268
Views
0
CrossRef citations to date
0
Altmetric
Research Article

An indoor service area determination approach for pedestrian navigation path planning

ORCID Icon, ORCID Icon & ORCID Icon
Pages 321-332 | Received 01 Dec 2021, Accepted 29 Oct 2022, Published online: 16 Dec 2022

References

  • Alam, M., Perugu, H., & McNabola, A. (2018). A comparison of route-choice navigation across air pollution exposure, co2 emission and traditional travel cost factors. Transportation Research Part D: Transport and Environment, 65, 82–100. https://doi.org/10.1016/j.trd.2018.08.007
  • Andersen, J. L. E., & Landex, A. (2008). Catchment areas for public transport. WIT Transactions on the Built Environment, 101, 175–184. https://www.witpress.com/elibrary/wit-transactions-on-the-built-environment/101/19399
  • Andreev, S., Dibbelt, J., Nöllenburg, M., Pajor, T., & Wagner, D. (2015). Towards Realistic Pedestrian Route Planning. 15th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2015). In G. F. Italiano & M. Schmidt, Eds. Vol. 48. OpenAccess Series in Informatics (OASIcs), Dagstuhl: Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik. (pp. 1–15). https://doi.org/10.4230/OASIcs.ATMOS.2015.1
  • Balata, J., Berka, J., & Mikovec, Z. (2018). Indoor-outdoor intermodal sidewalk-based navi- gation instructions for pedestrians with visual impairments. In International Conference on Computers Helping People with Special Needs (pp. 292–301). Springer International Publishing.
  • Basiri, A., Lohan, E. S., Moore, T., Winstanley, A., Peltola, P., Hill, C., Amirian, P. F., & e Silva, F. P. (2017). Indoor location based services challenges, requirements and usability of current solutions. Computer Science Review, 24, 1–12. https://doi.org/10.1016/j.cosrev.2017.03.002
  • Cambra, P. J., Gonc¸alves, A., & Moura, F. (2019). The digital pedestrian network in complex urban contexts: A primer discussion on typological specifications. Finisterra, 54(110), 155–170.
  • Cheema, M. A. (2018). Indoor location-based services: Challenges and opportunities. SIGSPA- TIAL Special, 10(2), 10–17. https://doi.org/10.1145/3292390.3292394
  • Chen, J., & Clarke, K. C. (2020). Indoor cartography. Cartography and Geographic Information Science, 47(2), 95–109. https://doi.org/10.1080/15230406.2019.1619482
  • Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1(1), 269–271. https://doi.org/10.1007/BF01386390
  • Dong, W., Qin, T., Liao, H., Liu, Y., & Liu, J. (2020). Comparing the roles of landmark visual salience and semantic salience in visual guidance during indoor wayfinding. Cartography and Geographic Information Science, 47(3), 229–243. https://doi.org/10.1080/15230406.2019.1697965
  • Duckham, M., & Kulik, L. (2003). “Simplest” paths: Automated route selection for navigation. In International Conference on Spatial Information Theory (pp. 169–185). Springer.
  • Flisek, P., & Lewandowicz, E. (2019). A methodology for generating service areas that accounts for linear barriers. ISPRS International Journal of Geo-Information, 8(9), 423. https://doi.org/10.3390/ijgi8090423
  • Idrees, A., Iqbal, Z., & Ishfaq, M. (2015). An efficient indoor navigation technique to find optimal route for blinds using QR codes. In Proceedings of the Industrial Electronics and Applications (ICIEA), 2015 IEEE 10th Conference on, Auckland, New Zealand (pp. 690–695).
  • Indriasari, V., Mahmud, A. R., Ahmad, N., & Shariff, A. R. M. (2010). Maximal service area problem for optimal siting of emergency facilities. International Journal of Geographical Information Science, 24(2), 213–230. https://doi.org/10.1080/13658810802549162
