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Building Confidence in TFlowFuzzy

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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  1. Building Confidence in TFlowFuzzy Trip Table Development, Validation and Application in Downtown Windsor

  2. Outline • Study Overview • Traditional Approach • Trip Table Development with TFlowFuzzy • Ways to Improve the Method • Conclusions

  3. 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

  4. Overview: Study Area Tunnel to Detroit Casino Windsor Downtown Windsor

  5. 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

  6. 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

  7. 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

  8. 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

  9. Windsor Road Network and Initial Casino Study Area Potential Road Closure

  10. TFlowFuzzy: Model Development 41 zones 102 connectors

  11. 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

  12. TFlowFuzzy: Analysis Results 2% 0% 1% 0% 6% 0% 1% -1% 1% 2% 1% 2%

  13. TFlowFuzzy: Analysis Results

  14. 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

  15. Windsor Road Network and Expanded Downtown Study Area Potential Road Closures Potential Two-way Conversions

  16. 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

  17. 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

  18. TFlowFuzzy: Analysis Results -1% 8% 8% 5% 5% 3% -4% 9%

  19. 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.

  20. Application of TFlowFuzzy Trip Table Base Case – Existing One-way Network

  21. Application of TFlowFuzzy Trip Table Alternative – Complete Two-way Network

  22. 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

  23. Conclusions • 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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