Discrete event simulation experiments and geographic information systems in congestion management planning

Abstract

regional transportation system and the movement of large traffic volumes through it, are characteristic of stochastic systems. The standard traffic management or transportation planning approach uses a slice in time view of the system. Static, mean values of system variables are used for the basis of incident-caused, congestion management decisions. By reason of the highly variable nature of transportation systems, discrete event simulation is used in the planning process. The simulation model is highly dependent on the spatial accuracy of real world coordinates of nodes and the lengths of the roadway network links. Link travel times, queue spill back and turn lane queue size are directly related to the magnitude of incident-caused congestion, and the roadway system's ability to recover from it. The incorporation of accurate geographic information system (GIS) data with a powerful transportation simulation software package and properly designed data collection and analysis techniques are invaluable in support of transportation incident management decisions.