Search Results (53)

This research situates urban planning as a social well-being determinant, highlighting that cities function as social habitats that shape individuals’ quality of life, as well as being physical spaces. The study emphasises the dangers of inadequate urban management, particularly when it is based on biased or incomplete information. This has the potential to exacerbate inequality and undermine the benefits of urbanisation. The present study focuses on the intersection of gender, social roles, and access to basic infrastructure, including childcare centres, elderly facilities, healthcare services, pedestrian paths, street lighting, and green areas. By addressing this critical urban issue, namely the uneven distribution of opportunities for well-being, the study contributes to the existing body of knowledge in this field. The Capability Approach, developed primarily by Amartya Sen and Martha Nussbaum, provides a theoretical framework for evaluating individuals’ freedom to pursue the lives they value. Theories of subjective well-being (SWB) are rooted in psychological and economic traditions that assess individuals’ life satisfaction, happiness, and emotional equilibrium The present study proposes a methodological framework that integrates the Capability Approach with Subjective Well-Being theory. This approach facilitates a more comprehensive measurement of citizens’ well-being, transcending the limitations of traditional gender dichotomies. The study identifies the manner in which infrastructural design affects individual capabilities and demonstrates the manner in which urban policies can foster gender equality and inclusive socio-economic development. It is therefore evident that the research provides urban planners and policymakers with actionable insights by demonstrating that equitable infrastructure provision is a cornerstone of sustainable, socially just urban development. Full article

Aim: Older adult pedestrians are at greater risk of severe injuries than younger pedestrians due to gradual physical changes and coexisting medical conditions. This leads to longer hospital stays, increased mortality risk, and higher inpatient costs. Focusing on the aging population, this study explores the characteristics and injury profiles of pedestrian crossing accidents in the capital city of Bern, Switzerland. Methods: Our retrospective cohort study comprised adult patients admitted to our ED between 1 January 2013 and 31 December 2023, as crossing (or zebra crossing)-related pedestrian victims. Two cohorts were formed on the basis of age < 65 and ≥65 years and compared according to the setting of the accident, type, pattern of the injury, and clinical outcomes (short-term mortality, ICU/hospital length of stay). Results: Of a total of 124 patients, 31.5% (n = 39) of patients were elderly (65+ group). In contrast to the younger patients, the aging population was predominantly admitted as inpatients (64.1% vs. 35.3%, p = 0.001) and was hospitalised in the intensive care unit (20.5% vs. 6%, p = 0.020). Older patients were more likely to be polytraumatised (41% vs. 11.8%, p = 0.001) and to have been tossed or hurled than patients under 65 years (75% vs. 47.3%, p = 0.016). Fractures of the upper extremities (17.9% vs. 4.7%, p = 0.016), pelvis (30.8% vs. 9.4%, p = 0.003), and thoracic spine (12.8% vs. 2.4%, p = 0.019) were significantly more common in the elderly population. Intracranial haemorrhage (35.9% vs. 17.6%, p = 0.026), abdominal trauma (17.9% vs. 5.9%, p = 0.035), and relevant vessel damage (30.8% vs. 3.5%, p < 0.001) were also significantly higher in geriatric patients. Trauma indices were slightly more increased in the older population than in the younger group (ISS; p = 0.004 and AIS > 2 of chest and thoracic spine; abdomen, pelvic contents, and lumbar spine; extremities & bony pelvis p < 0.05). The 65+ group had a longer length of hospital stay (p = 0.001) and ICU stay (p = 0.002). A hospital stay longer than 7 days was also significantly more common in elderly individuals (p = 0.007). In-hospital (15.4% vs. 1.2%, p = 0.001) and 30-day mortality (17.9% vs. 1.2%, p < 0.001) were significantly higher in patients over 65 years of age. Conclusion: In our study, the impact of pedestrian crossing accidents was more severe in the elderly, as indicated by the severity of injuries, hospitalisation rate, longer length of hospital and ICU stays, and higher mortality rates. These findings underline the importance of developing tailored strategies to reduce crosswalk accidents and to optimise management approaches for these vulnerable patients. Full article

