2026-10-07

7 arXiv categories· 96 journals· 4129 candidates — 7 worth your time· 69 without an open abstract

Headline

US one-way commuting times and travel modes, from 2006 to 2024

Today, together

tag shift
no tag ran above its 30-day average
shares references
no items share references today counted over the 7 papers published above
on the same shoulders
no foundation work was cited by four of the day's papers counted over the 68 of this day's 76 named papers whose reference lists we have — standing on the same older work is not the same as being about the same thing
first appearance
Edinburgh Napier University; Iran University of Art; Ollscoil na Gaillimhe – University of Galway none of them on a paper we published in the 117 days before this issue

Two counts, not one counted twice: every row here but “on the same shoulders” counts the papers published above, and that one counts every paper this day named — those and the ones under Also published today, whose abstracts we could not read.

This study analyzes US one-way commuting times from 2006 to 2024 using American Community Survey data alongside travel-diary comparisons from Europe and England. Another study analyzed the relationship between the neighborhood built environment and five mental health outcomes across 356 neighborhoods in Tehran, Iran. Finally, a strategic framework was established to transition South Korea's Incheon Free Economic Zone from a traditional smart city to an AI-driven urban model.

datapreprint

Marcus Oyelaran, Daniel R. Whitcombe
arXiv stat.AP

Transportation Planning and Optimization · Urban Transport and Accessibility · transportation and logistics systems · census data · United States · New York City

How Long Is the Journey to Work? One-Way Commuting Time in the United States from American Community Survey Data, 2006-2024, with Travel-Diary, European and English Comparisons

This study analyzes US one-way commuting times using American Community Survey 1-year tables from 2006 to 2024, alongside comparisons from the 2022 National Household Travel Survey, the 2019 EU labor force survey, and England's travel diary. The average US commute for non-home-based workers rose from 25.0 minutes in 2006 to 27.2 minutes in 2024, peaking at 27.6 minutes in 2019. Public transit riders averaged 49.5 minutes compared to 26.5 minutes for solo drivers, while 9.3% of all commuters traveled 60 minutes or more each way in 2024.

Why it matters — It provides a comprehensive, multi-source baseline of commuting durations and modes across nearly two decades, capturing the dramatic shifts in work-from-home rates which spiked from 5.7% in 2019 to 17.9% in 2021 before settling at 13.3% in 2024.

Caveat: The analysis relies on three distinct national data collection systems with different definitions of commuting, which are presented side-by-side rather than integrated into a single model.

arXiv · pdf

published: Applied Spatial Analysis and Policy

Pouria Boujari, Mojtaba Shahabi Shahmiri
Applied Spatial Analysis and Policy

Edinburgh Napier University

Urban Transport and Accessibility · Urban Green Space and Health · Health disparities and outcomes · spatial econometrics · Edinburgh Napier University · University of Tehran

Spatial Associations Between the Neighborhood Built Environment and Mental Health: Evidence from Tehran

This study analyzed the relationship between the built environment and five mental health outcomes across 356 neighborhoods in Tehran, Iran, using Ordinary Least Squares, Spatial Durbin Models, and Geographically Weighted Regression. The analysis revealed that high residential density is consistently linked to poorer mental health, while population density has no significant association. Access to daily services correlates with reduced somatic symptoms and social dysfunction, whereas anxiety and depression are primarily driven by neighborhood socio-demographic factors like unemployment.

Why it matters — It demonstrates that different dimensions of urban density (residential versus population density) have distinct, non-equivalent impacts on specific mental health outcomes, showing that interventions should target the quality of high-density environments and socioeconomic disparities rather than density in the abstract.

Caveat: The study relies on secondary neighborhood-level data, which aggregates individual mental health experiences to the neighborhood scale and may introduce ecological fallacy risks.

Applied Spatial Analysis and Policy · pdf · doi

published: Discover Cities

Sangho Lee
Discover Cities

Incheon National University

Smart Cities and Technologies · AI and Big Data Applications · Education and Learning Interventions · Incheon National University

A strategic framework for transitioning from smart city to AI city in the Incheon free economic zone (IFEZ)

This study establishes the IFEZ AI City Framework, a four-pillar architecture designed to transition South Korea's Incheon Free Economic Zone from a traditional smart city to an AI-driven urban model. The framework integrates an AI City Brain platform, specialized vertical AI industry clusters across Songdo, Yeongjong, and Cheongna, a responsible governance layer aligned with the 2026 AI Basic Act, and a phased implementation roadmap spanning 2026 to 2030.

Why it matters — It provides a structured, district-scale blueprint and transferable design principles for urban planners looking to upgrade existing smart city infrastructure into coordinated, AI-driven urban operating systems.

