Search Results (1,723)

This article draws on public opinion surveys conducted as part of the AV-PL-ROAD project, “Polish Road to Automation of Road Transport”. Although selected findings from this survey material were published in 2023, the earlier study was limited to descriptive statistical analysis. The present paper re-examines the same empirical dataset through a different analytical framework focused on latent-structure reconstruction, using a different analytical framework focused on latent-structure reconstruction, providing a more structured and informative interpretation of perceptions of autonomous vehicles in Poland. The study combines within-respondent standardization, Principal Component Analysis (PCA), and k-means clustering to identify the dominant dimensions of perception and recurring perception profiles, complemented by qualitative insights from focus group interviews (FGI) used to support interpretation. The results indicate that perceptions of autonomous vehicles are not one-dimensional, but are organized around three main axes: systemic benefits versus implementation barriers, technological trust and information security, and regulatory-ethical readiness linked to deployment conditions. The analysis also reveals four recurring perception profiles that do not map directly onto simple demographic divisions and are better understood in relation to operational and institutional context. In addition, statistically significant differences between clusters were confirmed using nonparametric tests (Kruskal–Wallis with Dunn–Šidák post hoc analysis). The main contribution of the paper is methodological: it illustrates that previously analyzed survey data can yield structurally informative insights, including the identification of latent dimensions, perception profiles, and statistically significant differences between clusters when reinterpreted through a latent-space approach rather than conventional descriptive methods. The findings provide additional evidence on the social and institutional conditions of transport automation in Poland and provide a more robust analytical basis for future mobility policy and implementation strategies. Full article

Urban heat stress is a growing challenge in hot semi-arid cities, where neighbourhood urban design influences microclimate and outdoor comfort. This study evaluates the effect of neighbourhood spatial layout in Erbil city, using ENVI-met simulations. Five neighbourhoods with varying layouts were modelled under standardized conditions, including uniform building height, surface characteristics, and meteorological forcing. Hourly outputs of air temperature, relative humidity, wind speed, surface temperature, mean radiant temperature, universal thermal climate index, and sky view factor were analyzed after excluding the spin-up period. Results indicate that, while all neighbourhoods exhibited similar diurnal timing of thermal extremes, a key distinctive finding is the identification of a neighbourhood that behaves differently across seasons. The Pavilion neighbourhood remained cooler during summer conditions, while maintaining warmer thermal conditions during winter. This dual seasonal behaviour contrasts with the other neighbourhoods, which generally exhibit a trade-off between reduced summer heat stress and winter cooling. The Pavilion neighbourhood is distinguished by the presence of integrated water lagoons, suggesting that the blue infrastructure, in combination with spatial openness and greenery, can moderate thermal extremes. Overall, the study highlights the importance of neighbourhood-scale spatial design in mitigating urban heat and provides evidence to support the development of sustainable neighbourhoods. Full article

The redevelopment of aging planned cities in South Korea presents a significant carbon dilemma, balancing long-term operational savings against the immediate impact of embodied emissions from new construction. This study addresses this challenge by systematically identifying and prioritizing carbon reduction measures applicable across the entire building life cycle for this specific urban context. Following a comprehensive literature and case study review that produced an initial list of 28 measures, an expert panel of 21 South Korean professionals from academia, public, and private sectors was convened to evaluate their practical applicability and importance. The analysis yielded a final, prioritized framework of 23 measures. Experts strongly endorsed measures related to improving building envelope performance and enhancing energy efficiency, highlighting their immediate impact and feasibility. Conversely, several renewable energy systems and sustainable construction methods were rated lower, primarily due to concerns over high costs, low public acceptance, and prevailing technical constraints. By moving beyond a simple inventory to a prioritized, evidence-based framework, this research provides a clear and actionable guide for policymakers to make strategic decisions for low-carbon urban transformation. Full article

