the habitat as a public matter with social inclusion. Coordinated action is needed for environmental protection, territorial planning and public policies. Therefore, the purpose of this research is to analyze the implementation of Artificial Intelligence, Big Data and IoT within Traffic Management systems, specifically, within the Ibero-American zone, likewise, to examine the most effective artificial intelligence technologies and algorithms such as Predictive Models that provide traffic flows helping to have better control within the roads, these use Neural Networks to improve the statistical models used in these models, Machine Learning and Deep Learning among others, which have shown to have positive results in predicting demand and reducing vehicular congestion and accidents within cities and identify the challenges and limitations found in the implementation of these solutions within cities. For the above, a bibliographic review and a bibliometric analysis were carried out, which was performed using the Scopus database, supported by Bibliometrix and VOSviewer for bibliometrics, analyzing information on data, trends and characteristics of research publication, most preferred and productive journals, author, journal and productive countries, thematic evaluation and co-occurrence of words. The results show a low relevance of Ibero-America within the field of study despite having several investigations developed within it. The knowledge obtained in this research will be valuable for young researchers, industry professionals, transport policy makers and government entities in their search to identify solutions to road congestion.

Abstract: The explosive growth in the use of motor vehicles has caused many issues in ensuring road and traffic safety. The aim of this paper is to establish the trends and factors that explain traffic violations across the Republic of Kyrgyzstan from 2019 to 2023 to provide information that can be utilized by traffic management authorities. To this end we analyze the frequency and types of violations as well as the distribution of violations by date and time, geographical regions, and types of vehicles from a data set that has sourced more than 2,354,392 recorded traffic violations since Safe City Project commenced in Kyrgyzstan. The analysis defines the places and times where there is traffic, most violations of traffic laws and their major causes. The results inform smart and evidence-based approaches aimed at the enhancement of traffic control, improving compliance levels and overall tackling of the problem of road safety. This work also emphasizes the importance of data analytics applications in addressing the problems of managing traffic in big cities efficiently.

Abstract: Fatigue from multiple sources (e.g., circadian, workload, stress, etc.) can create a compound safety risk. Pilots operating medium-haul (M-H) routes may be susceptible to compound fatigue risk, but sources of fatigue in M-H operations have not been robustly quantified. In an anonymous survey, airline pilots working M-H rosters were asked to rank, on a scale of 0 to 10, the level of fatigue they experience from 40 separate factors across four domains: 1) circadian; 2) environmental; 3) operational; and 4) psychosocial, with higher scores indicating more fatigue. Pilots also reported habitual sleep duration. N=223 pilots (90 Captains; 133 First Officers; mean age: 43±9 years) completed the survey. Pilots rated circadian factors as most fatiguing on average (6±1), followed by factors in the psychosocial and environmental domains (both 5±1), and finally, the operational domain (4±2). Pilots reported sleeping seven hours on average; sleep was not significantly related to fatigue ratings (all p&gt;0.05). Operational fatigue factors related to higher work volume (e.g., working longer hours, shorter breaks, etc.) were rated as more fatiguing. Schedules features that impinge on the window of circadian low (e.g., early starts, late ends) were fatiguing even in M-H pilots with daytime schedules that allow for sufficient sleep duration.

Abstract:

The highway transportation industry is an important component of the transportation industry and one of the key industries causing global climate change. Studying the carbon emission efficiency and influencing factors of enterprises in this industry is of great significance. To identify the carbon emission level of highway transportation enterprises, this article uses a set of table data from China's highway and waterway transportation enterprises to calculate the emissions of carbon sources from the movement of trucks in highway freight transportation enterprises using the "top-down" method. Based on this, the RAM model is used to calculate the economic efficiency, carbon emission efficiency, and unified efficiency of road freight transportation enterprises, and the characteristics of the three types of efficiency are analyzed to further explore the factors that affect the carbon emission efficiency of enterprises. The research results indicate that: (1) both economic efficiency and carbon emission efficiency exhibit spatial agglomeration characteristics, but in 2021, the degree of spatial agglomeration has decreased. (2) From 2020 to 2021, the carbon emission efficiency rankings of various regions remained relatively stable, with the western region, eastern region, central region, and northeastern region ranking in order of carbon emission efficiency; Due to the impact of the epidemic, the economic efficiency of various regions has fluctuated to some extent in 2020-2021, and the fluctuation of unified efficiency is closer to the fluctuation of economic efficiency. (3) The analysis results of the impact on carbon emission efficiency are as follows: the faster the Internet develops, the more stringent the urban environmental requirements are, the higher the carbon emission efficiency of road transport enterprises will be; The more diversified the business model and the longer the transportation distance, the higher the carbon emission efficiency of the enterprise.

Abstract: This study investigates the relationship among lane width, velocity, and accident rates to enhance understanding their impact on road safety and transportation. Analysis of data from 320 urban arterial sections in Utah indicated that narrower lane widths can improve road safety. Reduced vehicle speeds were related to narrower lanes on urban arterials, which did not result in increased collision rates. Reducing one foot in lane width led to an average speed decrease exceeding one mph. Additional factors influencing speed on urban arterials encompass the number of lanes, the existence of medians, on-street parking, roadside obstructions, and block length. Safety modeling indicated no clear correlation between lane width and total crash frequency per mile. Injury crash rates positively correlated with lane width and speed, suggesting that broader lanes and elevated speeds augment the probability of injury crashes. Additional critical elements affecting crash statistics comprised the number of lanes and the Average Annual Daily Traffic (AADT) per lane (in thousands). The study endorses the reduction of lane widths as a viable approach to augment road safety and boost urban transportation infrastructure. The results provide essential direction for policymakers and transportation authorities aiming to enhance road safety and efficiency.

Abstract: Accessibility in public transport is essential for fostering inclusive and sustainable urban development, ensuring equitable mobility for all citizens, particularly individuals with physical disabilities or reduced mobility. Globally, over 1.3 billion individuals, including 4.12 million in Spain, live with disabilities. Despite legislative advances, many cities struggle to meet accessibility standards that enable independent and safe use of public transport. This study evaluates the accessibility of 431 bus stops in Burgos, Spain, using a validated, replicable methodology that incorporates on-site observations, critical accessibility assessments, geolocation, and photographic documentation. Findings highlight persistent barriers, including issues with vehicle encroachment prevention, stop locations, bus shelter design, and the availability of accessible formats such as Braille and audio. Overcoming these barriers can significantly enhance urban mobility, reduce environmental impacts, and align with Sustainable Development Goal 11, particularly Target 11.2, which emphasises accessible and sustainable transport systems. This adaptable methodology offers cities worldwide a robust framework to improve public transport accessibility, contributing to global efforts in creating inclusive, resilient, and climate-neutral urban systems.

Abstract: This study aims to analyse fatal motorcycle accidents in Slovenia over 10 years, highlighting key factors contributing to these incidents. The study integrates data from four databases to evaluate accident trends, infrastructural elements, and rider behaviour through a multi-stage analysis. Results indicate that excessive speed, incorrect direction, and overtaking manoeuvres are primary causes of fatal accidents, especially on non-urban roads. Single-vehicle accidents frequently involve collisions with roadside objects, including safety barriers and poles, highlighting the need for targeted infrastructural improvements. Statistical analysis reveals that seven factors statistically influenced the behaviour of motorcyclists and caused the accident: three human factors (age, gender, experience), one infrastructural factor (pavement width), and three external conditions (accident type, cause, and location). This study provides a foundation for future research on less severe accidents and proactive risk behaviour analysis, aiming to improve motorcyclist safety comprehensively.