Urban Currents

Calibrating adaptive smoothing methods for freeway traffic reconstruction

This study presents a Python implementation of the Adaptive Smoothing Method (ASM) for freeway traffic reconstruction, featuring end-to-end calibration formulated as a parameterized kernel optimization problem. Built in PyTorch to allow integration with deep learning workflows, the model was calibrated and evaluated using sparse radar sensor network data against ground truth from a full-state observation testbed.

Why it matters — It provides an open-source, reproducible benchmark for freeway traffic reconstruction that can be calibrated directly from real-world data and easily integrated into modern deep learning pipelines.

European Transport Research Review · doi

Sectoral public perceptions, health implications, and climate adaptation responses to urban heat island in a coastal Indian metropolis

A structured survey of 283 respondents across industrial, commercial, urban residential, and suburban residential zones in Chennai, India, analyzed public awareness and adaptation strategies regarding the urban heat island (UHI) effect. The study used descriptive statistics and chi-square tests to reveal that nearly one-third of participants were unaware of UHI, with 56.4% of households relying on air conditioning for relief and others using hydration or reduced physical activity.

Why it matters — It documents how environmental perceptions and heat adaptation strategies vary by specific urban sectors in a rapidly growing coastal Indian metropolis, revealing that cultural and spiritual beliefs significantly shape how residents explain climate change and urban heat.

Caveat: The findings rely on self-reported survey data from a relatively small sample of 283 respondents in a single metropolitan area.

Discover Cities · doi

Structural and functional robustness in public transportation networks of Latin American cities

This study evaluates the structural and functional robustness of public transit networks in Mexico City, Rio de Janeiro, and Buenos Aires under simulated complete bus-line removal scenarios. Using open infrastructure and mobility data, the researchers measured network fragmentation, trip feasibility, and increased travel costs as lines were progressively dismantled. The analysis revealed a strong alignment between structural and functional robustness across all three cities, with Rio de Janeiro demonstrating the highest structural resilience due to its high line redundancy.

Why it matters — By combining topological network metrics with actual mobility data, this approach moves beyond purely structural vulnerability assessments to quantify the real-world cost and feasibility of trips during major transit disruptions.

Caveat: The study relies on complete bus-line removal as the sole disruption model, which may not capture more common partial service reductions or localized infrastructure failures.

Discover Cities · pdf · doi

Context-sensitive Sponge City strategies: A cross-case and multi-scalar analysis

This study develops a global typology of 38 Sponge City strategies categorized by spatial scale, basin principles, and hydrological processes, and evaluates eight Dutch projects across Amsterdam, Rotterdam, Almere, Purmerend, and The Hague. Using a qualitative, interpretivist methodology with thematic coding, the research analyzes how these strategies perform across five lowland landscape types (coastal, riverine, peat, sandy, and clay) and assesses their ecological, spatial, and social dimensions.

Why it matters — It reveals a significant gap between theoretical Sponge City models and their practical execution, demonstrating that successful climate resilience requires shifting from purely hydrological engineering to context-sensitive designs that actively integrate social equity, accessibility, and community participation.

Caveat: The empirical evaluation of real-world projects is limited to lowland landscape types in the Netherlands, which may restrict the direct applicability of the specific project findings to upland or arid urban environments.

Cities · doi

Exploring the role of politicians and bureaucrats in governance of metropolitan areas. Experiences from Czechia

This study analyzes political-administrative relations in the newly established metropolitan areas of Czechia using semi-structured interviews with politicians and civil servants from two metropolitan regions. The research reveals that civil servants wield significant influence due to their technical expertise in project management and EU funding, while politicians remain largely disengaged from the metropolitan agenda.

Why it matters — It demonstrates that the institutional weakness and uncertain status of emerging metropolitan governance structures stem directly from a political class focused on short-term local electoral benefits rather than regional coordination, leaving bureaucrats to drive the agenda by default.

Caveat: The findings are based on qualitative interviews from only two metropolitan areas in a single country, which may limit generalizability to older or differently structured metropolitan systems.

