Operational improvements in a dense and congested region can have wide-ranging and unforeseen consequences in far-flung sections of the network. These congested networks demand fine-grained, high-fidelity modeling such as microsimulation to capture the complex interactions between route choice, traffic signals, and queue spillbacks. Until now, the available tools and technology were either insufficient or exorbitantly expensive for modeling and understanding how the effects of operational improvements propagate through the network. Here we describe our methods for an affordable and robust city-wide microsimulation.

We, a collaboration of Old Dominion University and Caliper Corporation, present this case study of the City of Virginia Beach, which sought to develop and calibrate a traffic simulation model for three time periods (morning, midday, and evening) spanning the 300-plus-square-mile area of the City of Virginia Beach. The model includes all links from the Hampton Roads planning model inside of the city limits and all signalized intersections. Ultimately, the operations model was successfully calibrated to match 15-minute dynamic traffic count data gathered from the City of Virginia Beach’s traffic count databases and from the Virginia Department of Transportation’s (VDOT) Freeway Management System (FMS).

The case study is presented as a model for other municipalities contemplating city- or region-wide microsimulation as an analysis tool for the study of projects and land use developments. As part of our toolkit for the project, we applied city-wide microsimulation-based dynamic traffic assignment (DTA) and dynamic origin-destination matrix estimation (ODME). We describe how we integrate of the MPO travel demand model, city traffic signal information, city directional and turning movement count information, and state highway count information.