Developing a large-scale hybrid simulation model: Lessons learned

Stephen Zitzow, Derek Lehrke, John Hourdos

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Long-term, regional travel demand models are essential tools used by planning organizations for resource management, project scheduling, and impact studies. Developed primarily at the macroscopic level, these tools lack sufficient detail to capture the influence of local geometry, dynamic traffic controls, or advanced transportation demand management strategies. To bridge the gap, a hybrid mesoscopic-microscopic model was developed. The core of the model, surrounding two light rail corridors in Minneapolis-Saint Paul, Minnesota (the Twin Cities), was developed at high resolution for microscopic simulation to capture the interaction between traffic signals, transit systems, and the road network. The remainder of the greater Twin Cities area was implemented according to the regional planning model (RPM) maintained by the Metropolitan Council. Interfacing the AIMSUN-based hybrid model with the CUBE-based RPM, the Twin Cities metro hybrid simulation was used to improve mode choice and traffic assignment iteratively to achieve a dynamic user equilibrium state. Significant lessons were learned about the effort needed to develop and to maintain such a model, with implications for future large-scale regional modeling.

Original languageEnglish (US)
Pages (from-to)107-116
Number of pages10
JournalTransportation Research Record
Volume2491
DOIs
StatePublished - Jan 1 2015

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