Advertisement

Background and Related Work

  • Natasha Petrovska
  • Aleksandar Stevanovic
  • Borko Furht
Chapter
  • 336 Downloads
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Abstract

Vehicle traffic has been an important research issue. Numerous studies have been conducted providing insights from various levels and perspectives. Researchers analyze traffic in terms of speed, flow rate, density, volume, occupancy, congestion, etc.

Keywords

Road Segment Visualization Tool Traffic Congestion Traffic Signal Intelligent Transportation System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    D. Levinson, “Highway Capacity and Level of Service.”Google Scholar
  2. 2.
    E. D. Arnold, Jr., “Congestion on Virginia’s Urban Highways,” National Transportation Library, April 1988.Google Scholar
  3. 3.
    J. Zhicai, Z. Xiaoxiong, and Y. Hongwei, “Simulation Research and Implemented Effect Analysis of Variable Speed Limits on Freeway,” Proceedings of the IEEE Intelligent Transportation Systems Conference, Washington, D.C., October 2004, pp. 894–898.Google Scholar
  4. 4.
    T. Thianniwet, S. Phosaard, and W. Pattara-Atikom, “Classification of Road Traffic Congestion Levels from GPS Data Using a Decision Tree Algorithm and Sliding Windows,” Proceedings of the 2014 AC International Joint Conference on Pervasive and Ubiquitous Computing.Google Scholar
  5. 5.
    W. Pattara-Atikom, P Pongpaibool, and S. Thajchayapong, “Estimating Road Traffic Congestion using Vehicle Velocity,” Proceedings of the 6th International Conference on ITS Telecommunications Proceedings, June 2006, pp. 1001–1004.Google Scholar
  6. 6.
    B. S. Kerner, “Tracing and Forecasting of Congested Patterns for Highway Traffic Management,” Proceedings of the IEEE Intelligent Transportation Systems Conference, Oakland, CA, August 2001, pp. 88–93.Google Scholar
  7. 7.
    D. Schrank and T. Lomax. “The 2002 Urban Mobility Report,” Texas Tranrpomiion Inrrimte. June 2002.Google Scholar
  8. 8.
    J. Lu and L. Cao, “Congestion Evaluation From Traffic Flow Information Based on Fuzzy Logic,” IEEE Intelligent Transportation Systems, Vol. 1, 2003, pp. 50–53.Google Scholar
  9. 9.
    P. Pongpaibool, P. Tangamchit, and K. Noodwong, “Evaluation of Road Traffic Congestion Using Fuzzy Techniques,” TENCON Conference, October 2007, pp. 1–4.
  10. 10.
    T. I. Damaiyanti, A. Imawan, and J. Kwon, “Extracting Trends of Traffic Congestion Using a NoSQL Database,” Proceedings of IEEE Fourth International Conference on Big Data and Cloud Computing, December 2014, pp. 209–213.Google Scholar
  11. 11.
    A. Padiath, L. Vanajakshi, S. C. Subramanian, and H. Manda, “Prediction of Traffic Density for Congestion Analysis Under Indian Traffic Conditions,” Proceedings of the 12th International IEEE Conference on Intelligent Transportation Systems, St. Louis, MO, USA, October 2009, pp. 1–6.Google Scholar
  12. 12.
    S. Pongnumkul, N. Kamsiriphiman, J. Poolsawas, and W. Amornwat, “CongestionGrid: A Temporal Visualization of Road Segment Congestion Level Data,” Proceedings of 13th International Symposium on Communications and Information Technologies (ISCIT).Google Scholar
  13. 13.
    A. C. Diker and E. Nasibov, “Estimation of Traffic Congestion Level via FN-DBSCAN Algorithm by Using GPS Data,” Proceedings of 4th International Conference on Problems of Cybernetics and Informatics, 2012.Google Scholar
  14. 14.
  15. 15.
  16. 16.
  17. 17.
    K.N. Balke, H.A. Charara, and R. Parker, “Development of a Traffic Signal Performance Measurement System (TSPMS),” Texas Transportation Institute, Texas A & M University System, 2005.Google Scholar
  18. 18.
    TRB, Highway Capacity Manual 2010. Retrieved from http://hcm.trb.org/, 2011.
  19. 19.
