Urban Currents

Exploring the adoption of digital technologies for environmental planning in Ghana

This study examines the awareness, adoption, drivers, and barriers of digital planning tools through qualitative interviews with 52 environmental planning practitioners across eight regions of Ghana. The findings reveal that while awareness of digital technologies is high, actual adoption is low and heavily concentrated on a narrow set of tools, specifically drones and artificial intelligence.

Why it matters — It identifies a critical gap between technology awareness and actual implementation in sub-Saharan African planning departments, demonstrating that public-private partnerships are the most vital driver for technology adoption due to severe constraints in government capacity.

Caveat: The findings are based on qualitative self-reporting from a sample of 52 practitioners, which may not fully capture the technical performance or objective usage rates of the digital tools.

Discover Cities · pdf · doi

Limits to sustainability in pedestrianized public spaces. Administrative constraints and unintended uses in Barcelona's green axes

This study evaluates the Consell de Cent green axis in Barcelona, a flagship superblock pedestrianization project, using architectural ethnography. The researchers combined field observations of everyday public space use with interviews of architects and residents, analysis of institutional design and land-use documents, and an assessment of ground-floor commercial changes following the street's redesign.

Why it matters — It demonstrates that administrative and regulatory frameworks actively constrain ecological goals during the design phase, while also showing how pedestrianization triggers unplanned commercial shifts and unexpected mobility patterns that undermine intended sustainability outcomes.

Caveat: The findings are based on a qualitative case study of a single, highly publicized flagship project in Barcelona, which may limit direct generalizability to less prominent pedestrianization schemes.

Habitat International · doi

Description, development and application of the integrated transport and health impact modelling tool for global cities (ITHIM-global)

The open-source Integrated Transport and Health Impact Modelling Tool for Global Cities (ITHIM-Global) was developed to simulate how shifts in transport modes affect carbon dioxide emissions, road traffic fatalities, air pollution exposure, and physical activity. Using a quasi-microsimulation approach, the model estimates age- and sex-specific mortality and years of life lost using non-linear dose-response functions. Its application was demonstrated in Bogotá, Colombia, by modeling 5% trip shifts to buses, cars, or cycling, showing that public and active transit shifts yield health benefits primarily through increased physical activity.

Why it matters — It provides a flexible, open-source health impact assessment tool specifically designed for low- and middle-income countries, where rapid urbanization demands accessible tools to quantify the health and environmental trade-offs of transport planning decisions.

Caveat: The model's demonstration relies on hypothetical 5% mode shift scenarios rather than observed policy interventions.

Journal of Transport & Health · doi

Understanding stakeholder preferences for autonomous delivery robots in small communities: A study from Veberöd, Sweden

This study conducted a scenario-based multi-actor-multi-criteria analysis (MAMCA) during a live autonomous delivery robot (ADR) trial in the village of Veber%d, Sweden. It evaluated the preferences of multiple stakeholder groups simultaneously, finding that participants favored ADR systems capable of managing high shipment volumes and diverse goods while supporting the local economy, social ties, and environmental goals.

Why it matters — It shifts the evaluation of autonomous delivery systems from isolated stakeholder perspectives to a collective, socio-technical framework, demonstrating that community acceptance in small settlements depends on local social and economic values rather than purely commercial or operational metrics.

Caveat: The findings are based on a single live trial in a small Swedish village, which may limit their applicability to larger urban areas or different cultural contexts.

Research in Transportation Economics · doi

Optimizing loading space locations for walkable city centers

The study develops a multi-agent discrete event simulation and optimization model to locate freight loading spaces while minimizing total delivery time, which includes driving, walking, and service times. The model incorporates pedestrian zone restrictions as spatial constraints and was applied to the city center network of Omiya City, Japan, to evaluate delivery efficiency under actual pedestrianization plans.

Why it matters — It provides a quantitative tool to balance urban pedestrianization with logistics efficiency, allowing planners to evaluate how specific walkability policies impact delivery times before implementation.

Caveat: The optimization and simulation framework is demonstrated on a single city center network in Japan, which may limit the immediate generalizability of the specific location configurations to other urban layouts.