Advanced Driver Assistance Systems (ADAS) are increasingly shaping urban mobility and road safety, yet their benefits depend not only on technical performance, but also on driver acceptance. This study examines how Hungarian drivers perceive and evaluate key ADAS functions, Adaptive Cruise Control (ACC), Lane Keeping/Centering Assist (LKA/LCA), and Forward Cross Traffic Alert (FCTA), in urban driving contexts. The research is based on qualitative focus group discussions conducted in Győr, Hungary, involving drivers aged 20–50 from different age cohorts. Data were analyzed using thematic analysis. The findings show that the acceptance of ADAS is strongly context-dependent and function specific. ACC was perceived primarily as a comfort-enhancing tool, especially on longer or more monotonous routes, while LCA was often regarded intrusive and less reliable in urban conditions due to poor road markings, potholes, and frequent stop-and-go situations. On the contrary, blind spot and cross-traffic-related functions were evaluated more positively due to their direct safety benefits. Trust, perceived risk, and control emerged as key dimensions of acceptance, with many participants emphasising the importance of warning-based support rather than a strong autonomous intervention. In general, the study concludes that urban acceptance of ADAS is shaped by the interaction of infrastructure conditions, perceived usefulness, and driver trust, highlighting the need for more transparent, context sensitive, and user-centered system design in support of safer urban mobility. Full article

Modern architectural heritage is increasingly threatened by rapid urban transformation, yet documentation practices often remain descriptive and insufficiently aligned with governance decision-making processes. This article addresses the gap between heritage documentation and regulatory readiness by proposing the Modern Heritage Documentation Protocol (MHDP), a governance-oriented framework that transforms documentation into decision-grade evidence. The protocol integrates a structured evidence taxonomy and a staged documentation workflow that links architectural documentation to heritage governance requirements, including designation review, conservation planning, and adaptive reuse decisions. The framework was tested through demonstrator applications across three modern architectural heritage cases to evaluate its operational applicability within real documentation workflows. The results show that structured evidence capture and synthesis can convert fragmented heritage information into coherent documentation that supports governance decisions in rapidly transforming urban environments. By reframing documentation as a governance-oriented process, the proposed framework contributes to more effective heritage management and supports the integration of modern architectural heritage within sustainable urban development strategies. Full article

Illegal waste dumping (IWD) remains a major challenge for many developing municipalities, contributing to environmental degradation, public health risks, and socio-economic burdens. This study aims to assess the environmental, health, and socio-economic impacts of IWD and to examine the influence of socio-demographic variables (gender, education, age, and income) on perceived impacts. Primary data was collected through a quantitative survey of 381 participants from the Thabazimbi Local Municipality. The Mann–Whitney test was used to compare perceived IWD impacts between gender groups, and the Kruskal–Wallis test was used to compare perceived IWD impacts across education, age, and income groups. The results showed strong agreement (>80%) on the perceived environmental health and socio-economic impacts of IWD, indicating that IWD is a universal challenge across the municipality. Moreover, the statistical analysis revealed that income and education groups differed in their perceived environmental and socio-economic impacts (p < 0.05), respectively, although the differences were minimal across the impact statements. The study provides valuable insights by integrating environmental, health, and socio-economic effects of IWD across various socio-demographic groups. In doing so, municipalities can develop more sustainable waste management systems that reduce IWD and support broader sustainability objectives, including environmental protection, public health improvement, and socio-economic development. Full article

