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A spatial data model of blind outdoor navigation for path optimization

Author

Listed:
  • Chengfeng Cai

    (Jiangxi University of Science and Technology)

  • Deer Liu

    (Jiangxi University of Science and Technology)

  • Zhen Liu

    (Jiangxi University of Science and Technology)

Abstract

Current navigational aids for blind people do not provide spatial information that meets the requirements of blind and visually impaired people (BVIP) for travel, and traditional map-based navigation services cannot be used directly for navigation. The purpose of this paper is to establish a spatial data model that aligns with their outdoor travel requirements to assist them in accessing spatial information. In alignment with the analysis of spatial information requirements for blind people during outdoor travel, the proposed data model divides the outdoor space into the path layer, the functional layer, the obstacle layer, and the transport and weather layer. Areas such as schools and sports fields, which fulfill certain requirements for them, are categorized as functional features. Essential public transportation stations for outdoor travel are included in transport station features, while obstacles that pose threats to their safety constitute obstacle features. Various features in space are spatially connected through different paths. The proposed semantic information properties enhance the information content representation of the features. The geometry of the features and the topological relationships between them are recorded and used for path planning and navigation in combination with the path layer. Finally, the eastern campus of Jiangxi University of Science and Technology served as an experimental area for the development of a prototype system based on the data model, and a case analysis was provided.

Suggested Citation

  • Chengfeng Cai & Deer Liu & Zhen Liu, 2024. "A spatial data model of blind outdoor navigation for path optimization," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
  • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-03824-6
    DOI: 10.1057/s41599-024-03824-6
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