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Impact of the road network configuration on map-matching algorithms for FCD in urban environments

Impact of the road network configuration on map-matching algorithms for FCD in urban environments

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Novel ubiquitous traffic sensors such as floating car data (FCD) are getting extended due to the use of 24 h connected smartphones and global positioning systems. Road conditions such as travel speeds in each road link and mobility demand can be monitored by measurements coming from moving vehicles consisting of geolocation and speed information with timestamps. Map-matching is the process needed to identify the corresponding road link on a digital map and define the position of the geolocated vehicle on this link, overcoming positioning errors. Matching processes in urban environments are more prone to error due to the topology and features of city road networks. In this study, the accuracy of the map-matching is discussed depending on the road configuration for FCD in urban and interurban scenarios, under sampling frequencies ranging from 5 to 60 s. Concretely, in this analysis, three matching techniques have been evaluated against road density, nominative speed limit, edge length and edge count values in order to quantify the impact of these variables on the matching accuracy.

References

    1. 1)
      • 1. Official Journal of the European Union L207: ‘Directive 2010/40/EU of the European Parliament and of the Council’, 2010.
        .
    2. 2)
      • Z.C. He , S. Xi-Wei , L.J. Zhuang .
        2. He, Z.C., Xi-Wei, S., Zhuang, L.J., et al: ‘On-line map-matching framework for floating car data with low sampling rate in urban road networks’, IET Intell. Transp. Syst., 2013, 7, pp. 404414.
        . IET Intell. Transp. Syst. , 404 - 414
    3. 3)
      • D. Bernstein , A. Kornhauser .
        3. Bernstein, D., Kornhauser, A.: ‘An introduction to map matching for personal navigation assistants’, 1996.
        .
    4. 4)
      • Y. Lou , C. Zhang , Y. Zheng .
        4. Lou, Y., Zhang, C., Zheng, Y., et al: ‘Map-matching for low-sampling-rate GPS trajectories’. Proc. 17th ACM SIGSPATIAL Int. Conf. Advances in Geographic Information Systems, GIS ‘09, Seattle, WA, USA, November 2009, pp. 352361.
        . Proc. 17th ACM SIGSPATIAL Int. Conf. Advances in Geographic Information Systems, GIS ‘09 , 352 - 361
    5. 5)
      • S. Mattheis , K. Al-Zahid , B. Engelmann .
        5. Mattheis, S., Al-Zahid, K., Engelmann, B., et al: ‘Putting the car on the map: a scalable map matching system for the open source community’. Proc. INFORMATIK 2014: Workshop Automotive Software Engineering, Stuttgart, Germany, September 2014.
        . Proc. INFORMATIK 2014: Workshop Automotive Software Engineering
    6. 6)
      • M. Quddus , W. Ochieng , R. Noland .
        6. Quddus, M., Ochieng, W., Noland, R.: ‘Current map-matching algorithms for transport applications: state-of-the art and future research directions’, Transp. Res. C, Emerging Technol., 2007, 15, (5), pp. 312328.
        . Transp. Res. C, Emerging Technol. , 5 , 312 - 328
    7. 7)
      • C. White , D. Bernstein , A. Kornhauser .
        7. White, C., Bernstein, D., Kornhauser, A.: ‘Some map matching algorithms for personal navigation assistants’, Transp. Res. C, Emerging Technol., 2000, 8, (1-6), pp. 91108.
        . Transp. Res. C, Emerging Technol. , 91 - 108
    8. 8)
      • J.S. Greenfeld .
        8. Greenfeld, J.S.: ‘Matching GPS observations to locations on a digital map’. Proc. 81st Annual Meeting of the Transportation Research Board, 2002.
        . Proc. 81st Annual Meeting of the Transportation Research Board
    9. 9)
      • S. Brakatsoulas , D. Pfoser , R. Salas .
        9. Brakatsoulas, S., Pfoser, D., Salas, R., et al: ‘On map-matching vehicle tracking data’. Proc. 31st Int. Conf. Very Large Data Bases, Trondheim, Norway, August 2005, pp. 853864.
        . Proc. 31st Int. Conf. Very Large Data Bases , 853 - 864
    10. 10)
      • N. Velaga , M. Quddus , A. Bristow .
        10. Velaga, N., Quddus, M., Bristow, A.: ‘Developing an enhanced weight-based topological map-matching algorithm for intelligent transport systems’, Transp. Res. C, Emerging Technol., 2009, 17, (6), pp. 672683.
        . Transp. Res. C, Emerging Technol. , 6 , 672 - 683
    11. 11)
      • J. Yuan , Y. Zheng , C. Zhang .
        11. Yuan, J., Zheng, Y., Zhang, C., et al: ‘An interactive-voting based map matching algorithm’. Proc. 11th Int. Conf. Mobile Data Management (MDM), May 2010, pp. 4352.
        . Proc. 11th Int. Conf. Mobile Data Management (MDM) , 43 - 52
    12. 12)
      • H. Yang , S. Cheng , H. Jiang .
