Social dimensions of transportation

Inclusive accessibility: Analyzing socio-economic disparities in perceived accessibility

New paper!  Kar, A., Xiao, N., Miller, H.J. and Le, H.T.K. “Inclusive accessibility: Analyzing socio-economic disparities in perceived accessibility,” Computers, Environment and Urban Systems,  114, 102202

Highlights

  • Inclusive access considers both physical and perceptual barriers to travel.
  • Perceptions of safety and comfort vary with people’s socio-economic statuses.
  • Existing infrastructure and services yield unequal access across communities.
  • High-income white populations experience transportation privileges over others.
  • Low-income communities with greater risk exposures perceive higher mobility barriers.

Abstract

Existing accessibility measures mainly focus on the physical limitations of travel and ignore travelers’ perceptions, behavior, and socio-economic differences. By integrating approaches in time geography and travel behavior, this study introduces a bottom-up inclusive accessibility concept that aggregates individual-level travel perceptions across socio-economic groups to evaluate their multimodal access to opportunities. We classify accessibility constraints into hard constraints (physical space-time limitations to travel) and soft constraints (perceptual factors influencing travel, such as safety perceptions, comfort, and willingness to travel). We categorize travelers into 12 mutually exclusive socio-economic groups from a mobility survey dataset of 477 travelers. We apply a support vector regressor-based ensemble algorithm to estimate network-level walking perception scores as soft constraints for each social group. We derive group-specific inclusive accessibility measures that consider space-time limitations from transit and sidewalk networks as hard constraints and minimize the group-specific soft constraint to a certain threshold. Finally, we demonstrate the effectiveness of group-specific inclusive accessibility by comparing it with the classic access measure. Our study provides scientific evidence on how people of varying socio-economic statuses perceive the same travel environment differently. We find that socio-economically disadvantaged communities experience higher mobility barriers and lower accessibility while walking and using transit in Columbus, OH. Our study demonstrates a transition from person- to place-based accessibility measures by sequentially quantifying mobility perceptions for individual travelers and aggregating them by social groups for a large geographic scale, making this approach suitable for equity-oriented need-specific transportation planning.

 

Measuring just accessibility within planetary boundaries

New paper: Willberg, E., Tenkanen, H., Miller, H.J., Pereira, R. H. M. and Toivonen, T. (2023) “Measuring just accessibility within planetary boundaries,” Transport Reviews, DOI: 10.1080/01441647.2023.2240958.

Abstract. Our societies struggle to provide a good life for all without overconsuming environmental resources. Consequently, scholarly search for approaches to meet environmental and social goals of sustainability have become popular. In transport research, accessibility is a key tool to characterise linkages between people, transport, and land use. In the current paper, we propose a conceptual framework for measuring just accessibility within planetary boundaries. We reviewed transport studies and discovered a substantial literature body on accessibility and social disadvantage, much vaster compared to the literature around environmental and ecological impacts of accessibility. We also show a gap in approaches that have integrated these two perspectives. Building on the review, we suggest a conceptual framework for incorporating environmental and social sustainability goals in accessibility research. We conclude the paper by pointing to key challenges and research avenues related to the framework, including (i) dealing with uncertainty and complexity in socio-ecological thresholds, (ii) integrating environmental limits into the conceptualisations of transport equity, (iii) measuring accessibility through other costs than travel time, and (iv) integrating both quantitative and qualitative data.

Turning old maps into 3D digital models of lost neighborhoods

New paper:  Lin Y, Li J, Porr A, Logan G, Xiao N, Miller HJ (2023) “Creating building-level, three-dimensional digital models of historic urban neighborhoods from Sanborn Fire Insurance maps using machine learning.” PLoS ONE 18(6): e0286340. https://doi.org/10.1371/journal.pone.0286340.

Abstract. Sanborn Fire Insurance maps contain a wealth of building-level information about U.S. cities dating back to the late 19th century. They are a valuable resource for studying changes in urban environments, such as the legacy of urban highway construction and urban renewal in the 20th century. However, it is a challenge to automatically extract the building-level information effectively and efficiently from Sanborn maps because of the large number of map entities and the lack of appropriate computational methods to detect these entities. This paper contributes to a scalable workflow that utilizes machine learning to identify building footprints and associated properties on Sanborn maps. This information can be effectively applied to create 3D visualization of historic urban neighborhoods and inform urban changes. We demonstrate our methods using Sanborn maps for two neighborhoods in Columbus, Ohio, USA that were bisected by highway construction in the 1960s. Quantitative and visual analysis of the results suggest high accuracy of the extracted building-level information, with an F-1 score of 0.9 for building footprints and construction materials, and over 0.7 for building utilizations and numbers of stories. We also illustrate how to visualize pre-highway neighborhoods.

 

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