    H.X. Liu, W. Ma, H. Hu, X. Wu, and G. Yu , “SMART-SIGNAL: Systematic Monitoring of Arterial Road Traffic Signals”, Proceedings of the 11th International IEEE Conference on Intelligent Transportation Systems Beijing, China, October 2008, pp. 1061–1066.Google Scholar
  20. 20.
    J. J. Bezuidenhout, P. Ranjitkar, and R. Dunn, “Estimating Queue Length at Signalized Intersections from Single Loop Detector Data,” Proceedings of the Eastern Asia Society for Transportation Studies, Vol. 9, 2013.Google Scholar
  21. 21.
    A. Zaiat and R. J. F. Rossett, “Towards an Integrated Multimodal Transportation Dashboard,” Proceedings of the IEEE 17th International Conference on Intelligent Transportation Systems (ITSC) October 2014. Qingdao, China, pp. 145–150.Google Scholar
  22. 22.
    R. Sen, B. Raman and P. Sharma, “Horn-Ok-Please,” Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services, pp. 137–150.Google Scholar
  23. 23.
    W. Viriyasitavat, J. M. Roldan, and O. K. Tonguz, “Accelerating the Adoption of Virtual Traffic Lights Through Policy Decisions,” Proceedings of the International Conference on Connected Vehicles and Expo (ICCVE).Google Scholar
  24. 24.
    M. Ferreira, R. Fernandes, H. Conceição, W. Viriyasitavat, and O. K. Tonguz, “Self-Organized Traffic Control,” Proceedings of the 7th ACM International Workshop on VehiculAr InterNETworking.Google Scholar
  25. 25.
    M. Nakamurakare, W. Viriyasitavat, and O. K. Tonguz, “A Prototype of Virtual Traffic Lights on Android-based Smartphones”, Poster and Demonstration Sessions, 10th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), June 2013, pp. 236–238.
  26. 26.
    S. Shekhar, C.T. Lu, R. Liu, C. Zhou, “Cubeview: A System for Traffic ata Visualization,” Proceedings of the IEEE 5th International Conference on Intelligent Transportation Systems, September 2002, Singapore, pp. 674–678.Google Scholar
  27. 27.
    H. Piringer, M. Buchetics, and R. Benedik, “AlVis: Situation Awareness in the Surveillance of Road Tunnels,” Proceedings of the IEEE Conference on Visual Analytics Science and Technology (VAST), pp. 153–162.Google Scholar
  28. 28.
    C-T. Lu, A. P. Boedihardjo, and J. Zheng, “AITVS: Advanced Interactive Traffic Visualization System,” Proceedings of the 22nd International Conference on Data Engineering 2006.
  29. 29.
    M. L. Pack, “Wide-area, Web-based Mobility Analysis Using Probe Data,” Proceedings of the 15th International IEEE Conference on Intelligent Transportation Systems Anchorage, Alaska, USA, September 2012, pp. 1682–1686.Google Scholar
  30. 30.
    J. Yoon, B. Noble, and M. Liu, “Surface Street Traffic Estimation,” Proceedings of the 5th International Conference on Mobile Systems, Applications and Services, pp. 220–232.Google Scholar
  31. 31.
    Z. Wang, M. Lu, X. Yuan, J. Zhang, and H. van de Wetering “Visual Traffic Jam Analysis Based on Trajectory Data,” IEEE Transactions on Visualization and Computer Graphics, December 2013, pp. 2159–2168.Google Scholar
  32. 32.
    N. Willems, H. van de Wetering, and J.van Wijk. “Visualization of Vessel Movements,” Proceedings of the 11th Eurographics Conference on Visualization, pp. 959–966.Google Scholar
  33. 33.
    M. Pack, K. Wongsuphasawat, M. VanDaniker, and D. Filippova. “Ice – Visual Analytics for Transportation Incident Datasets,” Proceedings of the IEEE International Conference on Information Reuse & Integration, August 2009, pp. 200–205.
  34. 34.
  35. 35.
  36. 36.
    A. Anwar, T. Nagel, and C. Ratti, “Traffic Origins: A Simple Visualization Technique to Support Traffic Incident Analysis,” Proceedings of the IEEE Pacific Visualization Symposium (PacificVis), March 2014, pp. 316–319.Google Scholar
  37. 37.
    E. Denaxas, S. Mpollas, D. Vitsios, C. Zolotas, D. G. Bleris, G. M. Spanos, and N. P. Pitsianis, “Real-time Urban Traffic Information Extraction from GPS Tracking of a Bus Fleet,” Proceedings of the IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS), April 2013, pp. 58–63.
