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Volumn 13, Issue 2, 2009, Pages 73-84

Enhancing predictions in signalized arterials with information on short-term traffic flow dynamics

Author keywords

Neural Networks; Pattern based Prediction; Short term Prediction; Traffic Flow

Indexed keywords

INTELLIGENT TRANSPORTATION SYSTEMS; PATTERN-BASED PREDICTION; PREDICTION SCHEMES; PREDICTION TECHNIQUES; SHORT-TERM PREDICTION; SHORT-TERM TRAFFIC FLOW; TRAFFIC DYNAMICS; TRAFFIC FLOW;

EID: 70349501971     PISSN: 15472450     EISSN: 15472442     Source Type: Journal    
DOI: 10.1080/15472450902858384     Document Type: Article
Times cited : (52)

References (46)
  • 4
    • 0001528567 scopus 로고
    • Predicting intersection queue with neural network models
    • Chang, G.-L., and Su, C.-C. (1995). Predicting intersection queue with neural network models. Transportation Research Part C, 3(3), 175-191.
    • (1995) Transportation Research Part C , vol.3 , Issue.3 , pp. 175-191
    • Chang, G.-L.1    Su, C.-C.2
  • 5
    • 0035567818 scopus 로고    scopus 로고
    • A study of hybrid neural network approaches and the effects ofmissing data on traffic forecasting
    • Chen,H.,Grant-Muller S.Mussone,L., andMontgomery, F.(2001).A study of hybrid neural network approaches and the effects ofmissing data on traffic forecasting. Neural Computing and Applications, 10,277-286.
    • (2001) Neural Computing and Applications , vol.10 , pp. 277-286
    • Chen, H.1    Grant-Muller, S.2    Mussone, L.3    Montgomery, F.4
  • 7
    • 0001845905 scopus 로고
    • ATHENA: A method for short-term inter-urban motorway traffic forecasting
    • Danech-Pajouh, M., and Aron, M. (1991). ATHENA: A method for short-term inter-urban motorway traffic forecasting. Recherche Transport Securite, 6, 11-16.
    • (1991) Recherche Transport Securite , vol.6 , pp. 11-16
    • Danech-Pajouh, M.1    Aron, M.2
  • 8
    • 0029485810 scopus 로고
    • Areviewof neural networks applied to transport
    • Dougherty, M. (1995).Areviewof neural networks applied to transport. Transportation Research Part C, 3(4), 247-260.
    • (1995) Transportation Research Part C , vol.3 , Issue.4 , pp. 247-260
    • Dougherty, M.1
  • 10
    • 0034701731 scopus 로고    scopus 로고
    • On the structures and quantification of recurrence plots
    • Gao, J., and Cai, H. (2000). On the structures and quantification of recurrence plots. Physics Letters A, 270, 75-87.
    • (2000) Physics Letters A , vol.270 , pp. 75-87
    • Gao, J.1    Cai, H.2
  • 11
    • 41849117283 scopus 로고    scopus 로고
    • Real-time vehicle reidentification and performance measures on signalized arterials
    • September 17-20, Toronto, ON, Canada. MA7
    • Geroliminis, N., and Skabardonis, A. (2006). Real-time vehicle reidentification and performance measures on signalized arterials. 9th International IEEE Conference on Intelligent Transportation Systems, September 17-20, Toronto, ON, Canada. MA7. 3, 188-193.
    • (2006) 9th International IEEE Conference on Intelligent Transportation Systems , vol.3 , pp. 188-193
    • Geroliminis, N.1    Skabardonis, A.2
  • 12
    • 0002146970 scopus 로고
    • Synthesis of recent work on the nature of speed-flow and flow-occupancy (or density) relationships on freeways
    • Hall, F. L., Hurdle, V. F., and Banks, J. H. 1992. Synthesis of recent work on the nature of speed-flow and flow-occupancy (or density) relationships on freeways. Transportation Research Record, 1365, 12-18.
    • (1992) Transportation Research Record , vol.1365 , pp. 12-18
    • Hall, F.L.1    Hurdle, V.F.2    Banks, J.H.3
  • 13
    • 0029332532 scopus 로고
    • Event-based short-term traffic flow prediction model
    • Head, L. K. (1995). Event-based short-term traffic flow prediction model. Transportation Research Board, 1510, 45-52.
    • (1995) Transportation Research Board , vol.1510 , pp. 45-52
    • Head, L.K.1
  • 14
    • 0027884516 scopus 로고