Transportation Research Part A Policy and Practice · doi

Scheduled service network redesign in freight transportation: Joint demand and service selection under disruption

This study introduces the Scheduled Service Network Redesign (SSNR) problem, formulated as a mixed-integer programming model to optimize demand selection and service routing after natural disasters. Because pre-disaster demands and services must be executed on a damaged physical network with severed links and terminals, the paper develops a Benders Decomposition reformulation to solve the complex optimization problem and evaluates its performance against an exact solver.

Why it matters — It provides a mathematical framework for freight operators to maximize post-disaster profits by systematically deciding which customer demands to accept and how to reroute them when physical infrastructure is partially destroyed.

Caveat: The model's performance and managerial insights are demonstrated through sensitivity analyses and solver comparisons rather than a real-world case study or empirical validation on a specific regional transport network.

Transportation Research Part C Emerging Technologies · doi

The role of urban built environment in promoting dockless bike-sharing and metro integration: an adaptive catchment area approach

The study introduces an Adaptive Catchment Area (ACA) framework based on actual dockless bike-sharing trajectories to analyze how the built environment influences first- and last-mile integration with the metro system in Chengdu. Using Multiscale Geographically Weighted Regression and heat-weighted sensitivity analysis, it measures the impact of street connectivity, greenery, development intensity, and employment types across morning and evening peak hours.

Why it matters — It replaces arbitrary, fixed-radius geometric buffers with actual, data-driven cycling footprints, revealing that high-end office clusters can suppress metro-bike integration while general workplaces and human-scale street greenery enhance it.

Caveat: The empirical findings are based on a single case study of Chengdu and require temporal caution when generalizing to other urban contexts.

Transportation Research Interdisciplinary Perspectives · doi

An extended integrated TAM–TPB–IDT model for explaining new energy vehicle purchase intentions among China’s Generation Z

This study analyzed the factors driving New Energy Vehicle (NEV) purchase intentions among China's Generation Z using survey data from 487 young adults. The researchers integrated the Technology Acceptance Model, the Theory of Planned Behaviour, and Innovation Diffusion Theory, analyzing the data through Partial Least Squares Structural Equation Modelling. The model revealed that perceived usefulness, environmental consciousness, compatibility, charging infrastructure, and smart networked technology positively influence purchase intentions, while perceived risk is not a significant barrier.

Why it matters — It identifies the specific drivers of electric vehicle adoption for a rising demographic in the world's largest NEV market, demonstrating that digital connectivity and infrastructure availability outweigh perceived risks for younger buyers.

Caveat: The findings are based on self-reported purchase intentions rather than actual purchasing behavior.

Transportation Research Interdisciplinary Perspectives · doi

A multi-objective mathematical model for hub location-allocation with inspection under uncertainty: a benders decomposition approach

The study presents a robust multi-objective mathematical model for locating rail hubs and allocating defective wagons for preventive maintenance. The model balances economic costs, environmental impacts, and social factors like transit time reduction and job creation under parameter uncertainty. Small-scale scenarios are solved using an enhanced epsilon-constraint method, while large-scale instances are addressed using a hybrid weighted-sum and Benders decomposition algorithm.

Why it matters — It provides a mathematical framework that integrates maintenance logistics directly into rail network design, demonstrating that increasing wagon capacity is the most effective lever for reducing overall infrastructure, transport, and inspection costs.

Caveat: The model's performance and stability were evaluated using sensitivity analyses on parameter ranges rather than a real-world case study or empirical rail network dataset.

Transportation Research Interdisciplinary Perspectives · doi

Greenness across the lifespan and adult respiratory health: A longitudinal cohort study

This longitudinal cohort study analyzed 57,056 observations from 39,780 participants aged 6 to 25 in Taiwan between 2000 and 2022 to evaluate how life-course exposure to greenness, measured via a two-year average NDVI, affects adult respiratory health. The analysis found that each interquartile range increase in NDVI was associated with 17% to 29% lower odds of lung function impairment, alongside increases of 1.88% in FVC, 1.99% in FEV1, and 1.92% in MMEF. Life-course modeling identified adolescence as the critical period where greenness exposure has the strongest association with adult lung function, with PM2.5 reduction mediating 4.83% to 11.84% of the overall benefit.

Why it matters — It establishes a developmental timeline for environmental health benefits, demonstrating that adolescent exposure to green space is particularly critical for adult lung function and that air pollution mitigation is a key pathway for this effect.