        12. Yang, H., Cheng, S., Jiang, H., et al: ‘An enhanced weight-based topological map matching algorithm for intricate urban road network’, Procedia, Soc. Behav. Sci., 2013, 96, pp. 16701678, Intelligent and Integrated Sustainable Multimodal Transportation Systems Proceedings from the 13th COTA International Conference of Transportation Professionals (CICTP2013).
        . Procedia, Soc. Behav. Sci. , 1670 - 1678
    13. 13)
      • J.J.-C. Ying , B.-N. Shi , K.-C. Lan .
        13. Ying, J.J.-C., Shi, B.-N., Lan, K.-C., et al: ‘Spatial-temporal mining for urban map-matching’. UrbComp 14, New York, NY, USA, August 2014.
        . UrbComp 14
    14. 14)
      • M. Quddus , S. Washington .
        14. Quddus, M., Washington, S.: ‘Shortest path and vehicle trajectory aided map-matching for low frequency GPS data’, Transp. Res. C, Emerging Technol., 2015, 55, pp. 328339, Engineering and Applied Sciences Optimization (OPT-i) – Professor Matthew G. Karlaftis Memorial Issue.
        . Transp. Res. C, Emerging Technol. , 328 - 339
    15. 15)
      • W.Y. Ochieng , M.A. Quddus , R.B. Noland .
        15. Ochieng, W.Y., Quddus, M.A., Noland, R.B.: ‘Map-matching in complex urban road networks’, Braz. J. Cartography, 2004, 55, (2), pp. 118.
        . Braz. J. Cartography , 2 , 1 - 18
    16. 16)
      • P. Newson , J. Krumm .
        16. Newson, P., Krumm, J.: ‘Hidden Markov map matching through noise and sparseness’. Proc. 17th ACM SIGSPATIAL Int. Conf. Advances in Geographic Information Systems, GIS ‘09, New York, NY, USA, 2009, pp. 336343.
        . Proc. 17th ACM SIGSPATIAL Int. Conf. Advances in Geographic Information Systems, GIS ‘09 , 336 - 343
    17. 17)
      • C. Goh , J. Dauwels , N. Mitrovic .
        17. Goh, C., Dauwels, J., Mitrovic, N., et al: ‘Online map-matching based on hidden Markov model for real-time traffic sensing applications’. Proc. 15th Int. IEEE Conf. Intelligent Transportation Systems (ITSC), Anchorage, USA, September 2012, pp. 776781.
        . Proc. 15th Int. IEEE Conf. Intelligent Transportation Systems (ITSC) , 776 - 781
    18. 18)
      • O. Mazhelis .
        18. Mazhelis, O.: ‘Using recursive Bayesian estimation for matching GPS measurements to imperfect road network data’. Proc. 13th Int. IEEE Conf. Intelligent Transportation Systems (ITSC), Funchal, Madeira Island, Portugal, September 2010, pp. 14921497.
        . Proc. 13th Int. IEEE Conf. Intelligent Transportation Systems (ITSC) , 1492 - 1497
    19. 19)
      • T. Feng , H. Timmermans .
        19. Feng, T., Timmermans, H.: ‘Map matching of GPS data with Bayesian belief networks’, J. Eastern Asia Soc. Transp. Stud., 2013, 10, pp. 100112.
        . J. Eastern Asia Soc. Transp. Stud. , 100 - 112
    20. 20)
      • M. Hashemi , H.A. Karimi .
        20. Hashemi, M., Karimi, H.A.: ‘A critical review of real-time map-matching algorithms: current issues and future directions’, Comput. Environ. Urban Syst., 2014, 48, pp. 153165.
        . Comput. Environ. Urban Syst. , 153 - 165
    21. 21)
      • F. Marchal , J. Hackney , K.W. Axhausen .
        21. Marchal, F., Hackney, J., Axhausen, K.W.: ‘Efficient map matching of large global positioning system data sets: tests on speed-monitoring experiment in Zürich’, Trans. Res. Rec.: J. Trans. Res. Board, 2005, 1935, pp. 93100.
        . Trans. Res. Rec.: J. Trans. Res. Board , 93 - 100
    22. 22)
      • F.C. Pereira , H. Costa , N. Pereira .
        22. Pereira, F.C., Costa, H., Pereira, N.: ‘An off-line map-matching algorithm for incomplete map databases’, Eur. Transp. Res. Rev., 2009, 1, (3), pp. 107124.
        . Eur. Transp. Res. Rev. , 3 , 107 - 124
    23. 23)
      • R. Dowling .
        23. Dowling, R.: ‘NCHRP report 616. multimodal level of service analysis for urban streets: users guide’ (NCHRP, 2009).
        .
    24. 24)
      • 24. Openstreetmap contributors, Planet dump. Available at http://planet.openstreetmap.org, accessed January 2016.
        .
    25. 25)
      • C. Moeller .
        25. Moeller, C.: ‘Osm2po: Openstreetmap converter and routing engine for java’. Available at http://osm2po.de, accessed September 2015.
        .
    26. 26)
      • G.H. Dunteman . (1989)
        26. Dunteman, G.H.: ‘Principal components analysis’ (SAGE Publications Inc., 1989), vol. 69.
        .
    27. 27)
      • M. Behrisch , L. Bieker , J. Erdmann .
        27. Behrisch, M., Bieker, L., Erdmann, J., et al: ‘SUMO – simulation of urban mobility: an overview’. Proc. Third Int. Conf. Advances in System Simulation, Barcelona, Spain, October 2011, pp. 6368.
        . Proc. Third Int. Conf. Advances in System Simulation , 63 - 68
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