Search System for Attractions in Thailand with Ontology and Name Matching

Main Article Content

นฤพนธ์ พนาวงศ์
จักรกฤษณ์ เสน่ห์

Abstract

- Traffic congestion has always been a serious problem for people in the big cities around the world. It causes unpleasant and unpredictable delay. Knowing the traffic condition in advance helps the drivers plan their trips wisely. Moreover, having real-time traffic information at hand, the drivers can adjust their route selections on-the-fly. This helps the drivers avoid entering the congested areas. Obviously, the traffic information plays an important role in alleviating the traffic problem. Currently, there are many methods used for collecting and distributing the traffic information. This article provides an in-depth review of these methods. In addition, the future traffic information systems and the challenges ahead will also be discussed.

Article Details

How to Cite
[1]
พนาวงศ์ น. and เสน่ห์ จ., “Search System for Attractions in Thailand with Ontology and Name Matching”, JIST, vol. 1, no. 2, pp. 60–69, Dec. 2010.
Section
Research Article: Soft Computing (Detail in Scope of Journal)

References

1. K. Balke, W. McCasland, S. Z. Levine, and C. L. Dudek, “Collection and dissemination of realtime travel time and incident information with in-vehicle communication technologies,” Proc. IEEE Vehicle Navigation and Info. Sys. Conf. (VNIS), Dearborn, Oct. 1991, pp. 77–82.

2. R. D. Huchingson, R. W. Mcnees, and C. L. Dudek, “Survey of motorist route selection criteria,” Transportation Research Record, vol. 643, pp. 45-48, 1977.

3. E. Sharazi, S. Anderson, and J. Stesney, Presentation, the 67th Annual Meeting of the Transportation Research Board, 1988.

4. M. Haselkorn, J. Spyridakis, L. Conquest, and W. Barfield, “Surveying commuter behavior as a basis for designing motorist information systems,” Proc. IEEE Vehicle Navigation and Info. Sys. Conf. (VNIS), Toronto, Sep. 1989, pp. 93–100.

5. G. Peersman, P. G. H. Spear, S. Cvetkovic, and C. Smythe, “A tutorial overview of the short message service within GSM,” Computing and Control Engineering Journal, vol. 11, pp. 79–89, April 2000.

6. J. Sevanto, “Multimedia messaging service for GPRS and UMTS,” Proc. IEEE Wireless Comm. and Networking Conf. (WCNC), Sep. 1999, pp. 1422–1426.

7. R. L. Anderson, “Electromagnetic loop vehicle detectors,” IEEE Trans. Vehicular Technology, vol. 19, pp. 23–30, February 1970.

8. C. Sun and S. G. Ritchie, “Individual vehicle speed estimation using single loop inductive waveforms,” California PATH Working Paper UCB-ITS-PWP-99-14, Oct. 1999.

9. D. L. Woods, B. P. Cronin, and R. A. Hamm, “Speed measurement with inductance loop speed traps,” Texas Transportation Institute Research Report FHWA/TX-95/1392-8, 1994.

10. I. Sreedevi, “Loop detectors,” [Online], 2005, available: http://www.calccit.org/itsdecision/serv_and_tech/Traffic_Surveillance/road-based/inroad/loop_summary.html

11. Y. Wakabayashi and M. Aoki, “Traffic flow measurement using stereo slit camera,” Proc. IEEE Intelligent Transportation Sys. Conf., Vienna, Sep. 2005, pp. 198–203.

12. S. Santini, “Analysis of traffic flow in urban areas using web cameras,” Proc. Workshop on Applications of Computer Vision, Palm Springs, Dec. 2000, pp. 140–145.

13. X. Yu, L. Duan, and Q. Tian, “Highway traffic information extraction from skycam MPEG video,” Proc. IEEE Intelligent Transportation Sys. Conf., Singapore, Sep. 2002, pp. 37–41.

