Urban Currents

Multimodal accessibility to healthy food in Stockholm: Identifying food deserts and urban inequalities across travel modes

The study evaluates healthy food accessibility in Stockholm across walking, cycling, public transport, and driving modes using 5-, 10-, and 15-minute travel-time thresholds. By combining OpenStreetMap and GTFS data, the researchers mapped accessibility isochrones, classified food outlets, and weighted the results by residential population to measure exposure. The analysis reveals that while driving offers near-universal access and cycling greatly expands reach, walking and public transit leave large portions of the population with limited options within short travel times, especially in peripheral neighborhoods.

Why it matters — It demonstrates that proximity-oriented planning frameworks do not automatically guarantee equitable food access when evaluated across different transport modes, highlighting a critical gap between walking-distance ideals and actual multimodal realities in a well-planned Nordic city.

Applied Geography · doi

Q-Net: Queue length estimation via Kalman-based neural networks

The researchers developed Q-Net, a state-space queue estimation framework that integrates aggregated vehicle counts from loop detectors with segment-wise average speed measurements from floating car data. Tested on urban main roads in Rotterdam, Netherlands, the model uses an AI-augmented Kalman filter to learn time-varying gain dynamics and groups speed measurements into fixed-size local groups to keep parameters independent of road section length.

Why it matters — It enables accurate, real-time queue length estimation on signalized intersections using existing, privacy-preserving data sources, eliminating the need for expensive physical sensing infrastructure like cameras or radar.

Caveat: The framework's performance and transferability were evaluated using data from a single city, Rotterdam.

Transportation Research Part C Emerging Technologies · doi

A multidisciplinary framework for brownfield regeneration of Rieti case study

This study presents a multidisciplinary regeneration framework tested on the former SNIA-Montecatini industrial complex in Rieti, Italy. The methodology integrates demographic and volumetric analyses with energy simulations, GIS-based accessibility modeling under the 15-minute city paradigm, and a feasibility assessment for a Renewable Energy Community. The resulting design incorporates relocated public services, green and blue infrastructure, coworking spaces, green roofs, and integrated greenways.

Why it matters — It provides a replicable, interdisciplinary model showing how medium-sized cities can convert obsolete, centrally located industrial voids into self-sufficient energy hubs and public service anchors that mitigate urban heat islands.

Caveat: The framework's performance and feasibility outcomes are based on simulations and models for a single case study site rather than observed post-occupancy data.

Discover Cities · pdf · doi

From avoided emissions to potential credits: A simulation-based case study of helicopter-to-eVTOL substitution in São Paulo

This study simulated the one-to-one replacement of 146 intra-metropolitan helicopter flights in the Sao Paulo Metropolitan Region with electric vertical take-off and landing (eVTOL) aircraft. Using flight trajectories constrained by local helicopter routes and simulated in the BlueSky air traffic simulator, the model calculated energy use and carbon dioxide equivalent emissions. The full substitution of these flights under a conflict-resolution scenario with a 60-second lookahead time avoided 10.27 tonnes of CO2e, representing a mean relative emission reduction of 92.11% in Monte Carlo sensitivity analyses.

Why it matters — It provides a transparent, simulation-based procedure to quantify the potential carbon credits and emission reductions of urban air mobility, demonstrating that the climate benefits of eVTOLs are highly sensitive to local electricity-grid carbon intensity and baseline helicopter fuel efficiency.

Caveat: The findings are based on a small sample of 146 simulated flights within a single metropolitan area and assume a direct, one-to-one replacement of helicopter trips.

Case Studies on Transport Policy · doi

Green in isolation: An interpretable spatial machine learning approach to understanding green satisfaction disparities in segregated neighborhoods

The study developed a spatial machine learning framework, MGW_LightGBM, combined with SHAP to model residents' green satisfaction using multisource data and deep learning. It analyzed how 2D landscape patterns and 3D green morphologies, such as tree height and canopy volume, nonlinearly influence satisfaction across segregated and informal neighborhoods.

Why it matters — It demonstrates that 3D structural elements of urban vegetation are more influential on resident satisfaction than traditional 2D landscape metrics, while revealing that residents in informal neighborhoods exhibit highly pragmatic and spatially adaptive attitudes toward green space due to economic constraints.

Caveat: The abstract does not specify the geographic location, sample size, or the specific cities where the multisource data was collected to train and validate the model.