Urban mobility plays a vital role in shaping sustainable cities, yet the effectiveness of public transportation is often undermined by poor last-mile connectivity (LMC). In the National Capital Region (NCR) of Delhi, despite the Delhi Metro Rail serving as a key transit system, limited integration with surrounding areas hinders accessibility, which particularly affects women, elderly adults, and socioeconomically disadvantaged groups. This study evaluates LMC performance at two key metro stations, Nehru Place and Botanical Garden, using a mixed-methods approach that includes user surveys, spatial survey, thematic analysis, and infrastructure scoring across five critical pillars: accessibility, safety and comfort, intermodality, service availability, and inclusivity. The findings communicate notable contrasts. Botanical Garden exhibits strong intermodal linkages, pedestrian-friendly design, and supportive signage, while Nehru Place indicates a need for infrastructural improvements, safety advancement and upgrades, and strengthened universal design features. These disparities limit effective metro usage and discourage a shift from private to public transport. The study highlights the importance of user-centered, multimodal solutions and the need for cohesive urban governance to address LMC gaps. By identifying barriers and opportunities for improvement, this research paper contributes to the formulation of more inclusive and sustainable urban transport strategies in Indian metropolitan regions. Full article

This research explores the environmental safety challenges faced by pocket parks in the context of urban aging within Chinese cities. It systematically analyzes visual elements that influence the elderly’s perception of environmental safety by applying interpretable machine learning techniques. By integrating panoramic image semantic segmentation and explainable AI models (e.g., SHAP and PDP), the study transforms subjective environmental perception into measurable indicators and constructs an environmental safety perception model using the LightGBM algorithm. Results indicate that sufficient pedestrian areas and moderate crowd activities significantly enhance safety perception among the elderly. Conversely, the presence of cars emerges as the most substantial adverse factor. Natural elements, such as vegetation and grass, exhibit nonlinear effects on safety perception, with an optimal threshold range identified. The research further elucidates the intricate synergies and constraints among visual elements, underscoring that the highest perceived safety arises from the synergistic combination of positive factors. This study deepens the understanding of environmental perception among the elderly and offers a data-driven framework and practical guidelines for urban planners and designers. It holds significant theoretical and practical implications for advancing the refined and human-centered renewal of urban public spaces. Full article

While autonomous vehicles (AVs) are increasingly integrated into urban mobility, little is known about how digital capability shapes elderly pedestrians’ willingness to share roads with these technologies. This is especially true in the absence of explicit vehicle–pedestrian communication mechanisms. To address this gap, we combine the Theory of Planned Behavior (TPB) with the Pedestrian Behavior Questionnaire (PBQ) and segment elderly pedestrians using Latent Class Analysis (LCA). A sample of 750 older adults in Wuhan, China, was divided into two latent groups: digitally disengaged (70.8%) and digitally engaged (29.2%). Classification was based on four indicators: smart device usage, online social interaction, online entertainment, and online economic behavior. We then applied ordered logit models to estimate group-specific determinants of AV road-sharing acceptance. Results reveal clear heterogeneity across digital capability levels. For digitally disengaged seniors, positive pedestrian behaviors significantly increased willingness (β = 0.316, p = 0.001). Prior accident experience reduced willingness (0 accident: β = 0.435, p = 0.021; 1–2 accidents: β = −0.518, p = 0.012). For digitally engaged seniors, perceived behavioral control showed a marginally positive effect (β = 0.353, p = 0.066). Errors had a significant positive effect (β = 0.540, p = 0.009). Positive behaviors had a significant negative effect (β = −0.414, p = 0.007). These patterns indicate that digital capability not only modulates the strength of TPB pathways but also reshapes behavior–intention linkages captured by PBQ dimensions. Methodologically, the study contributes an integrated TPB–PBQ–LCA–OLM framework. This framework identifies digital capability as a critical moderator of AV acceptance among elderly pedestrians. Practically, the findings suggest differentiated strategies. For digitally disengaged users, interventions should build digital literacy and reinforce safe walking norms. For digitally engaged users, strategies should prioritize transparent AV intent signaling and features that enhance perceived control. Full article