  38. 38.
    Nokia Research. TrafficWorks. Community Enhanced Traffic. http://lumiaconversations.microsoft.com/tag/nokia-traffic-works/.
  39. 39.
    P. Chin-Hooi, S. Kalaivani, and K Radakrishnan, “Intelligent Traffic Information System for Klang Valley, Malaysia”, Proceedings of the 2008 IEEE Conference on Innovative Technologies in Intelligent Systems and Industrial Applications Multimedia University, Cyberjaya, Malaysia, July 2008, pp. 76–79.Google Scholar
  40. 40.
    Google, “Google Maps™,” Internet: https://www.google.com/maps/.
  41. 41.
    ITS Lab, “Traffy,” Internet: traffy.in.th, April 20, 2013.Google Scholar
  42. 42.
    BKKTraffic.com, “BKKTraffic.om,” Internet: bkktraffic.com, April 20, 2013.Google Scholar
  43. 43.
    Longdo, “Longdo Map,” Internet: map.longdo.com, April 20, 2013.Google Scholar
  44. 44.
    W. Andreas, W. Shangbo, G. H. Bruck, and J. Peter, “Traffic Congestion Estimation Service Exploiting Mobile Assisted Positioning Schemes in GSM Networks,” Procedia Earth and Planetary Science, 2009, pp. 1385–1392.Google Scholar
  45. 45.
    H. Guo, Z. Wang, B. Yu, H. Zhao, and X. Yuan, “TripVista: Triple Perspective Visual Trajectory Analytics and Its Application on Microscopic Traffic Data at a Road Intersection,” Proceedings of the IEEE Pacific Visualization Symposium (PacificVis), March 2011, pp. 163–170.
  46. 46.
    M. Harding, J. Finney, N. Davies, and M. Rouncefield, “Experiences with a Social Travel Information System,” Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing, September 2013, Zurich, Switzerland, pp. 173–182.Google Scholar
  47. 47.
    R-Y. Li, S. H.L. Liang, and D-W. Lee, “TrafficPulse: A Mobile GI System for Transportation,” Proceedings of the First ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, pp. 9–16.Google Scholar
  48. 48.
    B. Balázsi, O-T. Kardos, S. Ráduly, and K. Simon, “Software System for Broadcasting and Monitoring Traffic Information,” Proceedings of the IEEE 12th International Symposium on Intelligent Systems and Informatics, September 2014, Subotica, Serbia.Google Scholar
  49. 49.
  50. 50.
  51. 51.
  52. 52.
    B. Hull, V. Bychkovsky, Y. Zhang, K. Chen, M. Goraczko, A. Miu, E. Shih, H. Balakrishnan, and S. Madden, “CarTel: A Distributed Mobile Sensor Computing System,” Proceedings of the 4th International Conference on Embedded Networked Sensor Systems, pp. 125–138.Google Scholar
  53. 53.
  54. 54.
  55. 55.
  56. 56.
  57. 57.
    Y-Y. Chiang, S. Leyk, and C. A. Knoblock, “Survey of Digital Map Processing Techniques,” ACM Computing Surveys, April 2014.Google Scholar
  58. 58.
    S. Salvatore and P. Guitton, “Contour Line Recognition From Scanned Topographic Maps,” Proceedings of the Winter School of Computer Graphics, pp. 1–3.Google Scholar
  59. 59.
    A. Khotanzad and E. Zink, “Color Paper Map Segmentation Using Eigenvector Line-fitting,” Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, April 1996, pp. 190–194.Google Scholar
  60. 62.
  61. 63.
  62. 68.
    A. So, A. Stevanovic, and B. Koonce, “Estimating Performance of Traffic Signals based on Link Travel Times,” TRB Annual Meeting and publication in TR, January 2015.Google Scholar
  63. 70.
    N. Petrovska, “Software for journey planning with the public transport in Skopje”, Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS), 2010, 14th–15th October 2010 Helsinki (Kirkkonummi), Finland, pp 1–7.Google Scholar
  64. 71.
    N. Petrovska, “Multimodal Real Time Passenger Information of the Public Transport in Skopje”, ITS World Congress 2012, 22nd–26th October 2012, Vienna, Austria.Google Scholar

Copyright information

© The Author(s) 2016

Authors and Affiliations

  • Natasha Petrovska
    • 1
  • Aleksandar Stevanovic
    • 1
  • Borko Furht
    • 1
  1. 1.Florida Atlantic UniversityBoca RatonUSA

Personalised recommendations