    • Dynamic traffic pattern classification using artificial neural networks
    • Hua, J., and Faghri, A. (1993). Dynamic traffic pattern classification using artificial neural networks. Transportation Research Record, 1399, 14-19.
    • (1993) Transportation Research Record , vol.1399 , pp. 14-19
    • Hua, J.1    Faghri, A.2
  • 15
    • 3242676259 scopus 로고    scopus 로고
    • Optimizing traffic prediction performance of neural networks under various topological, input and traffic condition settings
    • Ishak, S., and Alecsandru, C. (2004). Optimizing traffic prediction performance of neural networks under various topological, input and traffic condition settings. Journal of Transportation Engineering, 130(4), 452-465.
    • (2004) Journal of Transportation Engineering , vol.130 , Issue.4 , pp. 452-465
    • Ishak, S.1    Alecsandru, C.2
  • 16
    • 26444571471 scopus 로고    scopus 로고
    • Dynamicwavelet neural network model for traffic flow forecasting
    • Jiang, X., and Adeli, H. (2005).Dynamicwavelet neural network model for traffic flow forecasting. Journal of Transportation Engineering, 13(10), 771-779.
    • (2005) Journal of Transportation Engineering , vol.13 , Issue.10 , pp. 771-779
    • Jiang, X.1    Adeli, H.2
  • 19
    • 0346009319 scopus 로고    scopus 로고
    • Three-phase traffic theory and highway capacity
    • Kerner, B. S. (2004). Three-phase traffic theory and highway capacity. Physica A, 333, 379-440.
    • (2004) Physica A , vol.333 , pp. 379-440
    • Kerner, B.S.1
  • 22
    • 33846338227 scopus 로고    scopus 로고
    • Recurrence plots for the analysis of complex systems
    • Marwan, N., Romano, M. C., Thiel, M., and Kurths, J. (2007). Recurrence plots for the analysis of complex systems. Physics Reports, 438(5-6), 237-329.
    • (2007) Physics Reports , vol.438 , Issue.5-6 , pp. 237-329
    • Marwan, N.1    Romano, M.C.2    Thiel, M.3    Kurths, J.4
  • 24
    • 43949166728 scopus 로고
    • A simplified theory of kinematic waves in highway traffic. II: Queueing at freeway bottlenecks
    • Newell, G. F. (1992). A simplified theory of kinematic waves in highway traffic. II: Queueing at freeway bottlenecks. Transportation Research. Part B: Methodological, 27, 281-313.
    • (1992) Transportation Research. Part B: Methodological , vol.27 , pp. 281-313
    • Newell, G.F.1
  • 27
    • 0035501669 scopus 로고    scopus 로고
    • Intelligent simulation and prediction of vehicle platoon dispersion
    • Qiao, F.,Yang, H., and Lam,W. H. K. (2001). Intelligent simulation and prediction of vehicle platoon dispersion. Transportation Research B:Methodological, 35(9), 843-863.
    • (2001) Transportation Research B:Methodological , vol.35 , Issue.9 , pp. 843-863
    • Qiao, F.1    Yang, H.2    Lam, W.H.K.3
  • 29
    • 0038034269 scopus 로고    scopus 로고
    • Meeting real-time requirements with imprecise computations:Acase study in traffic flowforecasting
    • Smith,B. L., andOswald, R. K. (2003).Meeting real-time requirements with imprecise computations:Acase study in traffic flowforecasting. Computer Aided Civil and Infrastructure Engineering, 18, 201-213.
    • (2003) Computer Aided Civil and Infrastructure Engineering , vol.18 , pp. 201-213
    • Smithb., L.1    Oswald, R.K.2
  • 31
    • 0037954189 scopus 로고    scopus 로고
    • A multivariate statespace approach for urban traffic flow modeling and prediction
    • Stathopoulos, A., and Karlaftis, M. G. (2003a). A multivariate statespace approach for urban traffic flow modeling and prediction. Transportation Research Part C, 11(2), 121-135.
    • (2003) Transportation Research Part C , vol.11 , Issue.2 , pp. 121-135
    • Stathopoulos, A.1    Karlaftis, M.G.2
  • 33
    • 0030298951 scopus 로고    scopus 로고
    • Combining Kohonen maps with ARIMA time-series models to forecast traffic flow
    • Van Der Voort, M., Dougherty, M., and Watson, S. (1996). Combining Kohonen maps with ARIMA time-series models to forecast traffic flow. Transportation Research, Part C, 4(5), 307-318.
