Mesoscopic-Wavelet Freeway Work Zone Flow and Congestion Feature Extraction Model-Reference-Cited by-同舟云学术

Mesoscopic-Wavelet Freeway Work Zone Flow and Congestion Feature Extraction Model

Published:2004-01 Issue:1 Volume:130 Page:94-103
ISSN:0733-947X
Container-title:Journal of Transportation Engineering
language:en
Short-container-title:J. Transp. Eng.

Author:

Adeli Hojjat¹,Ghosh-Dastidar Samanwoy²

Affiliation:

1. Professor, Dept. of Civil and Environmental Engineering and Geodetic Science, The Ohio State Univ., 2070 Neil Ave., Columbus, OH 43210-1275.

2. Graduate Student, Dept. of Civil and Environmental Engineering and Geodetic Science, The Ohio State Univ., 470 Hitchcock Hall, 2070 Neil Ave., Columbus, OH 43210-1275.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%290733-947X%282004%29130%3A1%2894%29

Reference43 articles.

1. Adeli H. and Samant A. (2000). “An adaptive conjugate gradient neural network-wavelet model for traffic incident detection.” Computer-aided civil and infrastructure engineering Vol. 15 No. 4 251–260.

2. Ahmed K. Ben-Akiva M. Koutsopoulos H. N. and Mishalani R. G. (1996). “Models for Freeway Lane Changing and Gap Acceptance Behavior.” Proc. 13th Int. Symp. on Transportation and Traffic Theory Lyon France.

3. Dynamical model of traffic congestion and numerical simulation

4. Continuum approach to car-following models

5. Berg P. and Woods A. (1999). “Relating car-following and continuum models of road traffic ” Traffic and granular flow D. Helbing H. J. Herrmann M. Schreckenberg and D. E. Wolf eds. Springer New York 389–394.

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