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Research Articles

Movement-aware map construction

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Pages 1065-1093 | Received 21 Jun 2019, Accepted 08 Dec 2020, Published online: 05 Jan 2021

References

  • Aanjaneya, M., et al., 2012. Metric graph reconstruction from noisy data. International Journal of Computational Geometry & Applications, 22 (4), 305–325. doi:10.1142/S0218195912600072.
  • Ahmed, M., et al., 2015a. A comparison and evaluation of map construction algorithms using vehicle tracking data. GeoInformatica, 19 (3), 601–632. doi:10.1007/s10707-014-0222-6.
  • Ahmed, M., et al., 2015b. Map construction algorithms. Switzerland: Springer International Publishing.
  • Ahmed, M., Fasy, B.T., and Wenk, C., 2014. Local persistent homology-based distance between maps. In: Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Dallas, TX, USA, 43–52.
  • Ahmed, M. and Wenk, C., 2012. Constructing street networks from GPS trajectories. In: Proceedings of the European Symposium on Algorithms, Ljubljana, Slovenia. Berlin Heidelberg: Springer, 60–71.
  • Bhattacharjee, S., Roy, S., and Bit, S.D., 2019. Post-disaster map builder: crowdsensed digital pedestrian map construction of the disaster affected areas through smartphone based DTN. Computer Communications, 134, 96–113. doi:10.1016/j.comcom.2018.11.010
  • Biagioni, J. and Eriksson, J., 2012a. Inferring road maps from global positioning system traces: survey and comparative evaluation. Transportation Research Record: Journal of the Transportation Research Board, 2291 (1), 61–71. doi:10.3141/2291-08.
  • Biagioni, J. and Eriksson, J., 2012b. Map inference in the face of noise and disparity. In: Proceedings of the 20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Redondo Beach, CA, USA, 79–88. doi:10.1145/2424321.
  • Brakatsoulas, S., et al., 2005. On map-matching vehicle tracking data. In: Proceedings of the 31st International Conference on Very Large Data Bases, Trondheim, Norway, 853–864.
  • Bruntrup, R., et al., 2005. Incremental map generation with GPS traces. In: Proceedings of Intelligent Transportation Systems conference, Vienna, Austria, 574–579.
  • Cao, L. and Krumm, J., 2009. From GPS traces to a routable road map. In: Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Seattle, WA, USA, 1–13. doi:10.1145/1653771.
  • Chen, C., et al., 2016. City-scale map creation and updating using GPS collections. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August, San Francisco, CA, USA, 1465–1474.
  • Cheng, Y., 1995. Mean shift, mode seeking, and clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 17 (8), 790–799. doi:10.1109/34.400568.
  • Davies, J.J., Beresford, A.R., and Hopper, A., 2006. Scalable, distributed, real-time map generation. IEEE Pervasive Computing, 5 (4), 47–54. doi:10.1109/MPRV.2006.83.
  • Deng, M., et al., 2018. Generating urban road intersection models from low-frequency GPS trajectory data. International Journal of Geographical Information Science, 32 (12), 2337–2361. doi:10.1080/13658816.2018.1510124.
  • Edelkamp, S. and Schrödl, S., 2003. Route planning and map inference with global positioning traces. In: R. Klein, H.-W. Six, and L. Wegner, eds. Computer science in perspective. Berlin, Heidelberg: Springer, 128–151.
  • Efentakis, A., et al., 2014. Crowdsourcing turning restrictions for OpenStreetMap. In: Proceedings EDBT/ICDT Workshops, Athens, Greece, 355–362.
  • Fan, H., et al., 2014. Quality assessment for building footprints data on OpenStreetMap. International Journal of Geographical Information Science, 28 (4), 700–719. doi:10.1080/13658816.2013.867495.
  • Fathi, A. and Krumm, J., 2010. Detecting road intersections from GPS traces. In: Proceedings of the International Conference on Geographic Information Science (GISCIENCE), Zurich, Switzerland, 56–69.
  • Flanagin, A.J. and Metzger, M.J., 2008. The credibility of volunteered geographic information. GeoJournal, 72 (3–4), 137–148.