  • Joseph, J. (2014). Qr code based indoor navigation with voice response. International Journal of Science and Research, 3(11), 923–926.
  • Jun, C., Park, I., Ryu, K.-W., & Koh, J.-H. (2006). 3D GIS Data Model for Indoor Route Finding. International Journal of Urban Sciences, 10(2), 87–95. https://doi.org/10.1080/12265934.2006.9693593
  • Knoblauch, R. L., Pietrucha, M. T., & Nitzburg, M. (1996). Field studies of pedestrian walking speed and start-up time. Transportation Research Record, 1538(1), 27–38. https://doi.org/10.1177/0361198196153800104
  • Kolavali, S. R., & Bhatnagar, S. (2009). Ant Colony Optimization Algorithms for Shortest Path Problems. In E. Altman & A. Chaintreau (Eds.) Network Control and Optimization. NET-COOP 2008. Lecture Notes in Computer Science (Vol. 5425, pp. 37–44). Springer. https://doi.org/10.1007/978-3-642-00393-6_5
  • LaValle, S. M. (1998). Rapidly-Exploring Random Trees: A New Tool for Path Planning, Technical Report 98-11, Computer Science Dept, Iowa State University.
  • Li, K.J. (2008). Indoor Space: A New Notion of Space. In M. Bertolotto, C. Ray, & X. Li (Eds.) Web and Wireless Geographical Information Systems. W2GIS 2008. Lecture Notes in Computer Science (Vol. 5373, pp. 1–3). Springer. https://doi.org/10.1007/978-3-540-89903-7_1
  • Lin, D., Song, G., & Jia, F. (2014). Review of the research progresses in spatial model for indoor location-based service. Journal of Navigation and Positioning, 2(4), 17–26.
  • Liu, L., & Zlatanova, S. (2013). A Two-level Path-finding Strategy for Indoor Navigation. In S. Zlatanova, R. Peters, A. Dilo, & H. Scholten (Eds.) Intelligent Systems for Crisis Management. Lecture Notes in Geoinformation and Cartography. (pp. 31–42). Springer. https://doi.org/10.1007/978-3-642-33218-0_3
  • Liu, L., & Zlatanova, S. (2015). An approach for indoor path computation among obstacles that considers user dimension. ISPRS International Journal of Geo-Information, 4(4), 2821–2841. https://doi.org/10.3390/ijgi4042821
  • Macatulad, E., & Blanco, A. (2019). A 3DGIS multi-agent geo-simulation model for assessment of building evacuation scenarios considering urgency and knowledge of exits. International Journal of Urban Sciences, 23(3), 318–334. https://doi.org/10.1080/12265934.2018.1549505
  • Munkres, J. R. (1984). Elements of algebraic topology (Vol. 2). Addison-Wesley Menlo Park.
  • Nandini, D., & Seeja, K. (2019). A novel path planning algorithm for visually impaired people. Journal of King Saud University-Computer and Information Sciences, 31(3), 385–391.
  • Noreen, I., Khan, A., & Habib, Z. (2016). A comparison of rrt, rrt* and rrt*-smart path planning algorithms. International Journal of Computer Science and Network Security (IJCSNS), 16(10), 20.
  • Richter, K.-F., Winter, S., & Santosa, S. (2011). Hierarchical representations of indoor spaces. Environment and Planning: B, Planning & Design, 38(6), 1052–1070. https://doi.org/10.1068/b37057
  • Sharker, M. H., Karimi, H. A., & Zgibor, J. C. (2012). Health-optimal routing in pedestrian navigation services. In Proceedings of the First ACM Sigspatial International Workshop on Use of GIS in Public Health (pp. 1–10). HealthGIS'12. https://doi.org/10.1145/2452516.2452518
  • Staats, B., Diakité, A., Voûte, R., & Zlatanova, S. (2019). Detection of doors in a voxel model, derived from a point cloud and its scanner trajectory, to improve the segmentation of the walkable space. International Journal of Urban Sciences, 23(3), 369–390. https://doi.org/10.1080/12265934.2018.1553685
