POLARIS: Agent-based modeling framework development and implementation for integrated travel demand and network and operations simulations

J Auld, M Hope, H Ley, V Sokolov, B Xu… - … Research Part C …, 2016 - Elsevier
J Auld, M Hope, H Ley, V Sokolov, B Xu, K Zhang
Transportation Research Part C: Emerging Technologies, 2016Elsevier
This paper discusses the development of an agent-based modeling software development
kit, and the implementation and validation of a model using it that integrates dynamic
simulation of travel demand, network supply and network operations. A description is given
of the core utilities in the kit: a parallel discrete event engine, interprocess exchange engine,
and memory allocator, as well as a number of ancillary utilities: visualization library,
database IO library, and scenario manager. The overall framework emphasizes the design …
Abstract
This paper discusses the development of an agent-based modeling software development kit, and the implementation and validation of a model using it that integrates dynamic simulation of travel demand, network supply and network operations. A description is given of the core utilities in the kit: a parallel discrete event engine, interprocess exchange engine, and memory allocator, as well as a number of ancillary utilities: visualization library, database IO library, and scenario manager. The overall framework emphasizes the design goals of: generality, code agility, and high performance. This framework allows the modeling of several aspects of transportation system that are typically done with separate stand-alone software applications, in a high-performance and extensible manner. The issue of integrating such models as dynamic traffic assignment and disaggregate demand models has been a long standing issue for transportation modelers. The integrated approach shows a possible way to resolve this difficulty. The simulation model built from the POLARIS framework is a single, shared-memory process for handling all aspects of the integrated urban simulation. The resulting gains in computational efficiency and performance allow planning models to be extended to include previously separate aspects of the urban system, enhancing the utility of such models from the planning perspective. Initial tests with case studies involving traffic management center impacts on various network events such as accidents show the potential of the system.
Elsevier
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