Rapid urbanization combined with global climate change is intensifying the Surface Urban Heat Island (SUHI) effect worldwide, posing significant risks to human health, thermal comfort, and quality of life in cities. Characterized by notably higher temperatures in urban areas compared to their rural surroundings, the SUHI phenomenon is driven by factors such as increased built-up density and reduced vegetation cover. In this context, open-source remote sensing data, particularly from the Landsat satellite series, play a crucial role in studying surface urban heat islands. Available freely, Landsat’s multispectral and thermal imagery provides extensive spatial coverage and consistent temporal frequency, enabling long-term diachronic analyses. This study leverages a 40-year time series (1984–2024) of Landsat thermal data to map surface temperature variations in urban environments between Kenitra and Rabat cities, facilitating the identification of heat-excess zones linked to anthropogenic factors. Based on the results obtained, the LU/LC maps show that the study area is characterized by the notable growth of urbanization over the period 1984–2024, particularly in the dynamic poles of the region such as the city centers of Kénitra, Rabat, and Sale. This dynamic is highlighted by an increase from 1.8% to 3% in the total area of the region, accompanied by a remarkable decrease in agricultural land and bare soils. The evaluation of the Random Forest (RF) model’s performance also indicates that it successfully classified the data and predicted the LU/LC classes effectively, as confirmed by metric indices such as the Receiver Operating Characteristic curve and the Kappa index, which present very high average values exceeding 90%. Furthermore, the exploitation of the thermal bands of Landsat images provided relevant information on surface temperature variation. The SUHI maps show that the Rabat-Sale-Kenitra (RSK) region experienced a progressive increase in temperature over the study period, rising from 27 °C in 1984 to 44 °C in 2024. This value could increase further due to the continuous dynamics of urbanization. Together, these tools provide a robust framework for understanding the spatiotemporal dynamics of surface urban heat islands and support sustainable urban planning. Full article

Under China’s carbon peaking and carbon neutrality goals, building-integrated photovoltaics (BIPV) are a key option for low-carbon urban transition. However, how urban morphology shapes effective PV potential in severe cold cities remains poorly understood. Previous work focuses on single buildings or citywide resource mapping and rarely yields actionable planning controls. Using Harbin as a case, this study integrates GIS with explainable machine learning to relate building-cluster morphology to effective PV generation potential. An XGBoost model is interpreted with SHAP and partial dependence analysis to quantify factor importance and response ranges. Building density (BD) and floor area ratio (FAR) are the dominant predictors, ranking above the other morphological indicators. PV density peaks at moderate BD (≈0.20–0.35) under medium-to-high development intensity, and it increases when building distribution is moderately even (NNI ≈ 1.3–1.5) with moderate height differentiation. These coupled responses define a Morphological Sweet Spot, indicating that higher PV performance depends on coordinated morphological configurations rather than on any single parameter. The framework provides an interpretable, data-driven basis for building-cluster BIPV assessment and for translating model outputs into morphology-based planning guidance for low-carbon renewal in severe cold regions. Full article

Urban emptiness is a recurring spatial condition across contemporary cities, resulting from long-term planning decisions, functional transformations, and shifting socio-economic dynamics. Urban voids are often interpreted as signs of failure or neglect; however, they also represent flexible and open-ended spaces embedded within everyday urban environments. This study develops and tests the Adaptive Void Assessment Framework (AVAF), a five-dimensional typological instrument applied to n = 33 urban voids identified through a systematic grid-based field survey (100 × 100 m resolution) in the central urban zone of Nitra, Slovakia (March 2025–January 2026). The framework evaluates sites across nine indicators spanning openness, social appropriation, ecological succession, temporal persistence, and institutional flexibility, yielding composite Adaptivity Index scores and four dominant adaptive regimes. The findings demonstrate that 34% of identified voids function in a socially active regime while 14% exhibit ecological dominance, with a moderate positive correlation identified between temporal persistence and adaptive capacity (r = 0.46, p < 0.05). This challenges conventional deficit-based classifications and reframes urban voids as active components of the urban metabolism capable of enhancing ecological connectivity and spatial flexibility within post-industrial urban landscapes. This reframes urban voids from residual outcomes of urbanization to spaces with potential for green integration within sustainable contemporary cities. Full article