Habitat International · doi

Wheels up, deals down: The role of air travel in facilitating international trade in India

This study analyzed the relationship between in-person business air travel and India's bilateral trade from 2015 to 2023 using a structural gravity model. It found that a 1% increase in indirect business passengers (those on connecting flights) is associated with a 0.085% increase in expected exports and a 0.044% increase in expected imports, outperforming the trade association of direct passengers. Counterfactual simulations indicate that COVID-19 aviation disruptions reduced India's potential 2021 exports by 31% and imports by 11%, while rolling back Open Skies agreements would cut exports by 4.69% and imports by 1.81%.

Why it matters — The research quantifies the specific trade value of indirect versus direct business flights, demonstrating that connecting business travelers have a disproportionately high association with trade flows and proving how sensitive international trade is to aviation policy rollbacks and pandemic-era disruptions.

Caveat: The study relies on observational air traffic and trade data to establish associations, which may not fully isolate causal mechanisms despite the use of a structural gravity framework.

Transportation Research Part A Policy and Practice · doi

Come fly with me: Scheduling point-to-point transports with collective drones

This study models and solves a scheduling problem for point-to-point aerial transport using collective drones, where multiple smaller drones cooperate to carry heavy, bulky loads. The authors formulate the scheduling problem to minimize makespan while ensuring drone capacities meet job weights and allow for transit times between tasks, evaluating their decomposition-based solution methods and fleet compositions through a computational study.

Why it matters — It establishes a scheduling framework for a new logistics paradigm where drone fleets are dynamically coupled to transport heavy goods, moving beyond the traditional single-drone, lightweight delivery model.

Caveat: The performance and scheduling outcomes are evaluated through simulated computational experiments rather than a real-world physical deployment.

Transportation Research Part B Methodological · doi

Predicting specific injury patterns from crash data: a GIDAS-based and manufacturer-independent logistic regression approach for next generation eCall

This study developed and validated logistic regression models to predict specific, clinically relevant injury patterns for front-row vehicle occupants using German In-Depth Accident Study (GIDAS) data. The models utilize crash severity (Energy Equivalent Speed), restraint use, and vehicle characteristics as predictors, achieving high discrimination with an area under the receiver operating characteristic curve (AROC) above 0.85 for most injury groups. External validation on a recent GIDAS subset confirmed the reproducibility of predictions for head, thorax, and overall severe injuries.

Why it matters — It establishes a manufacturer-independent framework that can translate raw crash telemetry into immediate, region-specific injury predictions. This capability allows next-generation eCall systems to provide emergency dispatchers with precise triage intelligence for allocating specialized trauma resources before responders arrive.

Caveat: The models were developed and validated using historical GIDAS datasets, and their real-world operational utility is still undergoing prospective multicenter validation.

Transportation Research Interdisciplinary Perspectives · doi

Modeling engagement-mediated associations between urban green space quality and well-being in a Global South metropolis

Using survey data from 2,108 residents of the So Paulo Metropolitan Region, Brazil, this study analyzed how perceived urban green space quality relates to psychological well-being. Structural equation modeling revealed that higher levels of green space engagement are positively associated with well-being (̢ = 0.352; p < 0.001). Perceived environmental quality, particularly naturalness, was linked to well-being indirectly through these engagement pathways rather than through a direct relationship.

Why it matters — It provides empirical evidence from a major Latin American metropolis, shifting the focus of urban green space planning from merely increasing the quantity of green areas to prioritizing qualitative improvements that encourage active resident engagement.

Caveat: The study relies on self-reported survey data to measure both perceived environmental quality and psychological well-being, which may introduce subjective bias.

Urban forestry & urban greening · doi

TrafficMind: A System-Oriented Review of Large Language Models for Intelligent Transportation Systems

This review synthesizes recent research on large language models (LLMs) in intelligent transportation systems, proposing a system-level framework called TrafficMind where LLMs act as a shared semantic and reasoning layer. The analysis spans applications in perception, forecasting, control, planning, and coordination, examining how LLMs integrate with reinforcement learning, knowledge graphs, and digital twins.

Why it matters — It establishes that the primary value of LLMs in transportation is not numerical optimization or real-time actuation, but their capacity to unify heterogeneous data, regulations, and human inputs. It also provides a safety-oriented design principle, showing that LLMs are currently most reliable when kept outside of closed-loop control in safety-critical settings like traffic signals and urban air mobility.

Journal of Transportation Engineering Part A Systems · doi

Digital Synergy and Regional Sustainable Development: Promotion or Inhibition? Empirical Evidence from China

This study analyzes the relationship between digital synergy and regional sustainable development across China using panel Tobit, threshold, and mediating effect models. The analysis reveals an overall N-shaped relationship, though regional variations exist, showing a positive linear impact in eastern China and an N-shaped pattern in the central and western regions. The mechanism operates by accelerating resource sharing and reshaping innovation models, which in turn drives green technological innovation and industrial structure upgrading.

