The Effective Integration of Analysis, Modeling, and Simulation Tools

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FOREWORD

Simulation models used in transportation analysis are not well integrated among different domains (e.g., operations, safety, and environment) and for different levels of analysis (i.e., macro, meso, and micro). This project developed a prototype data hub and data schema using the Network EXplorer for Traffic Analysis (NeXTA) open-source software tool to save users time to input data and to model and display results in a common format. Researchers tested the newly developed model integration approach to address real-world transportation planning, operations, and management problems and demonstrated the approach to transportation planners at Portland Metro and Pima Association of Governments. The test applications validated the open-source data hub functionality by taking existing regional travel demand models from the respective regions, exporting the data to a dynamic traffic assignment model for mesoscopic analysis, exporting to a signal timing optimization tool, and then exporting to a microscopic simulation tool for detailed operations analysis. Preliminary results showed that the data hub prototype overcame many shortcomings associated with integrated modeling applications. The analyses took only 7 to 11 h to complete with the data hub in comparison to 35 to 52 h without the data hub, which is a total time savings of 80 percent. This report documents the findings and recommendations from the research, and it is aimed at model users, managers at modeling agencies, software developers, and researchers who are interested in advancing integrated modeling practices.

Joseph I. Peters
Director, Office of Operations
Research and Development

TECHNICAL REPORT DOCUMENTATION PAGE

SI* (Modern Metric) Conversion Factors

TABLE OF CONTENTS

• Executive Summary
  
  
• Introduction
  • Characteristics of Effective Integration
  • Market Demand for Integration Tools
    
    
• Multi-Resolution AMS Tool Integration
  • Introduction
  • Use Cases
  • Needed Capabilities for effective model integration
    • Data Constraints and Inefficiencies
  • Calibration/Validation
  • Behavioral Response
    
    
• AMS Data Hub Concept of Operations
  • Introduction
  • Federates
  • Data Conversion Toolbox
  • Database Schema
  • Cloud STORAGE
  • Visualization
    • V/C Visualization
    • Speed Visualization
    • Queuing Visualization
      
      
• Test Network Overview
  • Introduction
  • Description of Test Networks
    • Tucson, AZ, Test Network
    • Portland, OR, Test Network
    • Objectives of the Portland test application are as follows:
      
      
• Tucson, AZ, Test Application Results
  • Introduction
    • Step 1—Export Network from Regional TDM
    • Step 2—Import Network from Regional TDM
    • Step 3—Read Demand Data from Regional TDM
    • Step 4—Run Assignment with DTALite to Equilibrium
    • Step 5—Cut a Subarea Within the Larger Model for More Detailed Analysis
    • Step 6—Prepare Field Data for ODME
    • Step 7—Run ODME Using Field Data for Calibration
    • Step 8—Export to Synchro^®/PTV Vissim^® for Signal Optimization and/or
      Microscopic Analysis
  • Summary
    
    
• Portland, OR, Test Application Results
  • Introduction
    • Step 1—Export Network from Regional TDM
    • Step 2—Import Network from Regional TDM
    • Step 3—Read Demand Data from Regional TDM
    • Step 4—Run Assignment with DTALite to Equilibrium
    • Step 5—Cut a Subarea within the Larger Model for More Detailed Analysis
    • Step 6—Prepare Field Data for ODME
    • Step 7—Run ODME Using Field Data for Calibration
    • Step 8—Export to Synchro^®/PTV Vissim^® for Signal Optimization and/or
      Microscopic Analysis
  • Summary
    
    
• Conclusions and Recommendations
  
  
• Appendix A. INI Configuration File
  
  
• Appendix B. Data Schema
  • Database system
  • Zones.
    • Existing Practice
    • Challenges
    • Proposed Structure
  • Nodes.
    • Existing Practice
    • Challenges
    • Proposed Structure
  • Links.
    • Existing Practice
    • Challenges
    • Proposed Structure
  • Demands
    • Existing Practice
    • Challenges
    • Proposed Structure
  • Transit
    • Existing Practice
    • Challenges
    • Proposed Structure
  • Household travel surveys
    • Existing Practice
    • Challenges
    • Proposed Structure
  • Travel model outputs
    • Existing Practice
    • Challenges
    • Proposed Structure
  • MOEs
    • Existing Practice
    • Challenges
    • Proposed Structure
  • Scenarios
    • Existing Practice
    • Challenges
    • Proposed Structure
  • Signal Control
    • Existing Practice
    • Challenges
    • Proposed Structure
  • Vehicle Trajectories
    • Existing Practice
    • Challenges
    • Proposed Structure
  • Configuration
    • Existing Practice
    • Challenges
    • Proposed Structure
      