Shared pilot-scale bases enhance organizational efficiency and improve the success rate of transformation by leveraging spatial proximity among innovation actors, serving as a critical bridge between laboratory R&D and industrialization in biomedicine. Unlike the dominant models in mature markets such as Europe and the United States, which rely on in-house R&D by leading firms or marketized outsourcing, China has developed a government-guided, regionally adapted model of shared pilot-scale bases. This study refines the classification of innovation actors within innovation ecosystem theory and aims to reveal the spatial agglomeration patterns of these actors within shared pilot-based ecosystems and identify the dominant forces within them. Our analysis reveals that: (1) Shared pilot-scale bases anchor themselves in regions of high innovation concentration, representing government-guided agglomerations of diverse innovation actors. (2) Influenced by variations in local economic foundations, innovation resources, and policies, the innovation networks of shared pilot bases in different cities exhibit both functional and morphological similarities and differences. (3) Strategic placement around leading enterprises can rapidly steer regional innovation gradients and foster industrial aggregation through pilot-scale activities. This study can provide a theoretical basis for spatial policymaking in China’s biomedical industry and offer a typological reference for the layout of pilot-scale platforms within heterogeneous innovation ecosystems globally. Full article

Large retail developments act as strong trip attractors and can substantially alter traffic demand patterns at adjacent urban intersections. This paper analyzes the operational impacts of a major shopping center on two nearby signalized intersections in Novi Sad, Serbia, and evaluates the effects of reconstructing one of them into a turbo roundabout. Traffic data collected before and after the shopping center opening, as well as before and after the intersection reconstruction, were analyzed using calibrated and validated microsimulation models. Results indicate that peak-hour traffic volumes increased by 8.38% and 6.96% at the analyzed intersections following the shopping center opening, leading to increased delays and operational stress under fixed signal control, particularly under unbalanced turning demands. The conversion of the three-leg signalized intersection into a turbo roundabout resulted in substantial reductions in average delay and improvements in level of service under identical traffic demand conditions, mainly due to the elimination of left-turn signal phases and reduced conflict interactions. The findings confirm that turbo roundabouts can provide significant operational benefits in dense urban environments characterized by strong directional flows; however, their effectiveness is highly context-dependent and influenced by traffic composition and geometric constraints. The results are interpreted as representative of typical weekday peak conditions, acknowledging data and temporal limitations. Full article

Electric vehicle (EV) adoption remains critically low in Thailand despite government initiatives, with limited understanding of how adoption factors vary across different user segments. This study investigates the determinants of EV adoption intentions across three distinct groups—internal combustion engine (ICE) users, hybrid electric vehicle (HEV/PHEV) users, and current EV users—to develop targeted adoption strategies. Data were collected from 3794 Thai vehicle users through on-site administered questionnaires and analyzed using multi-group structural equation modeling, integrating the Technology Acceptance Model, Theory of Planned Behavior, and environmental psychology constructs. Results reveal significant differences in adoption pathways across groups: ICE users show the strongest sensitivity to perceived ease of use, indicating technology apprehension as the primary barrier; HEV/PHEV users demonstrate transitional characteristics with the highest experience-usefulness relationship, while current EV users exhibit stronger influence from environmental identity and social norms. All 14 hypotheses were supported, though with varying effect magnitudes across groups. Surprisingly, the attitude-intention relationship was consistently weak across all segments, suggesting unmeasured cultural or contextual factors. This study contributes the first empirical evidence of segmented adoption patterns in an emerging market, revealing a progression pathway from technology-focused concerns (ICE) through balanced considerations (HEV/PHEV) to identity-driven adoption (EV). Findings provide actionable insights for policymakers to design segment-specific interventions: technology familiarization for ICE users, transition facilitation for hybrid users, and community-building for EV users. Full article