Caveat: The study relies on a cohort from a single region, Taiwan, which may limit the generalizability of the specific developmental windows and mediation percentages to other geographic or climatic contexts.

Urban forestry & urban greening · doi

Everyday politics against spatial injustice: an ethnographic approach to women's resistance in a southern European urban periphery

This paper presents a long-term feminist ethnographic study of a working-class neighborhood in the northern periphery of Granada, Spain, documenting how women organize mutual support and collectivize care. It details a repertoire of everyday urban politics, including the regulation of shared spaces, the creation of neighborhood-based care infrastructures, and the scaling of these networks into formal institutional claims and collective action.

Why it matters — It reframes care and social reproduction not merely as coping mechanisms for urban neglect, but as active political and spatial practices that challenge spatial injustice and expand the definition of the right to the city.

Caveat: The findings are based on a single-site ethnographic study of one neighborhood, which may limit direct generalizability to urban peripheries with different socio-political or cultural contexts.

City · doi

Kriformer: a novel spatiotemporal kriging approach based on graph transformers

The Kriformer model is a novel graph transformer designed for spatiotemporal kriging to estimate data at unobserved locations. It incorporates a custom positional encoding module for node features, a multi-head spatial interaction attention mechanism to capture relationships between observed and unobserved sites, and a random masking training strategy. The model's performance was validated using two real-world traffic speed datasets.

Why it matters — It provides a more accurate method for estimating traffic states and environmental metrics in areas with sparse, unreliable, or missing sensor coverage by expanding the model's perceptual range and improving edge information aggregation.

Caveat: The model's performance was only demonstrated on traffic speed datasets, meaning its effectiveness in other environmental monitoring domains remains unproven.

Transportmetrica A Transport Science · doi

Beyond indicator lists: aligning place-based health assessment tools using a semiotic framework

This study analyzed 14 widely used place-based health assessment tools using a semiotics-based framework across 18 attributes. The analysis revealed that while empirical-level variation is low, with all tools providing operational definitions, significant divergence occurs at the semantic, pragmatic, and social levels, where only 7% of the tools report formal reliability assessments.

Why it matters — It demonstrates that the primary barrier to comparing different urban health rating systems is cross-level structural misalignment rather than simple differences in the indicators themselves, offering a new semiotic compliance framework to harmonize these tools.

Caveat: The findings and proposed framework are based on a sample of 14 selected assessment tools, which may not represent all regional or specialized health rating systems in use.

Cities & Health · doi

Effects of Inert and Active Fillers and Their Physicochemical Properties on Asphalt Mixture Performance

This study evaluated the laboratory performance of two asphalt mixtures, a stone matrix asphalt and a surface mixture, when formulated with different inert and active fillers, including industrial waste-derived fly ash and steel slag. The research characterized the physical and chemical properties of these fillers and measured their impact on rutting, cracking, durability, and moisture resistance. The results show that mixtures containing fly ash and steel slag outperform control mixtures in rutting, cracking, and moisture-damage resistance, while stone matrix asphalt maintained robust performance across all filler types.

Why it matters — It demonstrates that specific industrial waste products can serve as superior, environmentally sustainable replacements for conventional mineral fillers in road infrastructure, simultaneously improving pavement durability and diverting industrial waste from landfills.

Caveat: The findings are based entirely on laboratory-mixed performance tests rather than long-term, real-world field deployments.

Transportation Research Record Journal of the Transportation Research Board · doi

Agent-Based Urban Freight Modeling: Lessons Learned from the Literature and a Framework for Passenger–Freight Integration

This study reviews the agent-based urban freight modeling literature to identify key limitations, such as isolated freight representations and a lack of temporal depth. It introduces a new conceptual framework that integrates logistics actors—including shippers, carriers, receivers, and consumers—with passenger transport systems across long-, medium-, and short-term decision modules within a shared traffic flow simulator.

Why it matters — By linking freight and passenger activities through virtual schedules and shared infrastructure, the framework enables planners to simulate cross-sector interactions, such as e-commerce demand, which were previously modeled in isolation.

Caveat: The presented framework is conceptual, meaning its practical computational performance and calibration challenges in a real-world deployment are not yet evaluated.

