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Volumn 138, Issue 8, 2012, Pages 1030-1039

Time series analysis and models of freeway performance

Author keywords

Computer simulation; Forecasting; Markov processes; Probability density; State space models; Statistical methods; Traffic congestion; Traffic surveys

Indexed keywords

COMPUTER SIMULATION; FORECASTING; MARKOV PROCESSES; PROBABILITY DENSITY FUNCTION; STATE SPACE METHODS; STATISTICAL METHODS; TIME SERIES ANALYSIS; TRAFFIC SURVEYS;

EID: 84876729994     PISSN: 0733947X     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)TE.1943-5436.0000403     Document Type: Article
Times cited : (11)

References (16)
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  • 3
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    • Implementing the concept of reliability for highway capacity analysis
    • Transportation Research Board, Washington, DC
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    • Brilon, W.1    Geistefeldt, J.2    Zurlinden, H.3
  • 6
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    • Systematic identification of freeway bottlenecks
    • Transportation Research Board, Washington, DC
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    • Chen, C.1    Skabardonis, A.2    Varaiya, P.3
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    • Gerlough, D.L.1    Huber, M.J.2
  • 9
    • 33846405260 scopus 로고    scopus 로고
    • Estimating the effects of traffic congestion on fuel consumption and vehicle emissions based on acceleration noise
    • Greenwood, I. D., Dunn, R. C. M., and Raine, R. R. (2007). "Estimating the effects of traffic congestion on fuel consumption and vehicle emissions based on acceleration noise." J. Transp. Eng., 133(2), 96-104.
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    • Beanplot: A boxplot alternative for visual comparison of distributions
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    • Freeway traffic flow rate measurement: Investigation into impact of measurement time interval
    • Smith, B. L, and Ulmer, J. M. (2003). "Freeway traffic flow rate measurement: Investigation into impact of measurement time interval." J. Transp. Eng., 129(3), 223-229.
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  • 15
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    • Modeling and forecasting vehicular traffic flow as a seasonal ARIMA process: Theoretical basis and empirical results
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.