Urban innovation spaces are crucial to stimulate innovative thinking and facilitate the integration of science, technology, and humanities. On the one hand, existing research on urban innovation spaces focuses on spatial patterns, associated networks, and spillover effects. They are limited to the macro scale and lack of innovation subject perspective. On the other hand, few studies have explored factors influencing the distribution by examining the needs of innovative talent. This study aimed to identify the evolution mechanism of urban innovation spaces. In total, 36,519 high-tech enterprises in Guangzhou from 2008 to 2023 were selected to represent urban innovation spaces. Spatial analysis methods and statistical methods were employed to investigate the spatiotemporal dynamic characteristics. Furthermore, employing multiscale geographically weighted regression, the study identifies multiple factors influencing the development of innovation spaces from the dual perspectives of the innovation environment and services. The results indicated that characterized by a southeast-northwest orientation, the urban innovation spaces of Guangzhou have displayed an apparent point–axis–face structural evolution, expanding from the central district into sparsely distributed in the suburbs. The factors influencing the distribution of urban innovation spaces, ranked by their degree of impact, were as follows: vehicle carrying, research institutions, public park, living convenience, university resources, business hotel, industrial structure height, and metro station. These findings facilitated the understanding of urban innovation space development and grasped the influencing factors and their functioning mechanisms. They provided references for innovation space planning amidst urban stock development. Full article

Winter road snow significantly alters surface friction conditions and traffic capacity, serving as a critical factor contributing to traffic accidents, congestion, and temporary traffic control measures. Compared with sparsely deployed road sensors and labor-intensive field inspections, traffic surveillance cameras offer advantages such as dense spatial coverage, low deployment cost, and continuous observation capability, providing a feasible solution for segment-level winter road condition monitoring. To meet traffic management needs, this study categorizes the impact of road snow on passability into four classes: Clear, Light, Medium, and Heavy. A road snow coverage dataset containing 10,498 images under complex traffic scenarios was constructed and has been publicly released. Furthermore, nine representative deep learning models were systematically evaluated to compare their recognition performance and applicability for this task. Experimental results show that all models achieved over 89% classification accuracy on the test set. To further examine cross-regional generalization capability, 48 surveillance cameras from Canada and Norway were selected for real-world validation. Among all models, Swin Transformer achieved the highest accuracy of 81.2% under complex lighting conditions and varying viewpoints, demonstrating superior stability and transferability. The findings provide quantitative guidance for model selection and engineering deployment of camera-based winter road monitoring systems. Full article

In urban areas, green spaces have become the main refuge for biodiversity, providing essential habitat and resources for urban-adapted species. However, scientific evidence on the fitness consequences of urban green space management for urban populations remains scarce, limiting our ability to design successful conservation and management strategies. Here, we assess the fitness consequences of different levels of management practices in green spaces (i.e., high for areas with continuous intervention such as regular mowing and irrigation, and low for areas with minimal, sporadic maintenance) based on a 19-year long-term monitoring of the Eurasian Tree Sparrow (Passer montanus), a species with high behavioural plasticity in response to human-altered habitats. We formulated a unistate capture–mark–recapture model to estimate age-dependent survival while accounting for uncertainty in recapture probability. Furthermore, by means of GLMMs, we tested if the level of management influences reproductive parameters (i.e., breeding failure, number of eggs, nestlings, fledglings, brood number from the same year, breeding success). We found that high urban green space management caused a decline in adult survival, but we found no effect on juvenile survival. We also found lower breeding failure, a greater number of eggs, and larger brood numbers in the low management areas, but no differences were found in the number of nestlings and fledglings. Consequently, we found no differences in overall breeding success. Our results highlight the reduction in survival in a near-threatened passerine species due to routine green urban space management, in addition to differences in reproductive parameters depending on the degree of green urban space management. Overall, we confirm that the same species show several reproductive strategies with different breeding effort to reach similar breeding success, whatever the human context is. However, birds pay the cost in adult survival, and probably in shortening life span. Therefore, the management of urban green spaces has a negative impact on biodiversity in cities. It is necessary to review the management practices of these urban areas and promote practices that are friendly to biodiversity. Full article