Tao Ye M.A.Sc Candidate University of Toronto

1. An Experimental Procedure for Mid Block-Based Traffic Assignment on Sub-area with Detailed Road Network MCRI Student Caucus Meeting September 13, 2003 Tao Ye M.A.Sc Candidate University of Toronto

2. Outline • Background and Problem Statement • Study Area and Data Resources • Procedure and Methodologies • Experimental Results • Summary and Conclusions

3. Background and Problem Statement • Conventional zone-based model

4. Background and Problem Statement • Conventional zone-based model • Zone-based: centroid to centroid • Lack enough detail for intrazonal trips and short trips (in GTA Model, 14% intrazonal trips are not included in the traffic assignment model) • Only 40% of the real road network in the GTA is included in the model • Not appropriate to provide accurate Origin-Destination trip matrices for input into emerging micro-simulation models of corridors or sub-networks

5. Objectives • Develop an experimental procedure to implement mid block-based (block: road link) traffic assignment on a detailed sub-area network • Create mid block points to realistically represent trip ends • Develop mid block-based trip matrix • Model the detailed network including all local streets • Perform mid block-based traffic assignment • Compare the results from mid block-based traffic assignment and zone-based traffic assignment • Data processing and network modeling---ArcGIS8.2, Traffic assignment---EMME/2

6. Study Area --- Downtown Core (PD1) Features (2001): 40.6 km2 64 traffic zones 86,900 households 164,200 residents

7. Data Resources • From Data Management Group: • 2001 Transportation Tomorrow Survey (TTS) • 2001 EMME/2 GTA network model • Traffic cordon counts in the study area • From Data, Map & Government Information Services: • 2001 Ontario detailed street map (Shapefile format) • 2001 Ontario land use map (Shapefile format) • 1996 Canada census: enumeration area (Shapefile format) • Building heights information from Statistics Canada (Shapefile) • 2002 Toronto air photos linked from Toronto Public Library (Jpeg)

8. Procedure and Methodology • Step 1: Create a traversal matrix for the study area from the GTA model • Step 2: Adjust the traversal OD matrix • Step 3: Define mid block points • Step 4: Estimate the production/attraction ratio for each mid block point • Step 5: Redistribute zone-based trip matrix to mid block- based trip matrix • Step 6: Create sub-area detailed network model • Step 7: Perform mid block-based traffic assignment

9. Create Traversal Matrix • Traversal Matrix (as used in EMME/2): An O-D matrix for a sub-area or a ramp-to-ramp matrix for a freeway facility extracted from the total demand matrix • Identify and label all links entering and exiting from sub-area • Run a traversal matrix traffic assignment in EMME/2 • Inputs: • Peak period auto-drive trip matrix retrieved from the 2001 TTS data • 2001 EMME/2 GTA Network Model • Outputs: • A sub area network extracted from the GTA network • An auto trip matrix consistent with the study area zone system, considering all the GTA traffic flows

10. Traversal Matrix Adjustment • Run the macro DEMADJ22 (a gradient approach) to get the adjusted matrix • traffic count screeline

11. Define mid block points • On the main road • Average 3-5 block points for each zone • Action buffer

12. Distribution of mid block points

13. Estimate Production/Attraction Ratio • Production ratio • Based on the population size • Census enumeration area population • Attraction Ratio • Based on the floor space • Three land use categories: commercial, governmental and institutional, industrial and storage • Assume 3-meter height as one floor layer

14. An example of the P/A ratio

15. Generate mid block-based trip matrix

16. Model a detailed network • Mid block point • Obtain coordinates from ArcGIS • Base network • Assume features for local street links: lane number---1, free flow speed---40, and lane capacity---400. • Turn tables • DMTI format: from link to link • EMME/2 format: from node to node

17. Experimental Results • Comparison oftwo network model features

18. Experimental Results (cont’d) • Mid block-based traffic assignment

19. Experimental Results (cont’d) • Zone-based traffic assignment

20. Experimental Results (cont’d) • Main road link volume analysis

21. Experimental Results (cont’d) • Local street volume analysis

22. Experimental Results (cont’d) • Running time analysis • *ngap: normalized gap, which is difference between • the mean trip time (or cost) at the previous iteration and the • mean minimal trip time (cost) computed by assigning the • demand to shortest path of the current iteration.

23. Conclusions and Recommendations • Summary of benefits and values • More realistic road network representation • Suitable for data analysis of GPS-based personal travel surveys • More precise results for traffic impact studies • More accurate inputs for the traffic micro-simulation studies • GTA model enhancement • Further research • Combination of long trips and short trips --- windowed model • Consideration of other measures to estimate production and attraction ratio • Enough traffic survey counts to conduct traversal matrix adjustment

24. Thank You! Open for Questions...