Pedestrian Movement Analysis


Published on

A study on pedestrian movement done in Tel-Aviv.
morphological and functional attributes of the built environment and their affect on pedestrian distribution

Published in: Education, Travel, Technology
1 Like
  • Be the first to comment

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Pedestrian Movement Analysis

  1. 1. Morphological and FunctionalAttributes of the Urban Environment and Pedestrian Movement Presented by: Yoav Lerman Tel-Aviv University
  2. 2. The joy of being a pedestrian
  3. 3. The sorrow of being a pedestrian
  4. 4. Tel-Aviv BasicsFounded: 1909Population: 400,000Land size: 52 sq. kmMetro Population: 3 million
  5. 5. AgendaResearch questionResearch area locationMethodology Spatial-physical dimension Functional dimensionFindings
  6. 6. Research QuestionWhich attributes of the built environment correlatewith the volume of pedestrian movement in twoadjacent areas in the center of Tel-Aviv?
  7. 7. Research Area
  8. 8. Research AreaEast of Ibn-Gvirol street vs. west of Ibn-Gvirol street Research area boundary Sub areas boundary
  9. 9. Methodology Dependent variable: pedestrian counts Independent variables: built environment attributes Positivist methodology based on non-intrusive observations Looking for statistical correlations between the independent variables and the dependent variable
  10. 10. Each square – 500m X 500m
  11. 11. Two dimensions of the built environment Spatial-physical dimension The basis of the urban form Extremely durable and rarely modified Functional dimension The content that fills the form Relatively fast changes
  12. 12. Spatial-Physical Variables Space syntax measures Connectivity by street name Pavement width Road crossing difficulty Intersection density
  13. 13. Functional Variables Commercial fronts Residential density Proximity to bus stations
  14. 14. Space Syntax MeasuresUse of DepthMap software based upon axial linesanalysis: Connectivity Control Integration - Global Integration – Mean distance from the entire street network - Local Integration – Mean distance from nearby streets
  15. 15. A Comment about Mapping Fixed the street network according to pedestrian routes Boulevards Squares
  16. 16. Street Scheme
  17. 17. Axial Lines
  18. 18. Connectivity
  19. 19. Connectivity
  20. 20. Global Int.
  21. 21. Global Int.
  22. 22. Connectivity by Street Name
  23. 23. Pavement Width
  24. 24. Commercial Fronts
  25. 25. Pedestrian Count Points 95 count points 51 street segments 24 western segments 24 eastern segments 3 border segments Count method: 5 minutes at each point 5 counts at each point (once per hour for 5 hours)
  26. 26. Pedestrian Count Points Location
  27. 27. Avg. Pedestrian Volume in each segment (per hour)
  28. 28. Findings Four correlated variables in descending order: R squared 0.83 1. Connectivity by street name 2. Total commercial front 3. Residential density in subzone 4. Proximity to bus stations
  29. 29. Findings – Western Area One correlated variable Connectivity by street name R squared 0.82 R squared 0.88 without boulevards and squares
  30. 30. Findings – Eastern Area Three correlated variables: R squared 0.86 1. Total commercial front 2. Space syntax connectivity 3. Space syntax control
  31. 31. Findings – Eastern Area (Cont’) Without the squares (Kikar Hamdina) Three correlated variables: R squared 0.9 1. Connectivity by street name 2. Space syntax global int. 3. Total commercial front
  32. 32. Summary In most cases the spatial-physical structure has greater correlation than the functional structure with pedestrian movement There are major differences between the western and eastern areas correlations Connectivity by street name correlated better than space syntax variables The large square in the eastern side changes the correlation model significantly