In this work, we present a system that generates customized pedestrian routes entirely based on data from OpenStreetMap (OSM). The system enables users to define to what extent they would like the route to have green areas (e.g., parks, squares, trees), social places (e.g., cafes, restaurants, shops) and quieter streets (i.e., with less road traffic). We present how the greenness, sociability, and quietness factors are defined and extracted from OSM as well as how they are integrated into a routing cost function. We intrinsically evaluate customized routes from one-thousand trips, i.e., origin⁻destination pairs, and observe that these are, in general, as we intended-slightly longer but significantly more social, greener, and quieter than the respective shortest routes. Based on a survey taken by 156 individuals, we also evaluate the system's usefulness, usability, controlability, and transparency. The majority of the survey participants agree that the system is useful and easy to use and that it gives them the feeling of being in control regarding the extraction of routes in accordance with their greenness, sociability, and quietness preferences. The survey also provides valuable insights into users requirements and wishes regarding a tool for interactively generating customized pedestrian routes.
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http://dx.doi.org/10.3390/s18113794 | DOI Listing |
Sci Rep
September 2024
School of Environment, Society and Sustainability, University of Utah, 260 South Central Campus Drive, Salt Lake City, UT, 84112, USA.
Sensors (Basel)
August 2024
DEETC-ISEL/IPL, R. Conselheiro Emídio Navarro, 1949-014 Lisbon, Portugal.
This study presents a novel approach to enhancing indoor navigation in crowded multi-terminal airports using visible light communication (VLC) technology. By leveraging existing luminaires as transmission points, encoded messages are conveyed through modulated light signals to provide location-specific guidance. The objectives are to facilitate navigation, optimize routes, and improve system performance through Edge/Fog integration.
View Article and Find Full Text PDFOptom Vis Sci
June 2024
Centre for Vision and Eye Research, Optometry and Vision Science, Queensland University of Technology, Brisbane, Queensland, Australia.
Sensors (Basel)
June 2024
ITS Lab, Institute of Computer Science, University of Tartu, 51009 Tartu, Estonia.
Urban environments are undergoing significant transformations, with pedestrian areas emerging as complex hubs of diverse mobility modes. This shift demands a more nuanced approach to urban planning and navigation technologies, highlighting the limitations of traditional, road-centric datasets in capturing the detailed dynamics of pedestrian spaces. In response, we introduce the DELTA dataset, designed to improve the analysis and mapping of pedestrian zones, thereby filling the critical need for sidewalk-centric multimodal datasets.
View Article and Find Full Text PDFSensors (Basel)
June 2024
Department of Geodesy and Geoinformation, TU Wien-Vienna University of Technology, 1040 Vienna, Austria.
The growing urban population and traffic congestion underline the importance of building pedestrian-friendly environments to encourage walking as a preferred mode of transportation. However, a major challenge remains, which is the absence of such pedestrian-friendly walking environments. Identifying locations and routes with high pedestrian concentration is critical for improving pedestrian-friendly walking environments.
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