With declining physical functions, elderly pedestrians face a significantly higher risk of severe injuries and fatalities in traffic accidents. This study investigates the factors influencing injury severity among elderly pedestrians using traffic accident reports collected by the Shaanxi Chang’an University Traffic Accident Evidence Identification Center, covering nationwide cases from 2023 to 2024. By analyzing 2351 accident reports involving pedestrians aged 60 and above, 31 feature variables closely related to accident severity were selected to build a predictive model based on the XGBoost algorithm. Additionally, the SHAP method was employed to perform feature attribution analysis on the model’s key variables. The experimental results show that: (1) the model achieved 86% accuracy, 83% precision, 87% recall, and an F1 score of 85%, demonstrating the reliability of XGBoost in predicting injury severity among elderly pedestrians. (2) Global analysis identified collision speed, injury location, and driver awareness as the main factors influencing injury severity. However, the key factors differ across accidents of different severity levels. (3) The effect of the same factor also varies by severity level. For example, driver awareness reduces the likelihood of minor injuries but has less impact on severe injuries or fatalities. This study provides a theoretical foundation for developing traffic safety policies targeting elderly pedestrians and contributes to effectively reducing the severity of injuries in elderly pedestrian traffic accidents. Full article

With rapid global aging, the community environment has become a critical factor influencing cognitive health in older adults. However, most existing studies focus on single environmental attributes and rely on linear analytical methods, which fail to capture the complex and synergistic effects of community features. Guided by an integrated theoretical perspective on environmental psychology, aging, and cognitive health, this study examines how multiple community environmental factors jointly affect cognitive function in elderly people. A case study was conducted among 215 older residents in Shanghai, China. An exploratory factor analysis (EFA) identified the following five key dimensions of community environment: pedestrian friendliness, blue–green spaces, infrastructure, space attractiveness, and safety. We then applied both Partial Least Squares Structural Equation Modeling (PLS-SEM) and Fuzzy Set Qualitative Comparative Analysis (fsQCA) to reveal linear and configurational relationships. The findings showed that pedestrian friendliness, blue–green spaces, and space attractiveness significantly enhance cognitive health, while fsQCA highlighted multiple pathways that underscore the non-linear and synergistic interactions among environmental features. These results provide theoretical insights into the mechanisms linking community environments and cognitive function and offer practical guidance for designing age-friendly communities. Full article

Urban mobility resilience plays a central role in sustainable urban planning discussions, especially considering the challenges of extreme events, climate change, and the increasing scarcity of fossil fuels. This study evaluates urban mobility resilience in Petrópolis (RJ), incorporating socio-spatial heterogeneity and energy vulnerability. This research fills methodological gaps in the literature by proposing a composite resilience index that integrates technical, socioeconomic, and fossil fuel dependency variables within a robust multicriteria framework. We selected eleven variables relevant to urban mobility and organized them into inference blocks. We normalized the variables using Gaussian functions, respecting their maximization or minimization characteristics. We applied the Analytic Hierarchy Process (AHP) to assign weights to the criteria and then aggregated and ranked the results using multicriteria analysis. The final index represents the adaptive capacity of urban territories facing the energy crisis, and we applied it spatially to the neighborhoods of Petrópolis. The analysis identified a significant concentration of neighborhoods with low resilience, particularly in quadrants, combining deficiencies in public transportation, high dependence on fossil fuels, and socioeconomic constraints. Factors such as limited pedestrian access, insufficient motorized public transport coverage, and a high proportion of elderly residents emerged as significant constraints on urban resilience. Intervention strategies that promote active mobility, improve accessibility, and diversify transportation modes proved essential for strengthening local resilience. The results emphasize the urgent need for public policies to reduce energy vulnerability, foster active mobility, and promote equity in access to transportation infrastructure. Full article

The prevalence of car dependence and sedentary lifestyles has created concern in the transportation and health sectors. Walking is the most popular and practical kind of exercise that can significantly enhance health. In Chile, more than half of older adults have health issues and almost 72% of the elderly population never engages in physical activity. This study aims to investigate the relationship between older adults’ walking behavior and the built environment along the streets and parks in Santiago’s middle-income neighborhoods. Six medium-income central and pericentral neighborhoods of Santiago were selected. The average number of older persons who walk along the paths and two modified audit forms were used to measure walking behavior and built environment features, respectively. Both correlation analysis and backward regression were used to examine the associations. While elements like the existence of bus stops, pedestrian streets, and general cleanliness contribute to the enhanced number of older adults who walk along street segments, the presence of insecurity signs was found to be negatively associated with the number of older adults who walk in the neighborhood parks. Furthermore, complexity and mystery showed a negative association with the number of older adults in the neighborhood parks. Urban policymakers might use these findings to encourage older adults to walk more in Santiago’s medium-income neighborhoods. Full article

