GIS-based dynamic traffic congestion modeling to support time-critical logistics

Abstract

Time-critical logistics (TCL) refer to time-sensitive procurement, processing and distribution activities. A confounding factor is the transportation networks that contain these logistic systems. This paper reports on a GIS-based decision support system for dynamic congestion modeling and shortest path routing in TCL. The system predicts network flow at detailed temporal resolutions and solves for the combined departure time and shortest path required for a shipment to reach its destination by a given deadline. The GIS provides effective decision support through its database management capabilities, graphical user interfaces and cartographic visualization. This supports analyses of `what-if?' scenarios regarding network disruptions.