Caveat: The proposed framework is currently conceptual and has not yet undergone expert consultation, stakeholder review, or empirical validation through actual deployment.

Discover Cities · doi

preprint

S. M Towhidul Alam, Md. Muhtashim Shahrier, Nazmul Haque, et al.
arXiv stat.AP

Traffic control and management · Traffic Prediction and Management Techniques · Transportation Planning and Optimization · deep learning · Bangladesh University of Engineering and Technology

Bayesian Markov Chain Monte Carlo-Based Simultaneous Speed Prediction Model for Heterogeneous Traffic on Urban Primary Roads

The study developed a simultaneous speed prediction model using a Bayesian Markov Chain Monte Carlo framework to estimate the operating speeds of six distinct vehicle types under heterogeneous, non-lane-based traffic conditions. Using vehicle trajectory data extracted via deep learning from drone videos of five primary roads in Dhaka, Bangladesh, the model achieved R-squared values between 0.922 and 0.956 and root mean square errors ranging from 0.50 to 1.56 km/h. The analysis revealed that excluding non-motorized vehicles increases overall operating speeds and delays the onset of congestion.

Why it matters — It provides a method to model and predict speeds for highly diverse, unstructured traffic streams where different vehicle classes—ranging from heavy trucks to non-motorized transport—interact without lane discipline, a capability missing from standard homogeneous traffic models.

Caveat: The empirical data used to calibrate and validate the model is limited to five primary road corridors within a single city.

arXiv · pdf

preprint

Róisín Luo, Karyn Morrissey
arXiv cs.CY

Flood Risk Assessment and Management · Disaster Management and Resilience · Mental Health via Writing · Ollscoil na Gaillimhe – University of Galway

Assessing flood-related wellbeing from public discourse in Ireland using large language model as judge, 2012--2025

The study analyzes flood-related wellbeing in Ireland from 2012 to 2025 using public discourse data from the Meta Content Library. Researchers developed a three-domain flood-wellbeing instrument and deployed a large language model reasoning pipeline to extract multi-indicator measures, mapping how flood stressors activate distress, shape coping capacity, and interact with social-institutional support systems.

Why it matters — It provides an unobtrusive, discourse-based method and a longitudinal dataset to measure the psychological and social dimensions of flood exposure over more than a decade, replacing traditional reactive surveys with continuous, large-scale monitoring of community resilience and adaptation.

Caveat: The study relies on social media discourse from a single platform's library, which may introduce demographic biases in who is represented in the wellbeing assessment.

arXiv · pdf

preprint

Ravinithesh Reddy Annapureddy, Staņislavs Šeiko, Natalie Higham-James, et al.
arXiv cs.HC

Building A Civic Tool for Community-Police Engagement to Adapt Neighborhood Policing

Through a Research through Design (RtD) inquiry, researchers co-designed and piloted 'Par drošu Rĩgu', a civic tool that integrates qualitative community safety experiences with quantitative police incident data. The co-design process involved workshops, material probes, and a pilot deployment with municipal police, NGOs, and city staff to facilitate stakeholder negotiation and increase officer-citizen interaction.

Why it matters — The tool demonstrates how combining physical and dashboard-based interactions can bridge the gap between institutional data and residents' lived experiences, establishing a collaborative method to rebuild trust in high-distrust post-socialist urban environments.

Caveat: While the pilot increased officer-citizen interactions, it also revealed persistent frictions in sustaining long-term collaboration among the diverse stakeholders.

arXiv · pdf · doi

preprint

Jianing Long, Xiaobin Li, Wuming Lei, et al.
arXiv cs.AI

Beijing

Joint upper-bound coverage and route-choice utility: an empirical evaluation on two urban proxy tasks

The study evaluated how traffic forecast accuracy and uncertainty coverage affect route decisions using speed data from Beijing and Chengdu. Across 150 origin-destination pairs and 14 test days per city, calibrating joint upper bounds increased coverage from 83.19% to 92.26% in Beijing and up to 90.64% in Chengdu, but actually increased lateness by up to 0.92 percentage points and mean travel time by up to 4.4 seconds. Conversely, a 14.91% reduction in speed mean absolute error reduced lateness by 1.46 percentage points.

Why it matters — It demonstrates that optimizing for joint coverage does not translate to better downstream routing utility, showing that higher statistical coverage can sometimes degrade actual travel outcomes.

Caveat: The findings are based on offline proxy tasks with three candidate paths and may not reflect online or causal routing benefits in real-world deployments.

arXiv · pdf

Still cited

Mark Nieuwenhuijsen (2020), Urban and transport planning pathways to carbon neutral, liveable and healthy cities; A review of the current evidence 1 of today's items cite it · 17 of 3240 in the archive stand on it

Also published today

These appeared today in journals we track. Their abstracts are not openly available, so we cannot summarise them.