      
• References

LIST OF FIGURES

• Figure 1. Illustration. Data flows and component diagram for AMS data hub
• Figure 2. Flowchart. Implementation of a conceptual integrated AMS tool
• Figure 3. Illustration. Level of aggregation for various AMS tool domains
• Figure 4. Illustration. AMS data hub architecture
• Figure 5. Screenshot. Google Fusion Tables^® data exported from NeXTA
• Figure 6. Illustration. Example network plotted using Google Maps^®
• Figure 7. Graph. Example scatter plot using Google Fusion Tables^®
• Figure 8. Illustration. NeXTA toolbar visualization options
• Figure 9. Illustration. V/C ratio performance by link
• Figure 10. Illustration. Speed performance by link
• Figure 11. Illustration. Queuing performance by link
• Figure 12. Illustration. Tucson, AZ, test network and intersection geometry
• Figure 13. Illustration. NW 185th Avenue arterial test network area
• Figure 14. Photo. Light rail crossing on NW 185th Avenue
• Figure 15. Photo. NW 185th Avenue arterial test corridor traffic
• Figure 16. Photo. Second view of NW 185th Avenue arterial test corridor traffic
• Figure 17. Screenshot. Sample INI configuration file
• Figure 18. Screenshot. File loading status window showing import results after completion
• Figure 19. Illustration. Tucson regional network imported into NeXTA
• Figure 20. Illustration. Subarea boundary selection for Tucson I-10 study area
• Figure 21. Illustration. Clipped subarea for the Tucson I-10 study area
• Figure 22. Illustration. Subarea field data sensor locations for ODME in DTALite
• Figure 23. Graph. Results before ODME for Tucson subarea
• Figure 24. Graph. Results after ODME for Tucson subarea
• Figure 25. Illustration. Tucson I-10 subarea network exported in Synchro^®
• Figure 26. Illustration. Tucson I-10 subarea network in PTV Vissim^®
• Figure 27. Illustration. Tucson network MOE visualization
• Figure 28. Illustration. Portland regional TDM loaded in PTV Visum^®
• Figure 29. Screenshot. Shape file export options in PTV Visum^®
• Figure 30. Screenshot. Saving demand matrices in PTV Visum^® to be imported into NeXTA
• Figure 31. Screenshot. Matrix export options in PTV Visum^®
• Figure 32. Screenshot. Network import menu location in NeXTA
• Figure 33. Screenshot. Import configuration INI file in NeXTA
• Figure 34. Screenshot. File loading status window displaying import results
• Figure 35. Illustration. Portland regional network imported into NeXTA/DTALite
• Figure 36. Illustration. Subarea boundary selection for NW 185th Avenue subarea
• Figure 37. Illustration. Clipped subarea for the NW 185th Avenue subarea
• Figure 38. Illustration. Results from converting zonal connectors to side streets in the
  NW 185th Avenue subarea
• Figure 39. Illustration. Subarea field data sensor locations for ODME in NeXTA
• Figure 40. Graph. Results before ODME for NW 185th Avenue subarea
• Figure 41. Graph. Results after ODME for NW 185th Avenue subarea
• Figure 42. Screenshot. NW 185th Avenue subarea network imported into Synchro^®
• Figure 43. Illustration. NW 185th Avenue subarea network imported in PTV Vissim^®
• Figure 44. Illustration. Comparison of observed and simulated link volumes in the
  NW 185th Avenue subarea in NeXTA

LIST OF TABLES

• Table 1. Estimated time saving from AMS data hub
• Table 2. Capabilities of AMS tools
• Table 3. Use cases for AMS tool integrated modeling applications
• Table 4. Summary of typical transportation AMS data types
• Table 5. Data flow for information propagation and exchange in cross domain applications
• Table 6. Data types
• Table 7. Source data for Tucson, AZ, test application
• Table 8. Source data for Portland, OR, test application
• Table 9. Model attributes configuration settings
• Table 10. Node import configuration settings
• Table 11. Link import configuration settings
• Table 12. Proposed zones data structure
• Table 13. Subarea zone table with sample subarea fields
• Table 14. Socioeconomic zone table with sample subarea fields
• Table 15. Sample fields in the base node table
• Table 16. Sample fields in the node geometry table
• Table 17. Sample fields in the node volume table
• Table 18. Sample fields in the link table
• Table 19. Sample fields in the link geometry table
• Table 20. Sample fields in the link volume table
• Table 21. Demand for activity-based TDMs
• Table 22. O-D for assignment in regional TDM
• Table 23. Production/attraction trip from four-step model
• Table 24. Higher time resolution for DTA or operations analysis
• Table 25. Traffic count
• Table 26. Sample fields in the stop table
• Table 27. Sample fields in the route table
• Table 28. Sample fields in the zone-to-zone fare table
• Table 29. Sample fields in the household table
• Table 30. Sample fields in the person table
• Table 31. Sample fields in the vehicle table
• Table 32. Sample fields in the raw trip table
• Table 33. Sample fields in the processed trip table
• Table 34. Sample fields in the trip table
• Table 35. Sample fields in the skim table
• Table 36. Sample fields in the link table
• Table 37. Sample fields in the activity-based model table
• Table 38. Subset table with sample MOE fields for nodes
• Table 39. Subset table with sample MOE fields for links
• Table 40. Subset table with sample MOE fields for path or corridor
• Table 41. Subset table with sample MOE fields for subarea and entire network
• Table 42. Subset table with sample scenario fields for links
• Table 43. Subset table with sample scenario fields for nodes
• Table 44. Signal control table with sample fields
• Table 45. Signal phasing table with sample fields
• Table 46. Vehicle trajectory table with sample fields
• Table 47. Example configuration table

LIST OF ABBREVIATIONS