Transportation Research Record Journal of the Transportation Research Board · doi

Push-Pull Determinants Among Bangladeshi Students Enrolled in NCR Private Universities: A Single-Destination Exploratory Study

This exploratory study surveyed 56 Bangladeshi students across three private universities in India's National Capital Region to identify migration drivers using Lee's push-pull framework. Analysis of the survey data via K-means clustering and binary logistic regression revealed that academic disruption at home was the primary push factor (mean score 3.73), while geographical and cultural proximity (mean score 3.80) and visa accessibility (mean score 3.73) were the strongest pull factors. Additionally, satisfaction with university infrastructure was the strongest predictor of a student's intent to recommend their institution to others (odds ratio of 2.54).

Why it matters — The study establishes that geographic nearness, cultural familiarity, and visa accessibility function together as a composite accessibility advantage, explaining why students choose regional private universities over traditional destinations like Australia and Germany.

Caveat: The findings are based on a small sample size of 56 students from only three private universities in a single metropolitan region, which limits generalizability to the broader population of international students.

arXiv · pdf

Distance-based subsidy rate design to incentivize ride-hail access to advanced air mobility hubs

This study models a distance-based subsidy rate design to incentivize ride-hail access to advanced air mobility (AAM) hubs, testing it using high-volume for-hire vehicle data from New York City taxi zones. The model incorporates passenger groups with varying values of time and evaluates route choices and operator profitability across candidate vertiports in Manhattan. The simulation reveals that AAM operators must subsidize ride-hailing trips to vertiports when air taxi operating costs exceed $12 per mile.

Why it matters — It establishes a quantitative threshold for when multimodal subsidies become financially necessary for air taxi operators, shifting the discussion of AAM integration from conceptual benefits to specific, spatially explicit pricing and cost boundaries.

Caveat: The findings are based on a simulation of airport access in a single, highly dense metropolitan area and may not generalize to cities with different spatial layouts or lower transit demand.

arXiv · pdf · doi

Urban Power Grid Topology and Hierarchy Identification from Open Data

The researchers developed an open-data-driven framework that reconstructs complete urban power grid topologies from high-voltage transmission lines down to individual building connections. The method fuses public infrastructure data using graph-based algorithms for high- and medium-voltage lines, then applies geospatial machine learning to OpenStreetMap building data to cluster power demand and infer low-voltage distribution lines. The framework was validated by mapping the entire grid network connecting 7,330 buildings and major electricity assets in the Alna district of Oslo, Norway.

Why it matters — It provides a method to bypass the proprietary restrictions on utility network data, enabling researchers to model last-mile power distribution, simulate cascading failures, and analyze grid resilience for renewable energy integration using entirely public data.

Caveat: The framework's reconstruction accuracy was demonstrated in only a single district in Oslo, and its performance may vary in regions with less complete OpenStreetMap data.

arXiv · pdf

Structure-Aware Graph Multi-Task Learning for Dynamic Sparse OD Demand Prediction

The SAGMTL framework decomposes origin-destination (OD) demand prediction into three joint tasks: regional activity states, OD connection activity, and edge-level flow intensity. It uses a node-edge collaborative representation module to capture spatial priors and temporal dynamics, and was evaluated using three real-world urban mobility datasets from Beijing, Chengdu, and Nanjing.

Why it matters — By separating the binary state of whether an OD connection is active from the continuous estimation of its flow volume, the model improves the accuracy and robustness of predictions for highly sparse, intermittent, and long-tailed urban travel patterns.

arXiv · pdf

Virginia Tech Transportation Safety Index (VTTSI)

The Virginia Tech Transportation Safety Index (VTTSI) is a real-time, cloud-native framework that calculates intersection safety scores on a 0 to 100 scale every 15 minutes. It fuses multi-year crash history from the Virginia Department of Transportation using Empirical Bayes stabilization with real-time connected-vehicle telemetry, including speed variance and vulnerable road user exposure. The system integrates these inputs using a CRITIC-weighted multi-criteria decision-making module and visualizes the results via an interactive Streamlit dashboard.

Why it matters — It replaces traditional, lagged crash-based safety assessments with a dynamic, exposure-adjusted monitoring system that captures rapid operational changes and behavioral turbulence as they happen.

Caveat: The system's validation is based on demonstrating coherent diurnal patterns and sensitivity to observed traffic turbulence, rather than direct predictive performance against independent, real-time crash events.

arXiv · pdf