  • Suresh, S., Anand, P. R., & Lenin, D. S. (2015). A novel method for indoor navigation using qr codes. International Journal of Applied Engineering Research, 10(77), 2015.
  • Upchurch, C., Kuby, M., Zoldak, M., & Barranda, A. (2004). Using gis to generate mutually exclusive service areas linking travel on and off a network. Journal of Transport Geography, 12(1), 23–33. https://doi.org/10.1016/j.jtrangeo.2003.10.001
  • Wang, Z., & Zlatanova, S. (2019). Safe route determination for first responders in the presence of moving obstacles. IEEE Transactions on Intelligent Transportations Systems, 21(3), 1044–1053.
  • Watson, D. F. (1981). Computing the n-dimensional delaunay tessellation with application to voronoi polytopes. The Computer Journal, 24(2), 167–172. https://doi.org/10.1093/comjnl/24.2.167
  • Wu, Y., & Xu, J. (2016). The indoor precise location and navigation system based on two- dimensional code and A* algorithm. Electronic Design Engineering, 24(23), 23–28.
  • Xu, M., Wei, S., Zlatanova, S., & Zhang, R. (2017). Bim-based indoor path planning con- sidering obstacles. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 4, 417. https://doi.org/10.5194/isprs-annals-IV-2-W4-417-2017
  • Yan, J., Diakité, A. A., & Zlatanova, S. (2019). A generic space definition framework to support seamless indoor/outdoor navigation systems. Transactions in GIS, 23(6), 1273–1295. https://doi.org/10.1111/tgis.12574
  • Yan, J., Diakité, A. A., Zlatanova, S., & Aleksandrov, M. (2019). Top-bounded spaces formed by the built environment for navigation systems. ISPRS International Journal of Geo- Information, 8(5), 224. https://doi.org/10.3390/ijgi8050224
  • Yang, L., & Worboys, M. (2011). Similarities and differences between outdoor and indoor space from the perspective of navigation. In Proceedings of the International Conference on Spatial Information Theory (COSIT’11). Belfast, Me, USA.
  • Yan, J., Lee, J., Zlatanova, S., Diakité, A. A., & Kim, H. (2022). Navigation network derivation for qr code-based indoor pedestrian path planning. Transactions in GIS, 26(3), 1240–1255. https://doi.org/10.1111/tgis.12912
  • Yan, J., Shang, J., Yu, F., Tang, X., & Zhou, Z. (2016). Indoor spatial structure and mapping methods for real-time localization. Geomatics & Information Science of Wuhan University, 41(8), 1079–1086.
  • Yan, J., Zlatanova, S., & Diakite, A. A. (2020). Two new pedestrian navigation path options based on semi-indoor space. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, VI-4/W1-2020, 175–182. https://doi.org/10.5194/isprs-annals-VI-4-W1-2020-175-2020
  • Yan, J., Zlatanova, S., & Diakité, A. (2021). A unified 3d space-based navigation model for seamless navigation in indoor and outdoor. International Journal of Digital Earth, 14(8), 985–1003. https://doi.org/10.1080/17538947.2021.1913522
  • Yan, J., Zlatanova, S., Lee, J. B., & Liu, Q. (2021a). Indoor traveling salesman problem (itsp) path planning. ISPRS International Journal of Geo-Information, 10(9), 9.
  • Yan, J., Zlatanova, S., Lee, J. B., & Liu, Q. (2021b). Indoor traveling salesman problem (itsp) path planning. ISPRS International Journal of Geo-Information, 10(9), 616. https://doi.org/10.3390/ijgi10090616
  • Zeng, W., & Church, R. L. (2009). Finding shortest paths on real road networks: The case for A*. International Journal of Geographical Information Science, 23(4), 531–543. https://doi.org/10.1080/13658810801949850

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.