Using a scalable modeling and simulation framework to evaluate the benefits of intelligent transportation systems

摘要

A scalable, distributed modeling and simulation framework has been developed at Argonne National Laboratory to study Intelligent Transportation Systems. The framework can run on a single-processor workstation, or run distributed on a multiprocessor computer or network of workstations. The framework is modular and supports plug-in models, hardware, and live data sources. The initial set of models currently includes road network and traffic flow, probe and smart vehicles, traffic management centers, communications between vehicles and centers, in-vehicle navigation systems, roadway traffic sensors, incident detection algorithms, and traffic advisories. The modeling and simulation capability has been used to examine proposed ITS concepts. Results are presented from modeling scenarios from the Advanced Driver and Vehicle Advisory Navigation ConcEpt (ADVANCE) experimental program to demonstrate how the framework can be used to evaluate the benefits of ITS and to plan future ITS operational tests and deployment initiatives.