Traffic congestion is a serious socio-economic problem causing environmental expense and nation's resource waste. To resolve traffic congestion, management of the existing traffic network is the most effective and important way for policy makers. Understanding the current traffic condition should precede the proper management, and Speed-Flow-Density diagram is useful to investigate it. This research investigates the current status of network through the queueing process which is very useful to explain the stochastic phenomena of traffic. Dynamic structure in the stochastic process enables us to reflect the structural change of the network condition in traffic congestion. We specify queueing model with structural change by nonlinear optimization method to find the best suitable model and estimate parameters of interest. With the optimized results, we develop network performance indices in terms of congestion and travel time, and evaluate the network efficiency in view of marginal congestion cost.
Bibliography:
Dewees, D. N. (1979). Estimating the time costs of highway congestion, Econometrica, 47 (6), 1499-1512.
Park, Y. S. and Jeon, S. B. (2010). A study on the queueing process with dynamic structure for speed-flow-density diagram, The Korean Journal of Applied Statistics, 23 (6), 1-12.
Theil, H. (1966). Applied Economic Forecasting, North-Holland, Amsterdam.
Vandaele, N., Van Woensel, T. and Verbruggen, A. (2000). A queueing based traffic flow model, Transportation Research D, 5, 121-135.
Van Woensel, T. and Vandaele, N. (2006). Empirical validation of a queueing approach to uninterrupted traffic flows, A Quarterly Journal of Operations Research, 4(1), 59-72.
Van Woensel T. and Cruz F. R. B. (2009), A Stochastic Approach to Traffic Congestion Costs, Computers and Operations Research, 36(6), 1731-1739.
Keywords: Queueing; Structural change; Congestion index; Congestion cost
Biography: Saebom Jeon, a Ph.D in Statistics since 2010, now works for Institute of Statistics, Korea University as a Research Professor.