14. T. N. Schoepflin and D. J. Dailey, “Dynamic camera calibration of roadside traffic management cameras for vehicle speed estimation,” IEEE Trans. Intelligent Transportation Sys., vol. 4, pp. 90–98, June 2003.

15. C. Li, K. Ikeuchi, and M. Sakauchi, “Acquisition of traffic information using a video camera with 2D spatio-temporal image transformation technique,” Proc. IEEE Intelligent Transportation Sys. Conf., Tokyo, Oct. 1999, pp. 634–638.

16. D. Douxchamps, B. Macq, and K. Chihara, “High accuracy traffic monitoring using roadside line-scan cameras,” Proc. IEEE Intelligent Transportation Sys. Conf., Toronto, Sep. 2006, pp. 875–878.

17. G. T. Kogut and M. M. Trivedi, “Maintaining the identity of multiple vehicles as they travel through a video network,” Proc. IEEE Workshop on Multi-Object Tracking, Vancouver, Jul. 2001, pp. 29–34.

18. T. Hasegawa, K. Imamura, and H. Zen, “Observation of moving vehicles by the plural cameras established freely,” Proc. IEEE Intelligent Transportation Sys. Conf., Dearborn, Oct. 2000, pp. 328–333.

19. Y. Wu, F. Lian, and T. Chang, “Traffic monitoring and vehicle tracking using roadside cameras,” Proc. IEEE International Conf. on Systems, Man, and Cybernatics (ICSMC), Taipei, Oct. 2006, pp. 4631–4636.

20. P. G. Michalopoulos, “Vehicle detection video through image processing: The autoscope system,” IEEE Trans. Vehicular Technology, vol. 40, pp. 21–29, February 1991.

21. A. Lai and N. Yung, “Vehicle-type identification through automated virtual loop assignment and block-based direction-biased motion estimation,” IEEE Trans. Intelligent Transportation Sys., vol. 1, pp. 86–97, June 2000.

22. M. S. Couto, J. L. Monteiro, and J. A. Santos, “Improving virtual loop sensor accuracy for 2D motion detection,” Proc. IEEE World Automation Congress, Orlando, Jun. 2002, pp. 365–370.

23. W. Wang, W. Lei, and H. Mizuta, “Probe car system based traffic information service experiment,” Proc. IEEE Intelligent Transportation Sys. Conf., Toronto, Sep. 2006, pp. 1134–1136.

24. M. Hu, Y. Wang, and Q. Shi, “Developing Beijing traveler information systems framework,” Proc. IEEE Intelligent Transportation Sys. Conf., Singapore, Sep. 2002, pp. 381–386.

25. X. Xia, Z.Niu, and W. Wang, “Concept and deployment of internet ITS,” Proc. IEEE Intelligent Transportation Sys. Conf., Washington DC, Oct. 2004, pp. 939–944.

26. X. Dai, M. Ferman, and P. Roesser, “A simulation evaluation of a real-time traffic information system using probe vehicles,” Proc. IEEE Intelligent Transportation Sys. Conf., Shanghai, Oct. 2003, pp. 475–480.

27. M. Chen and S. Chien, “Dynamic freeway travel time prediction using probe vehicle data: Link based versus path based,” Transportation Research Record, vol. 1768, pp. 157–161, 2001.

28. L. Wang, C. Wang, X. Shen, and Y. Fan, “Probe vehicle sampling for real-time traffic data collection,” Proc. IEEE Intelligent Transportation Sys. Conf., Vienna, Sep. 2005, pp. 886–888.

29. S. Turner and D. Holdener, “Probe vehicle sample sizes for real-time information: The Houston experience,” Proc. IEEE Vehicle Navigation and Info. Sys. Conf. (VNIS), Seattle, Jul. 1995, pp. 3–10.

30. R. Cheu, C. Xie, and D. Lee, “Probe vehicle population and sample size for arterial speed estimation,” Computer-Aided Civil and Infrastructure Engineering, vol. 17, pp. 53–60, January 2002.

