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Building Confidence in TFlowFuzzy. Trip Table Development, Validation and Application in Downtown Windsor. Outline. Study Overview Traditional Approach Trip Table Development with TFlowFuzzy Ways to Improve the Method Conclusions. Overview: City of Windsor.

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Building Confidence in TFlowFuzzy

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Building confidence in tflowfuzzy l.jpg

Building Confidence in TFlowFuzzy

Trip Table Development, Validation and Application in Downtown Windsor

Outline l.jpg


  • Study Overview

  • Traditional Approach

  • Trip Table Development with TFlowFuzzy

  • Ways to Improve the Method

  • Conclusions

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Overview: City of Windsor

  • Located across the Detroit River from Detroit, Michigan

  • Population of 323,000 in 2006

  • Major auto manufacturing centre

  • Promoting tourism industry

    • Expansion of Casino Windsor

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Overview: Study Area

Tunnel to Detroit

Casino Windsor

Downtown Windsor

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Overview: Assignment

  • To evaluate traffic implications of road network modifications

    • Road closures to facilitate Casino operations and expansion

    • One-way to two-way street conversions to improve accessibility and exposure to downtown businesses

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Traditional Approach

  • Develop / utilize OD Table from survey, macro-level model, etc.

  • Assign to VISSIM network

  • Compare simulated volumes to observed traffic counts

  • Adjust trip table as required

  • Re-assign

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Not applicable in this case:

No Survey Data

No Macro-level Model

Need to create a trip table for VISSIM assignment to evaluate the impact of closing a road in the Casino area

Traditional Approach

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Reason for Initial Study

  • New hotel and entertainment complex under construction at time of study

  • Closing road proposed to facilitate valet parking and VIP entrance

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Windsor Road Network and Initial Casino Study Area

Potential Road Closure

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TFlowFuzzy: Model Development

41 zones

102 connectors

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TFlowFuzzy: Model Development

  • Established base seed trip table

    • 25 trips between each major gateways pair

    • 12.5 trips between each minor gateways pair

    • 1 trip between internal zone pairs

    • 1 trips between gateways and internal zones

  • Adjusted seed trip table to ground counts with TFlowFuzzy

  • Assigned to network in VISUM and compared with ground counts

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TFlowFuzzy: Analysis Results





6% 0%

1% -1%

1% 2%



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TFlowFuzzy: Analysis Results

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TFlowFuzzy: Expanded Area

  • Initial results in small study area provided a reasonable correlation to observed conditions

  • Client asked for analysis of other proposed downtown road network changes

  • Network expanded to encompass other proposed changes

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Windsor Road Network and Expanded Downtown Study Area

Potential Road Closures

Potential Two-way Conversions

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TFlowFuzzy: Expanded Area

  • Developed traffic zone system (98 zones)

  • For each zone, surface areas by land use type estimated from Google Earth and MS Virtual Earth

  • Applied ITE Trip rates to generate zone productions and attractions

  • Distributed trips using logit model with unitary coefficients

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TFlowFuzzy: Expanded Area

  • Assigned initial trip table to network in VISUM

  • Applied TFlowFuzzy procedure

  • Assigned adjusted trip table to network in VISSIM

  • Compared simulated flows to observed values

  • Final trip table represents existing conditions

    • Base to which development traffic is added

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TFlowFuzzy: Analysis Results





5% 3%



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Application of TFlowFuzzy Trip Table

  • Trip table and site specific development traffic assigned to VISSIM network with road closures and two-way street conversions

    • Provided intersection levels-of-services throughout the network

    • Allowed for the evaluation of several network scenarios.

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Application of TFlowFuzzy Trip Table

Base Case – Existing One-way Network

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Application of TFlowFuzzy Trip Table

Alternative – Complete Two-way Network

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Way to Improve Method

  • Refine trip generation and distribution method

    • Improve function for trip distribution

      • Consider gravity model

      • Review weightings of gateway zones

    • Refine trip generation through more detailed land use data

      • City records to obtain floor space or other statistics for land use if available

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  • Trip tables synthesized using TFlowFuzzy provided adequate correlation between observed and modelled conditions

  • Method provides reasonable approach when no survey data or macro-level model is available

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