메뉴 건너뛰기




Volumn , Issue 1917, 2005, Pages 37-44

Factors affecting minimum number of probes required for reliable estimation of travel time

Author keywords

[No Author keywords available]

Indexed keywords

ESTIMATION; NUMERICAL ANALYSIS; PROBLEM SOLVING; RELIABILITY; VIRTUAL REALITY;

EID: 33645028137     PISSN: 03611981     EISSN: None     Source Type: Journal    
DOI: 10.3141/1917-05     Document Type: Conference Paper
Times cited : (31)

References (18)
  • 1
    • 0034432688 scopus 로고    scopus 로고
    • Determining the number of probe vehicles for freeway travel time estimation by microscopic simulation
    • TRB, National Research Council, Washington, D.C.
    • Chen, M. and S. I. J. Chien. Determining the Number of Probe Vehicles for Freeway Travel Time Estimation by Microscopic Simulation. In Transportation Research Record: Journal of the Transportation Research Board, No.1719, TRB, National Research Council, Washington, D.C. 2000, pp. 61-68.
    • (2000) Transportation Research Record: Journal of the Transportation Research Board, No.1719 , vol.1719 , pp. 61-68
    • Chen, M.1    Chien, S.I.J.2
  • 2
    • 0030287291 scopus 로고    scopus 로고
    • Determination of number of probe vehicles required for reliable travel time measurement in urban network
    • TRB, National Research Council, Washington D.C.
    • Srinivasan, K. K. and P. P. Jovanis. Determination of Number of Probe Vehicles Required for Reliable Travel Time Measurement in Urban Network. In Transportation Research Record 1537, TRB, National Research Council, Washington D.C. 1996, pp. 15-22.
    • (1996) Transportation Research Record , vol.1537 , pp. 15-22
    • Srinivasan, K.K.1    Jovanis, P.P.2
  • 4
    • 1942473008 scopus 로고    scopus 로고
    • Application of probe-vehicle data for real-time traffic state estimation and short-term travel-time prediction on a freeway
    • Transportation Research Board of the National Academies, Washington, D.C.
    • Nanthawichit, C. T. Nakatsuji, and H. Suzuki. Application of Probe-Vehicle Data for Real-Time Traffic State Estimation and Short-Term Travel-Time Prediction on a Freeway. In Transportation Research Record: Journal of the Transportation Research Board, No.1855, Transportation Research Board of the National Academies, Washington, D.C. 2003, pp. 49-59.
    • (2003) Transportation Research Record: Journal of the Transportation Research Board, No.1855 , vol.1855 , pp. 49-59
    • Nanthawichit, C.1    Nakatsuji, T.2    Suzuki, H.3
  • 5
    • 0036175981 scopus 로고    scopus 로고
    • Probe vehicle population and sample size for arterial speed estimation
    • Cheu, R. L. C. Xie, and D. Lee. Probe Vehicle Population and Sample Size for Arterial Speed Estimation. Computer-Aided Civil and Infrastructure Engineering, Vol. 17, No. 1, 2002, pp. 53-60.
    • (2002) Computer-Aided Civil and Infrastructure Engineering , vol.17 , Issue.1 , pp. 53-60
    • Cheu, R.L.1    Xie, C.2    Lee, D.3
  • 6
    • 3342924034 scopus 로고    scopus 로고
    • Travel time information using global positioning system and dynamic segmentation techniques
    • TRB, National Research Council, Washington, D.C.
    • Quiroga, C. A. and D. Bullock. Travel Time Information Using Global Positioning System and Dynamic Segmentation Techniques. In Transportation Research Record: Journal of the Transportation Research Board, No. 1660, TRB, National Research Council, Washington, D.C. 1999, pp. 48-57.
    • (1999) Transportation Research Record: Journal of the Transportation Research Board, No. 1660 , vol.1660 , pp. 48-57
    • Quiroga, C.A.1    Bullock, D.2
  • 7
    • 0035724797 scopus 로고    scopus 로고
    • Dynamic freeway travel-time prediction with probe vehicle data: Link based versus path based
    • TRB, National Research Council, Washington, D.C.
    • Chen, M. and S. I. J Chien. Dynamic Freeway Travel-Time Prediction with Probe Vehicle Data: Link Based versus Path Based. In Transportation Research Record: Journal of the Transportation Research Board, No. 1768, TRB, National Research Council, Washington, D.C. 2001, pp. 157-161.
    • (2001) Transportation Research Record: Journal of the Transportation Research Board, No. 1768 , vol.1768 , pp. 157-161
    • Chen, M.1    Chien, S.I.J.2
  • 10
    • 0000725993 scopus 로고    scopus 로고
    • Frequency of probe reports and variance of travel time estimates
    • Sen. A. P. Thakuriah, X. Zhu, and A. Karr. Frequency of Probe Reports and Variance of Travel Time Estimates. Journal of Transportation Engineering, Vol. 123, No. 4, 1997, pp. 290-297.
    • (1997) Journal of Transportation Engineering , vol.123 , Issue.4 , pp. 290-297
    • Sen, A.1    Thakuriah, P.2    Zhu, X.3    Karr, A.4
  • 11
    • 0033362555 scopus 로고    scopus 로고
    • Assessing expected accuracy of probe vehicle travel time reports
    • Hellinga B. and L. Fu. Assessing Expected Accuracy of Probe Vehicle Travel Time Reports. Journal of Transportation Engineering, Vol. 125, No. 6, 1999, pp. 524-530.
    • (1999) Journal of Transportation Engineering , vol.125 , Issue.6 , pp. 524-530
    • Hellinga, B.1    Fu, L.2
  • 14
    • 0345375534 scopus 로고    scopus 로고
    • Dynamic travel time prediction with real-time and historic data
    • Chien. S. and S. M. Kuchipudi. Dynamic Travel Time Prediction with Real-Time and Historic Data. Journal of Transportation Engineering, Vol. 129, No. 6, 2003, pp. 608-616.
    • (2003) Journal of Transportation Engineering , vol.129 , Issue.6 , pp. 608-616
    • Chien, S.1    Kuchipudi, S.M.2
  • 16
    • 0031472064 scopus 로고    scopus 로고
    • Traffic forecasting: Comparison of modeling approaches
    • Smith B. L. and M. J. Demetsky. Traffic Forecasting: Comparison of Modeling Approaches. Journal of Transportation Engineering, Vol. 123, No. 4, 1997, pp. 261-266.
    • (1997) Journal of Transportation Engineering , vol.123 , Issue.4 , pp. 261-266
    • Smith, B.L.1    Demetsky, M.J.2
  • 18
    • 33747425039 scopus 로고    scopus 로고
    • Estimating corridor travel time mean, variance, and covariance with intelligent transportation systems link travel time data
    • Eisele, W. S. and L. R. Rilett. Estimating Corridor Travel Time Mean, Variance, and Covariance with Intelligent Transportation Systems Link Travel Time Data. Presented at 81st Annual Meeting of the Transportation Research Board, Washington, D.C. 2002.
    • (2002) 81st Annual Meeting of the Transportation Research Board, Washington, D.C.
    • Eisele, W.S.1    Rilett, L.R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.