31. J. Ivan and V. Sethi, “Data fusion of fixed detector and probe vehicle data for incident detection,” Computer-Aided Civil and Infrastructure Engineering, vol. 13, pp. 329–337, September 1998.

32. E. A. Bretz, “X marks the spot, maybe [GPS avigation],” IEEE Spectrum, vol. 37, pp. 26–36, April 2000.

33 R. L. Bertini and S. Tantiyanugulchai, “Transit buses as traffic probes: Empirical evaluation using geo-location data,” Transportation Research Record, vol. 1870, pp. 35–45, 2005.

34. S. Tantiyanugulchai and R. L. Bertini, “Analysis of a transit bus as a probe vehicle for arterial performance measurement,” Institute of Transportation Engineers 2003 Annual Meeting, Seattle, 2003.

35. D. Boyce, N. Rouphail, and A. Kirson, “Estimation and measurement of link travel times in the ADVANCE project,” Proc. IEEE Vehicle Navigation and Info. Sys. Conf. (VNIS), New York, Oct. 1993, pp. 62–66.

36. D. J. Dailey, “Travel-time estimation using cross-correlation techniques,” Transportation Research Part B, vol. 27, pp. 97–107, April 1993.

37. J. Anderson, M. Bell, T. Sayers, F. Bush, and G. Heyman, “The short-term prediction of link travel times in signal controlled road networks,” Transportation Systems: Theory and Application of Advanced Technology, IFAC Symp., Aug. 1994, pp. 621–626.

38. V. Blue, G. F. List, and M. J. Embrechts, “Neural network freeway travel time estimation,” Proc. Intelligent Engineering Sys. Through Artificial Neural Networks, 1994, pp. 1135–1140.

39. V. P. Sisiopiku and N. M. Rouphail, “Toward the use of detector output for arterial link travel time estimation: A literature review,” Transportation Research Record, vol. 1457, pp. 158–165, 1995.

40. B. H. Meehan, “Travel times on dynamic message signs,” Institute of Transportation Engineers Journal, vol. 75, pp. 23–27, September 2005.

41. M. Conti and S. Giordano, “Multihop ad hoc networking: The reality,” IEEE Comm. Mag., vol. 45, pp. 88–95, April 2007.

42. E. M. Royer and C.-K. Toh, “A review of current routing protocols for ad hoc mobile wireless networks,” IEEE Personal Comm., vol. 6, pp. 46–55, April 1999.

43. R. Jurdak, C. V. Lopes, and P. Baldi, “A survey, classification and comparative analysis of medium access control protocols for ad hoc networks,” IEEE Comm. Surveys and Tutorials, vol. 6, pp. 2–16, First Quarter 2004.

44. B. Williams and T. Camp, “Comparison of broadcasting techniques for mobile ad hoc networks,” Proc. ACM International Symp. on Mobile Ad Hoc Networking and Computing (MOBIHOC), Lausanne, Jun. 2002, pp. 194–205.

45. S. Ni, Y. Tseng, Y. Chen, and J. Sheu, “The broadcast storm problem in a mobile ad hoc network,” Proc. ACM International Conf. on Mobile Computing and Networking (MOBICOM), Seattle, Aug. 1999, pp. 151–162.

46. J. Zhu and S. Roy, “MAC for dedicated short range communications in intelligent transport system,” IEEE Comm. Mag., vol. 41, pp. 60–67, December 2003.

47. H. Menouar, F. Filali, and M. Lenardi, “A survey and qualitative analysis of MAC protocols for vehicular ad hoc networks,” IEEE Wireless Comm., vol. 13, pp. 30–35, October 2006.

48. X. Yang and W. Recker, “Simulation studies of information propagation in a self-organizing distributed traffic information system,” Transportation Research Part C, vol. 13, pp. 370–390, October 2005.

49. L. Wischhof, A. Ebner, and H. Rohling, “Information dissemination in self-organizing intervehicle networks,” IEEE Trans. Intelligent Transportation Sys., vol. 6, pp. 90–101, March 2005.