Leveraging OpenStreetMap to investigate urban accessibility and safety of visually impaired pedestrians

Room: Auditorium B
Academic Track 🎓

Sunday, 14:10
Duration: 5 minutes (plus Q&A)

short paper - pdf

Presentation

video on media.ccc.de

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  • Achituv Cohen (University of California, Santa Barbara)
  • Asya Natapov (Loughborough University)
  • Sagi Dalyot (The Technion)

Cities worldwide encourage urban active mobility by advocating policy and planning. Although contribution is evident, in practice, these actions disregard population parts that have mobility impairments. This research suggests using OpenStreetMap data in customized analytical models to assess the accessibility level of the urban environment for visually impaired pedestrians. Models results show the existence and spatial distribution of existing accessibility problems, including challenging street network connectivity and dangerous walking areas. These models can be used to enable decision makers, city stakeholders and practitioners to enrich management, monitoring and development of their cities, and support sustainable, livable lifestyles and walkability equality.

Many efforts that include city policy and planning strategies are implemented to encourage urban active mobility. The outcome of these actions is measured by how transportable and accessible the city is. Although contribution is evident, in practice, the commonly used measures mostly disregard a huge part of the population that have mobility impairments, which require specific accessibility needs, preventing them to be an equal part of the sustainable city vision.

This research suggests using OpenStreetMap (OSM) data in customized analytical models to assess the accessibility level of the urban environment for visually impaired pedestrians. In principle, the models analyze the city on two levels: routing and accessibility. These are evaluated, correspondingly, based on possible routes, e.g., how long the optimal route is for visually impaired pedestrians compared to the shortest one, and on area, e.g., what is the overall accessibility and safety of a predefined urban extent. The play of both measures enables us to quantify the level of mobility and accessibility of the analyzed city. To do so, we implement the following steps:

  1. We examine the navigation preferences of visually impaired pedestrians in the urban space. This allows a better understanding of the various environmental and morphological factors and characteristics of the urban form that promote safe and accessible navigation. These are translated into spatial and temporal criterion: a) Way Type, which quantifies how suitable the path is in terms of usage and safety; b) the existence of Vision Impairment Assistive Landmarks that support safe wayfinding and navigation; c) Way Complexity, which measures the level of linearity of the path; and d) Crowdedness, which measures the overall pedestrian traffic volume.
  2. We transform OSM’s street network into a weighted graph, where for each graph edge we calculate the cost according to the above criteria. Cost is derived from segments that facilitate safe and accessible walking for visually impaired pedestrians (e.g., separated sidewalks and straight paths), and segments that hinder safe and accessible walking for visually impaired pedestrians (e.g., shared and overcrowded streets).
  3. We develop three analytical models that measure the accessibility level of the urban environment for visually impaired pedestrians: a) street-based, which relies on averaging the costs of all graph edges for a given area, hence it can be implemented for different urban levels (spatial extents); b) centrality-based, which adds on the street-based the centrality indices betweenness and closeness that consider the significance of each graph edge in the street network in respect to all other edges (high centrality values mostly signify streets that attract large pedestrian traffic flow); c) route-based, a navigational method, in which numerous routes are generated on the graph for location tuples, and then the weight ratio of the optimal route for visually impaired pedestrians and the shortest route (commonly used for seeing pedestrians) is evaluated. The smaller the weight value, the more accessible the route.

The developed models are evaluated for Greater London, the UK. 33 boroughs with their wards are analyzed, resulting in processing 421,107 streets, 377,164 OSM nodes and 634, 871 OSM ways. Results show the existence and spatial distribution of accessibility problems for visually impaired pedestrians. The street-based model highlights the fact that urban nature and green spaces, which are typically considered as contributing to wellbeing and encourage walking, are less accessible for visually impaired people, mostly due to the existing road types, e.g., gravel and dirt roads or shared spaces (bikes and pedestrians that share the same path), which are less accessible for this population. The centrality-based model shows that central streets are mostly more accessible, meaning that borough centers are considered in general as accessible, but as distance from city centers grows, the urban environment becomes less accessible. The route-based model, where more than 1,500,000 routes (with length shorter than 1,000 meters) were calculated, showed that on average the optimized routes are 11% longer and 17.5% more accessible than the shortest ones. Some optimal walking routes are twice as long as the shortest ones, where some impose safety issues that critically endanger visually impaired pedestrians. Wards that have a large proportion of street segments with poor accessibility evenly distributed throughout the ward tend to show less efficient route planning in terms of optimal routes that are considerably longer. In general, the route-based model produces clearer results to understanding the city’s morphology in terms of accessibility for visually impaired pedestrians.

To a large extent, these models depend on the quality of OSM data, such that feature completeness and tag correctness should be investigated. In terms of completeness, we found that sidewalks and crossings, which are two important model features, are not always mapped in OSM, mostly in the outskirts of London. One solution is to use learning methods and prediction models to complete missing data. In terms of tag correctness, we found that some inconsistencies exist with certain tags. One solution can be to make tag definitions in, e.g., OSM Wiki, more inclusive and clear, with a focus on accessibility aspects.

Results show how various accessibility levels for visually impaired pedestrians might be assessed and where they are found in the city, pointing to the existing problems this community faces today when navigating. These include challenging street network connectivity and dangerous walking areas. The results also demonstrate that the current practice of urban planning and design worldwide still suffers from lack of democratization, limiting the mobility and navigation of certain groups. The accessibility models developed in this research can be used for better city planning and design, enhancing the city mobility and walkability equality and improving quality of life for these vulnerable road users. Our findings provide analytical tools to enable decision makers, city stakeholders and practitioners to enrich management, monitoring and development of their cities, and support sustainable, livable lifestyles and walkability equality. These, in turn, will ease navigation and mobility of visually impaired pedestrians, overall improving health outcomes and their integration into society.