  • Fukunaga, K. and Hostetler, L., 1975. The estimation of the gradient of a density function, with applications in pattern recognition. IEEE Transactions on Information Theory, 21 (1), 32–40. doi:10.1109/TIT.1975.1055330.
  • Ge, X., et al., 2011. Data skeletonization via Reeb graphs. In: Advances in Neural Information Processing Systems, Granada, Spain, 837–845.
  • Goodchild, M.F., 2007. Citizens as sensors: the world of volunteered geography. GeoJournal, 69 (4), 211–221. doi:10.1007/s10708-007-9111-y.
  • Guo, T., Iwamura, K., and Koga, M., 2007. Towards high accuracy road maps generation from massive GPS traces data. In: Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, July, Barcelona, Spain, 667–670. doi:10.1109/IGARSS.2007.4422884.
  • Haklay, M., 2010. How good is volunteered geographical information? A comparative study of OpenStreetMap and Ordnance Survey datasets. Environment and Planning B: Planning and Design, 37 (4), 682–703. doi:10.1068/b35097.
  • Haklay, M. and Weber, P., 2008. Openstreetmap: user-generated street maps. IEEE Pervasive Computing, 7 (4), 12–18. doi:10.1109/MPRV.2008.80.
  • He, E., et al., 2018a. Signal reconstruction approach for map inference from crowd-sourced GPS traces. In: Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Seattle, WA, USA, 472–475.
  • He, S., et al., 2018b. RoadRunner: improving the precision of road network inference from GPS trajectories. In: Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, November, Seattle, WA, USA, 3–12.
  • Huang, J., et al., 2018. Automatic generation of road maps from low quality GPS trajectory data via structure learning. IEEE Access, 6, 71965–71975. doi:10.1109/ACCESS.2018.2882581
  • Karagiorgou, S. and Pfoser, D., 2012. On vehicle tracking data-based road network generation. In: Proceedings of the 20th International Conference on Advances in Geographic Information Systems, Redondo Beach, CA, USA, 89–98. doi:10.1145/2424321.
  • Karagiorgou, S., Pfoser, D., and Skoutas, D., 2013. Segmentation-based road network construction. In: Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Orlando, FL, USA, 460–463.
  • Karagiorgou, S., Pfoser, D., and Skoutas, D., 2017. A layered approach for more robust generation of road network maps from vehicle tracking data. ACM Transactions on Spatial Algorithms and Systems (TSAS), 3 (1), 3.
  • Kasemsuppakorn, P. and Karimi, H.A., 2013. A pedestrian network construction algorithm based on multiple GPS traces. Transportation Research Part C: Emerging Technologies, 26, 285–300. doi:10.1016/j.trc.2012.09.007
  • Kuntzsch, C., Sester, M., and Brenner, C., 2016. Generative models for road network reconstruction. International Journal of Geographical Information Science, 30 (5), 1012–1039. doi:10.1080/13658816.2015.1092151.
  • Lee, W.C. and Krumm, J., 2011. Trajectory preprocessing. In: Y. Zheng and X. Zhou, eds. Computing with spatial trajectories. Berlin, Heidelberg: Springer, 3–33.
  • Li, H., Kulik, L., and Ramamohanarao, K., 2016. Automatic generation and validation of road maps from GPS trajectory data sets. In: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management (CIKM), Indianapolis, USA, 1523–1532.
  • Lyu, H., et al., 2017. Geometric quality assessment of trajectory‐generated VGI road networks based on the symmetric arc similarity. Transactions in GIS, 21 (5), 984–1009.
  • Mariescu-Istodor, R. and Fränti, P., 2018. Cellnet: inferring road networks from gps trajectories. ACM Transactions on Spatial Algorithms and Systems (TSAS), 4 (3), 8.
  • Mehdipoor, H., et al., 2015. Developing a workflow to identify inconsistencies in volunteered geographic information: a phenological case study. PloS One, 10 (10), 1–14. doi:10.1371/journal.pone.0140811.
  • Neis, P. and Zipf, A., 2012. Analyzing the contributor activity of a volunteered geographic information project—The case of OpenStreetMap. ISPRS International Journal of Geo-Information, 1 (2), 146–165. doi:10.3390/ijgi1020146.
  • Ni, Z., et al., 2018. Incremental road network generation based on vehicle trajectories. ISPRS International Journal of Geo-Information, 7 (10), 382. doi:10.3390/ijgi7100382.