Cities · pdf · doi

When health risks meet habits: COVID-19 as a natural experiment in older adults’ use of local public transport in Italy

This study analyzes primary survey data from older adults in three Northern Italian cities to examine how their public transit habits for healthcare and socialization survived the COVID-19 pandemic. The analysis reveals that physical accessibility and cost affordability drive transit use for medical trips, while digital transit services and a lack of neighborhood social spaces increase transit use for social purposes. The findings show a strong correlation between pre-pandemic habits and post-pandemic intentions, suggesting long-term resilience in transit use among older populations.

Why it matters — It demonstrates that deep-seated travel habits in older adults can survive major public health disruptions, indicating that public transit demand for essential trips is likely to bounce back rather than permanently decline.

Caveat: The study relies on self-reported primary data and stated intentions from only three cities in a single region of Northern Italy.

Case Studies on Transport Policy · doi

The cost of community transport

Using a mixed-methods dataset that combines financial audits from 31 operators with operational telemetry from 175,000 trips in Australia, this study estimates a transparent cost function for community transport. The analysis reveals a structural deficit where the volume-weighted mean cost of AUD 67.50 per trip is nearly double the current flat-rate subsidy, and exposes a rural cost paradox where low labor costs mask high capital burdens. To address this, a National Variable Pricing Formula was designed as a two-part tariff with a base flag-fall, distance rates, and premiums for remote capital and high-needs clients, which simulations show increases sector-wide cost recovery from 52% to full sustainability.

Why it matters — It provides the first empirical cost analysis of community transport, replacing arbitrary flat-rate subsidies with a transferable, activity-based pricing formula that can prevent operator insolvency without driving cost inflation.

Caveat: The pricing formula and cost benchmarks are derived from a sample of 31 operators within the Australian regulatory and geographic context, which may limit direct application to other national subsidy frameworks.

Research in Transportation Economics · pdf · doi

A standardised Digital Twin design framework for transport system decarbonisation

The study presents a standardized Digital Twin (DT) design framework for transport system decarbonization by adapting the ISO-23247 manufacturing standard to the transport sector. The framework was developed by combining a systematic literature review of over 100 studies with a Delphi consultation of 10 experts from three UK research institutions, analyzing more than 10,000 data records. The resulting layered architecture spans road, rail, marine, and air transport, organizing systems into observable, communication, control, user, and cross-system entities.

Why it matters — It provides the first unified, scalable reference architecture that translates industrial manufacturing standards to the transport sector, moving beyond fragmented, function-specific use cases toward interoperable, system-level digital twins aligned with climate policy.

Caveat: The framework's practical utility and performance remain to be validated in real-world deployments, as the study is based on literature synthesis and expert consultation.

Sustainable Cities and Society · doi

Reflections on the value of trials: Insights from the shared e-scooter trial evaluation in New South Wales, Australia

This study evaluates a shared e-scooter trial conducted across three sites in New South Wales, Australia, between 2022 and 2024. Using an evaluation framework adapted from the European Union's CIVITAS initiative, the research assesses how the trial's outcomes and evaluation processes inform subsequent transport policy decisions.

Why it matters — It provides a structured framework and empirical evidence on how temporary micromobility trials can be systematically evaluated to guide governments on whether to transition from temporary pilots to permanent service deployments.

Caveat: The evaluation framework and policy reflections are derived from a single Australian state's regulatory and geographic context, which may limit direct applicability to other jurisdictions.

Transport Policy · pdf · doi

Bridging physics and data: A mass-adaptive UKF-LSTM framework for real-time joint estimation of freight train mass and running resistance

The study introduces a hybrid MAUKF-LSTM framework that combines a Mass-Adaptive Unscented Kalman Filter with a Long Short-Term Memory network to estimate freight train mass and running resistance in real time. Using timestamped position records from coasting intervals on two major UK mainline routes (Peterborough–Doncaster and Rugby–Crewe), the model separates mass from resistance by reformulating the Davis equation and training on a physics-informed loss function. The framework achieves relative mass errors of approximately 2% on the calibration route and under 1% on an unseen route.