The rapid development of electric vehicles (EVs) around the world has resulted in new challenges for road safety. Identifying the features of EV crashes is a precondition for developing effective countermeasures. However, due to the short history of EV development, existing studies on EV crashes are quite limited. China, which has the largest EV market in the world, has witnessed a substantial increase in EV crashes in recent years. Therefore, this study comprehensively investigated the characteristics of EV crashes by analyzing the 2023 traffic crash data from Changshu. This is a pioneering study that discusses EV safety by comparing real EV crashes and ICEV crashes from a city in China, the largest EV market in the world. It was found that EV crashes had a higher fatality rate compared to internal combustion engine vehicle (ICEV) crashes. Compared to ICEV crashes, EV crashes are more likely to hit pedestrians and occur during the starting phase. Among the vehicles involved in crashes, the proportion of EVs used for passenger and freight transport was higher than that of ICEVs. In addition, for EV crashes, the proportion of female drivers was much higher, but the proportion of elderly drivers was much lower. Thus, to identify the significant factors influencing crash severity, a logistic regression model was built. The results confirm that EV crashes are more likely to be more fatal than ICEV crashes. In addition, hitting pedestrians and light trucks and crashes occurring in rural areas, at intersections, during winter, and on weekdays could significantly increase the risk of fatalities. These findings are expected to provide new perspectives for improving EV safety within the wave of automotive electrification. Full article

(1) Research Highlights: Existing studies primarily focus on the supply-side evaluation of urban forest accessibility, emphasizing physical proximity while often overlooking real-time usage patterns and demographic-specific exposure. This study shifts the focus to social exposure, analyzing how diverse population groups interact with urban forests across different times of the day, integrating dynamic accessibility metrics. (2) Background and Objectives: Unlike previous research that predominantly assessed urban forest accessibility through conventional models based on static spatial proximity, this study incorporates spatiotemporal population distribution data to capture actual utilization patterns. By introducing a dynamic, exposure-based framework, this research aims to facilitate equitable and temporally sensitive access to green spaces across diverse demographic groups. (3) Materials and Methods: This study focuses on Seoul, South Korea, and applies the Gaussian-based Two-Step Floating Catchment Area (G2SFCA) methodology to assess urban forest accessibility. Living population data (2021–2024) from mobile telecommunications sources were used as demand indicators, while OpenStreetMap (OSM) green space data were utilized as supply indicators. Realistic travel distances were calculated using OSM pedestrian networks and Dijkstra’s algorithm, incorporating slope effects and distance decay functions. A K-means clustering algorithm was applied to classify four distinct exposure types based on demographic and temporal variations. (4) Results: The findings reveal significant disparities in urban forest exposure based on age group and time of day. Four major urban forest exposure patterns were identified: Type A—school-age children, with peak usage around midday; Type B—working-age adults, frequenting mid-sized urban forests during commuting and leisure hours; Type C—elderly individuals, utilizing large-scale urban forests and neighborhood parks mainly in the morning; Type D—young adults, engaging with small urban parks and rest areas at various times. (5) Conclusions: Urban forest management must move beyond the quantitative expansion of green spaces and instead implement customized policies that optimize accessibility and equitable distribution based on distinct temporal and demographic patterns of social exposure. By integrating real-time urban mobility data into urban forest planning, policies can better align green space supply with actual usage, fostering a more equitable, data-driven, and sustainable urban green infrastructure. Full article

This study investigates the association between aggressive driving behavior and elderly pedestrian traffic accidents using the Explainable Artificial Intelligence (XAI) method. This study focuses on Seoul, South Korea, where an aging population and urban challenges create a pressing need for pedestrian safety research. The analysis reveals that aggressive driving behaviors, particularly rapid acceleration, rapid deceleration, and speeding, are the most influential factors on the frequency of and deaths from elderly pedestrian traffic accidents. In addition, several built environments and demographic factors such as the number of crosswalks and elderly population play varying roles depending on the spatial match or mismatch between risky driving areas and accident spots. The findings of this study underscore the importance of tailored interventions including well-lit crosswalks, traffic calming measures, and driver education, to reduce the vulnerabilities of elderly pedestrians. The integration of XAI methods provides transparency and interpretability, enabling policymakers to make data-driven decisions. Expanding this approach to other urban contexts with diverse characteristics could validate and refine the findings, contributing to a comprehensive strategy for improving pedestrian safety globally. Full article