  • Pfoser, D., 2011. On user-generated geocontent. In: Proceedings of the International Symposium on Spatial and Temporal Databases. Minneapolis, MN, USA, 458–461.
  • Pfoser, D. and Jensen, C.S., 1999. Capturing the uncertainty of moving-object representations. In: Proceedings of the International Symposium on Spatial Databases (SSD), Hong Kong, China, 111–131.
  • See, L., et al., 2013. Comparing the quality of crowdsourced data contributed by expert and non-experts. PloS One, 8 (7), 1:11. doi:10.1371/journal.pone.0069958.
  • Shi, W., Shen, S., and Liu, Y., 2009. Automatic generation of road network map from massive GPS, vehicle trajectories. In: Proceedings of the 12th International IEEE Conference on Intelligent Transportation Systems, St. Louis, MO, USA, 1–6 . doi:10.1109/ITSC.2009.5309871.
  • Tang, L., et al., 2016. CLRIC: collecting lane-based road information via crowdsourcing. IEEE Transactions on Intelligent Transportation Systems, 17 (9), 2552–2562. doi:10.1109/TITS.2016.2521482.
  • Torre, F., et al., 2012. Matching GPS traces to (possibly) incomplete map data: bridging map building and map matching. In: Proceedings of the 20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Redondo Beach, CA, USA, 546–549.
  • Wang, J., et al., 2015a. A novel approach for generating routable road maps from vehicle GPS traces. International Journal of Geographical Information Science, 29 (1), 69–91. doi:10.1080/13658816.2014.944527.
  • Wang, J., et al., 2017. Automatic intersection and traffic rule detection by mining motor-vehicle GPS trajectories. Computers, Environment and Urban Systems, 64, 19–29. doi:10.1016/j.compenvurbsys.2016.12.006
  • Wang, S., Wang, Y., and Li, Y., 2015b. Efficient map reconstruction and augmentation via topological methods. In: Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems, Seattle, WA, USA, 1–10.
  • Wenk, C., Salas, R., and Pfoser, D., 2006. Addressing the need for map-matching speed: localizing global curve-matching algorithms. In: Proceedings of the 18th Int’l Conference on Scientific and Statistical Data Management (SSDBM), Vienna, Austria, 379–388.
  • Worrall, S. and Nebot, E., 2007. Automated process for generating digitised maps through GPS data compression. In: Proceedings of the Australasian Conference on Robotics and Automation, vol. 6, December, Brisbane, Australia.
  • Wu, H., Xu, Z., and Wu, G., 2019. A novel method of missing road generation in city blocks based on big mobile navigation trajectory data. ISPRS International Journal of Geo-Information, 8 (3), 142. doi:10.3390/ijgi8030142.
  • Xie, X., et al., 2015. Inferring directed road networks from GPS traces by track alignment. ISPRS International Journal of Geo-Information, 4 (4), 2446–2471. doi:10.3390/ijgi4042446.
  • Yang, W., Ai, T., and Lu, W., 2018a. A method for extracting road boundary information from crowdsourcing vehicle GPS trajectories. Sensors, 18 (4), 1261. doi:10.3390/s18041261.
  • Yang, X., et al., 2018b. Automatic change detection in lane-level road networks using GPS trajectories. International Journal of Geographical Information Science, 32 (3), 601–621. doi:10.1080/13658816.2017.1402913.
  • Zandbergen, P.A., 2009. Accuracy of iPhone locations: A comparison of assisted GPS, WiFi and cellular positioning. Transactions in GIS, 13 (1), 5–25. doi:10.1111/j.1467-9671.2009.01152.x.
  • Zhang, L., Thiemann, F., and Sester, M., 2010. Integration of GPS traces with road map. In: Proceedings of the second international workshop on computational transportation science, San Jose, CA, USA, 17–22. doi:10.1145/1899441.
  • Zhang, Y., et al., 2017. An automatic road network construction method using massive GPS trajectory data. ISPRS International Journal of Geo-Information, 6 (12), 400. doi:10.3390/ijgi6120400.
  • Zheng, Y., and Zhou, X. eds., 2011. Computing with spatial trajectories. Berlin, Heidelberg: Springer.

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