    • (1996) Transportation Research, Part C , vol.4 , Issue.5 , pp. 307-318
    • Van Der Voort, M.1    Dougherty, M.2    Watson, S.3
  • 35
    • 4444369422 scopus 로고    scopus 로고
    • Short-term traffic forecasting: Overview of objectives and methods
    • Vlahogianni, E. I., Golias, J. C., and Karlaftis,M.G. (2004). Short-term traffic forecasting: Overview of objectives and methods. Transport Reviews, 24(5), 533-557.
    • (2004) Transport Reviews , vol.24 , Issue.5 , pp. 533-557
    • Vlahogianni, E.I.1    Golias, J.C.2    Karlaftis, M.G.3
  • 36
    • 23844513726 scopus 로고    scopus 로고
    • Optimized and meta-optimized neural networks for short-term traffic flow modeling: A genetic approach
    • Vlahogianni, E. I., Kalaftis, M. G., and Golias, J. C., (2005). Optimized and meta-optimized neural networks for short-term traffic flow modeling: A genetic approach. Transportation Research Part C: Emerging Technologies, 13(3), 211-234.
    • (2005) Transportation Research Part C: Emerging Technologies , vol.13 , Issue.3 , pp. 211-234
    • Vlahogianni, E.I.1    Kalaftis, M.G.2    Golias, J.C.3
  • 37
    • 34249317652 scopus 로고    scopus 로고
    • Spatiotemporal short-term urban traffic volume forecasting using genetically optimized modular networks
    • Vlahogianni, E. I., Kalaftis, M. G., and Golias, J. C. (2007a). Spatiotemporal short-term urban traffic volume forecasting using genetically optimized modular networks, Computer-Aided Civil and Infrastructure Engineering, 22(5), 317-325.
    • (2007) Computer-Aided Civil and Infrastructure Engineering , vol.22 , Issue.5 , pp. 317-325
    • Vlahogianni, E.I.1    Kalaftis, M.G.2    Golias, J.C.3
  • 38
    • 33750338259 scopus 로고    scopus 로고
    • Statistical methods for detecting nonlinearity and non-stationarity in univariate short-term time-series of traffic volume
    • Vlahogianni, E. I., Karlaftis,M. G., and Golias, J. C. (2006). Statistical methods for detecting nonlinearity and non-stationarity in univariate short-term time-series of traffic volume. Transportation Research Part C: Emerging Technologies, 14(5), 351-367.
    • (2006) Transportation Research Part C: Emerging Technologies , vol.14 , Issue.5 , pp. 351-367
    • Vlahogianni, E.I.1    Karlaftism., G.2    Golias, J.C.3
  • 41
    • 0035563672 scopus 로고    scopus 로고
    • Multivariate vehicular traffic flow prediction: An evaluation ofARIMAXmodelling
    • Williams, B. M. (2001). Multivariate vehicular traffic flow prediction: an evaluation ofARIMAXmodelling. Transportation Research Record, 1776, 194-200.
    • (2001) Transportation Research Record , vol.1776 , pp. 194-200
    • Williams, B.M.1
  • 42
    • 33746860294 scopus 로고    scopus 로고
    • A wavelet network model for shortterm traffic volume forecasting
    • Xie, Y. C., and Zhang, Y. L. (2006). A wavelet network model for shortterm traffic volume forecasting. Journal of Intelligent Transportation Systems, 10(3), 141-150.
    • (2006) Journal of Intelligent Transportation Systems , vol.10 , Issue.3 , pp. 141-150
    • Xie, Y.C.1    Zhang, Y.L.2
  • 43
    • 0003948591 scopus 로고    scopus 로고
    • Evolutionary computation: Theory and applications
    • Yao, X. (1999). Evolutionary computation: Theory and applications. World Scientific.
    • (1999) World Scientific
    • Yao, X.1
  • 46
    • 0042639046 scopus 로고    scopus 로고
    • Detecting deterministic signals in exceptionally noisy environments using cross-recurrence quantification
    • Zbilut, P., Giuliani, A., and Webber, C. L. Jr. (1998). Detecting deterministic signals in exceptionally noisy environments using cross-recurrence quantification. Physics Letters A, 246(1-2), 122-128.
    • (1998) Physics Letters A , vol.246 , Issue.1-2 , pp. 122-128
    • Zbilut, P.1    Giuliani, A.2    Webber Jr., C.L.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.