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This report is an archived publication and may contain dated technical, contact, and link information
Publication Number:  FHWA-HRT-13-036    Date:  August 2013
Publication Number: FHWA-HRT-13-036
Date: August 2013


The Effective Integration of Analysis, Modeling, and Simulation Tools


This report describes a prototype of an open-source data hub that enables the exchange of data among multiple resolutions of analysis, modeling, and simulation (AMS) tools (referred to as the AMS data hub). The AMS data hub is a system of components consisting of network editing, calibration, and visualization tools for transportation modeling applications.

A key feature of the AMS data hub is a data schema designed to provide a consistent and easily accessible format for storing common modeling data across multiple resolutions. With support and buy-in from the modeling community, the data schema can evolve into a relational or object-oriented database to further enhance the ability to exchange data across resolutions and AMS tools.

The research team tested the AMS data hub prototype for an arterial network in Portland, OR, and a freeway network in Tucson, AZ. Results from the test applications show that the AMS data hub achieved the project goal of enabling the harmonious exchange of model data along with significant time savings.

Figure 1 summarizes the relationship comprising the AMS data hub that was carried out in the test applications.

This diagram summarizes the relationship comprising the analysis, modeling, and simulation (AMS) data hub, which was carried out in the test applications. The AMS data hub plus Network EXplorer for Traffic Analysis utility is at the center of a series of information flows. Elements that only feed into the AMS data hub include the travel demand model (TransCADTM, CubeTM, and PTV Visum®) and field data traffic counts, speeds, and travel times. Elements that flow into the the AMS data hub and receive information back from it include the dynamic traffic assignment (DTA) engines (refined operations and demand, origin-destination matrix estimation (ODME), and refining tools) and Synchro® signal optimization prep and import/export. Elements that only receive information from the AMS data hub include Google® visualization tools (Google Earth® and Google Maps®) and the microscopic export to PTV Visum® (for detailed operations analysis).
Figure 1. Illustration. Data flows and component diagram for AMS data hub.

Specific benefits of the AMS data hub include the following:

Results from the test application show significant time savings by using the AMS data hub compared to traditional ad hoc/manual methods. The most significant time savings are associated with network import functionality, creation of subarea origin-destination (O-D) matrices, automatic generation of signal timing for planning networks, and link volume calibration.

Table 1 summarizes the travel savings by component based on the results of the test applications, which reflect an 80 percent time savings.

Table 1. Estimated time saving from AMS data hub.


Without AMS Data Hub

With AMS Data Hub

Network import—Export, edit, and import network

8–10 h

1–2 h

Intersection control inference—Edit control type for all nodes

6–8 h

4–6 h

Subarea O-D matrices—Aggregate path flows at boundary

8–16 h

< 0.5 h

Convert connectors to side streets—Add new nodes, delete links, etc.

1–2 h

< 0.5 h

Signal timing with the quick estimation method (QEM)—Initial timings for intersections

6–8 h

< 0.5 h

ODME—Prepare field data and running ODME

6–8 h

2–3 h


35–52 h

7–11 h

Both the concept and interim tool demonstrations have been well received by the Portland Metro and Pima Association of Governments (PAG), which are the respective model agencies for the test applications. Portland Metro, in particular, has faced challenges with cross resolution modeling between macroscopic and mesoscopic tools. Their insights and requests, along with those of other professionals, have shaped the tools and functionality of the proof of concept AMS data hub tool. For example, Portland Metro expressed a strong desire to generate realistic signal timing plans and import them into the data hub (using Synchro®) for use with DTA. Portland Metro views signal timing as a key component to improving the realism of traffic assignments and results from DTA.

While this report discusses the integration of the AMS data hub for specific software tools to cross resolutions, the hub is intended to be an open source and customizable to support a wide variety of software tools. This is not an endorsement or recommendation of the specific software tools linked through this proof of concept, but rather a realistic test case for transferring data to support representative transportation analysis needs.

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