Why it matters — It demonstrates that the impact of digital integration is non-linear and geographically uneven, proving that digital development policies must be tailored to regional contexts rather than applied as uniform solutions.

Caveat: The study relies on macro-level regional panel data, which may obscure localized dynamics within specific cities or provinces.

Journal of Urban Planning and Development · doi

If You Want to Win, You’ve Got to Fight: A Guide to Effective Transportation Advocacy

This guide outlines strategic frameworks and tactical approaches for transportation advocacy in the United States, focusing on campaigns to reduce car dominance and promote sustainable transit alternatives.

Why it matters — It provides grassroots organizers and planners with a structured playbook for navigating political and institutional resistance to transit reform, turning abstract policy goals into actionable campaign strategies.

Caveat: The guide is a qualitative, practice-oriented manual rather than an empirical study with quantitative data or measurable outcomes.

Journal of the American Planning Association · doi

First decade revisited: architect-planners, public housing and the decolonization of Singapore

This study analyzes a little-known archive of primary housing files from the early years of Singapore's People's Action Party (PAP) government to trace the evolution of public housing from the late 1950s through the 1960s. It details how the Housing and Development Board (HDB) dissolved professional boundaries between architect-planners, civil servants, and politicians to build a highly centralized, dirigiste housing system. The analysis is structured across three phases: the deconstruction of the colonial planning order, the stabilization of the new system, and the reconstruction of architectural modernism to serve the postcolonial state.

Why it matters — It provides granular archival evidence that challenges the official state-propagated 'Singapore Story' of public housing, demonstrating that the HDB's success relied on an opportunistic blurring of professional and political boundaries rather than a clean, technocratic execution.

Caveat: The study relies on a single, specific archival trove focused on the early PAP administration, which may limit its perspective on broader public reception or alternative planning voices of the era.

Planning Perspectives · doi

Mobile city: Emerging media, space and sociality in contemporary Berlin, by Jordon H. Kraemer

This book-length ethnography examines the intersection of emerging mobile media, urban space, and sociality among young, White, aspiring middle-class residents in Berlin around 2010.

Why it matters — It documents how early mobile social networking technologies reshaped physical urban navigation and social networks during a specific transitional era in Berlin's post-reunification history.

Caveat: The study is a localized, qualitative ethnography focused on a specific demographic group in a single city during the year 2010.

Journal of Urban Affairs · doi

Beyond incentives: Multilevel institutional limits to residential rooftop solar adoption in Pune, India

This study analyzes the deceleration of residential rooftop solar adoption in Pune, India, using qualitative cross-stakeholder analysis mapped to a multilevel institutional framework. It traces how the market transitioned from early incentive-driven adoption among wealthy homeowners to a plateau characterized by interagency coordination gaps, regulatory shifts, and complex compliance procedures.

Why it matters — It demonstrates that sustaining decentralized energy transitions past the early-adopter phase depends on reducing administrative friction and stabilizing governance structures rather than simply increasing financial subsidies.

Caveat: The findings are based on a qualitative case study of a single, historically high-performing Indian city, which may limit direct generalizability to cities with different baseline institutional capacities.

Journal of Urban Affairs · doi

Networks of agglomeration: how population density rewires social networks and reshapes contagion dynamics

An agent-based model isolates the structural effects of population density by keeping population size and individual behaviors constant while changing only spatial proximity. The model simulates social tie formation based on physical closeness and popularity, revealing that higher density triggers a sharp transition from locally clustered communities to globally integrated networks with a highly connected core. Simulating contagions on these generated networks shows that simple contagions spread faster in dense settings, whereas complex contagions achieve wider and more reliable adoption rather than increased speed.

Why it matters — It demonstrates that physical density alone can fundamentally reorganize social network structures and accelerate social dynamics, independent of the economic incentives or behavioral changes usually used to explain why cities foster innovation and rapid change.

Caveat: The findings are based on a minimal agent-based simulation rather than empirical social network data from real-world cities.

arXiv · pdf

External Entropy Production and Human Evolution toward Multi-body Life

This study presents a thermodynamic model using coupled equations to analyze the evolution of human brain size, awareness, and group cooperation starting 2.5 million years ago. It models the transition to 'external entropy production' driven by tool use and fire control, estimating that external entropy production per capita scaled over a 20-million-year trajectory from the initial critical transition.

Why it matters — The model provides a thermodynamic framework that links early human technological development and social cooperation to modern global environmental challenges, framing issues like global warming as systemic consequences of external entropy production.

Caveat: The study relies on highly abstract thermodynamic equations and generalized archaeological timelines rather than direct empirical testing or specific localized datasets.

arXiv · pdf · doi