Why it matters — It enables accurate, real-time estimation of critical dynamic train parameters using standard position data, eliminating the need for expensive, dedicated onboard mass-measurement hardware.

Caveat: The framework's evaluation is limited to coasting intervals on two specific UK mainline rail corridors.

Transportation Research Part C Emerging Technologies · doi

How do non-emergency medical transportation services influence patients’ subjective well-being?

This study analyzes how user perceptions of non-emergency medical transportation (NEMT) service quality affect service satisfaction and subjective well-being. Using survey data from rural patients in Illinois, the analysis evaluates the influence of reliability, reservation technology, customer service, accessibility, and driver behavior.

Why it matters — It establishes a direct link between specialized medical transit quality and the subjective well-being of vulnerable rural populations, identifying service reliability as the primary driver of patient satisfaction.

Caveat: The findings are based on survey data from a specific rural patient population in Illinois, which may not generalize to urban NEMT users or other geographic regions.

Transportation Research Part D Transport and Environment · pdf · doi

Valuing eudaimonic wellbeing: A missing piece of the transport appraisal jigsaw

The paper develops a monetary valuation framework for changes in eudaimonic wellbeing, measured using Ryff's 1989 Scale, to address the lack of economic values for this dimension of wellness. The analysis confirms that changes in eudaimonic wellbeing carry a higher monetized value than changes in hedonic life satisfaction due to its integration of broader societal connections.

Why it matters — It provides a novel monetization method that allows transport planners to quantify and incorporate long-term, local quality-of-life benefits—such as those from walking and placemaking projects—which are typically undervalued or omitted in traditional cost-benefit appraisals.

Transportation Research Interdisciplinary Perspectives · pdf · doi

Complete Trip: A Linked Multimodal Human Mobility Dataset

The researchers developed Complete Trip, a dataset that reconstructs linked multimodal travel behavior from passive smartphone location-based services data. The initial release covers six counties in Utah during 2020, capturing journeys across car, bus, rail, and active transportation using a workflow of trip identification, mode imputation, route reconstruction, and trip linking. It provides network-based route representations and statistically calibrated expansion weights to support population-level inference.

Why it matters — It provides a continuous, journey-level representation of travel behavior that links sequential segments of a single trip together, overcoming the limitations of traditional datasets that only capture isolated travel segments.

arXiv · pdf

RACiMo: Red Ambiental Ciudadana de Monitoreo: A Student-Centred Citizen Science Network for Environmental Monitoring, Data Literacy, and Climate Awareness in Colombia

This paper documents the evolution of RACiMo, a student-centred citizen science and environmental monitoring network in Santander, Colombia, that has engaged approximately 515 students across urban, rural, and páramo communities. The initiative transitioned from custom Arduino-Raspberry Pi sensor kits to a multi-municipality network of professional weather and air-quality stations spanning five municipalities. The educational focus shifted from hardware assembly to data analysis, training participants to process and visualize local environmental datasets using Python and Jupyter notebooks.

Why it matters — It demonstrates how citizen science initiatives can scale beyond simple data collection by integrating data literacy and professional-grade monitoring, enabling communities to critically analyze and act on localized environmental issues like industrial pollution and freight traffic.

arXiv · pdf

Global drivers and barriers to the public acceptance of autonomous vehicles: Evidence from 17 countries

This study analyzed survey responses from 18,603 participants across 17 countries in Africa, Asia, Europe, North America, and South America to evaluate public acceptance of Level 3 conditionally automated vehicles. Using a structural equation model based on the Unified Theory of Acceptance and Use of Technology 2 framework, the research measured how performance expectancy, effort expectancy, social influence, facilitating conditions, and hedonic motivation influence the intention to use these vehicles.

Why it matters — It demonstrates that global acceptance of automated driving is primarily driven by perceived utility, social support, and enjoyment, rather than demographic traits or concerns about ease of use, expanding on previous research that was heavily biased toward European populations.

arXiv · pdf