A comfortable outdoor environment, like its indoor counterpart, can significantly enhance the quality of life and improve the physical and mental health of elderly populations. Urban spatial morphology is one of the key factors influencing outdoor environmental performance. To explore the interactions between urban spatial morphology and the outdoor environment for the elderly, this study utilized parametric tools to establish a performance-driven workflow based on a “morphology generation–performance evaluation–morphology optimization” framework. Using survey data from 340 elderly neighborhoods in Beijing, a parametric urban morphology generation model was constructed. The following three optimization objectives were set: maximizing the winter pedestrian Universal Thermal Climate Index (UTCI), minimizing the summer pedestrian UTCI, and maximizing sunlight hours. Multi-objective optimization was conducted using a genetic algorithm, generating a “morphology–performance” dataset. Subsequently, the XGBoost (eXtreme Gradient Boosting) and SHAP (Shapley Additive Explanations) explainable machine learning algorithms were applied to uncover the nonlinear relationships among variables. The results indicate that optimizing spatial morphology significantly enhances environmental performance. For the summer elderly UTCI, the contributing morphological indicators include the Shape Coefficient (SC), Standard Deviation of Building Area (SA), and Deviation of Building Volume (SV), while the inhibitory indicators include the average building height (AH), Average Building Volume (AV), Mean Building Area (MA), and floor–area ratio (FAR). For the winter elderly UTCI, the contributing indicators include the AH, Volume–Area Ratio (VAR), and FAR, while the inhibitory indicators include the SC and porosity (PO). The morphological indicators contributing to sunlight hours are not clearly identified in the model, but the inhibitory indicators for sunlight hours include the AH, MA, and FAR. This study identifies the morphological indicators influencing environmental performance and provides early-stage design strategies for age-friendly neighborhood layouts, reducing the cost of later-stage environmental performance optimization. Full article

In traffic accidents, elderly individuals face a significantly higher risk of mortality compared with other age groups. To investigate the factors contributing to elderly pedestrian accidents and their impact on injury severity, 1420 motor vehicle/elderly pedestrian collisions from the 2019–2023 Chinese Traffic Accident Deep Investigation Database were analyzed using the FP-growth algorithm. This analysis identified 5594 association rules across 28 types of variables within 4 categories of influencing factors. Logistic regression results indicate that pedestrian age, collision speed, time of occurrence, and accident location are significant factors affecting the mortality rate of elderly pedestrians in traffic accidents. Specifically, pedestrian age and collision speed significantly influence mortality rates. As collision speed increases, the mortality rate rises markedly. For elderly pedestrians aged 60 and above, the mortality rate increases by 3.7% with each additional year of age. Moreover, accidents occurring at night, in suburban areas, or in villages are associated with a higher mortality rate. This study offers scientific support for the formulation of safety measures aimed at improving the traffic safety of elderly pedestrians. Full article

This review paper investigates the current state of research on structure-to-human interaction (S2HI) in the monitoring and control of cyclo-pedestrian footbridges, focusing specifically on the biodynamic effects of oscillations on pedestrians. Its aim is, therefore, twofold: In the first half, it examines the limited but evolving understanding of human gait responses to vertical and horizontal vibrations at frequencies and amplitudes characteristic of footbridge dynamics. The second half includes a detailed analysis of various modelling strategies for simulating pedestrian and crowd dynamics, emphasising the movements and stationary behaviours induced by structural vibrations. The aim is to highlight the strengths and limitations of these modelling approaches, particularly their capability to incorporate biomechanical factors in pedestrian responses. The research findings indicate that existing studies predominantly focus on human-to-structure interaction (HSI), often neglecting the reciprocal effects of S2HI, with many results in the literature failing to adequately address the biomechanics of single pedestrians or crowds experiencing structural vibrations on cyclo-pedestrian bridges. This gap underscores the need for more precise and comprehensive studies in the field to improve the understanding of dynamic interactions between single or multiple walking individuals and footbridge vibrations, especially for vulnerable and elderly people with limited mobility. Furthermore, considerations regarding the impact of Structural Control and Health Monitoring to alleviate these issues are briefly discussed, highlighting the potential to optimise footbridge performance in terms of pedestrian comfort. Full article