Directionality Influences in Spatial Processes

1. Directionality Influences in Spatial Processes by JD Hunt, University of Calgary M Thériault, Université Laval P Villeneuve, Université Laval PROCESSUS Second International Colloquium Toronto ON, Canada June 2005

2. Overview • Introduction • Context • Motivations • Approach • Evidence • Disaggregate Observations of Choice Behaviour • Aggregate Patterns of System Behaviour • Conclusions • Modelling • Expectations regarding urban form • Planning and design

3. Introduction • Context • Modelling spatial decisions, representation relative location • Travel time components • Travel cost components • Comfort and convenience • What of ‘directionality’? • ‘together’, ‘on the way’ rather than ‘out of the way’ • Anchored relative to reference locations: work, CBD, etc • Nature of perception beyond times and costs • System reinforcing directional tendencies • Motivation • Adding representation of directionality – simple form • Seeing in results in various forms • Improved understanding • Higher fidelity • Increased accuracy? • Faster processing

4. Introduction • Approach • Draw on previous work in several locations • Evidence of directionality effects • Representation of these effects • Disaggregate behavioural evidence • Parking location choice in Edmonton • Commercial vehicle stop location choice in Calgary • Intermediate shopping stop choice in Quebec City • Aggregate system behavioural evidence • Trip durations in Quebec City • Historical development patterns in Quebec City • Recent employment dynamics in Montréal

5. Parking Location ChoiceEdmonton • 1983: Hunt • Develop mode choice model for regional travel demand model • Include parking location choice for CBD-destined auto driver alternative • composite utility for parking • parking demand allocation • support mode and parking policy analysis

6. Data • 1983 Morning Commuter Survey • 80 employers (business & government establishments) • 1702 travellers • 468 drivers, selecting parking locations • Employer parking policy regarding travellers • 124 publicly available off-street parking facilities • Unmetered on-street parking areas, aggregated into 12 areas

7. 107 Ave F E 97 St C D G 104 Ave Jasper Ave A B L H N 105 St 101 St Jasper Ave K 1 km I 109 St J Legend: area of on-street parking CBD boundary

8. Parking Location Choice Modelattributes in utility functions: • Walking distance to final destination • Parking charge per day • Number of stalls • Surface treatment – if paved or not • Adjacent land use – if residential or not • Security • Cleanliness • Angle relative to CBD and home, ANG

9. employer arranged off-street on-street …. …. individual on-street locations individual off-street locations Parking Location Choice Model Nesting Structure

10. home workplace ANG parking location ANG Measure

11. home workplace ANG parking location ANG Measure and ANG = 90° when • Walk distance < 450 m for off-street • Walk distance < 700 m for on-street

12. Parking Location ChoiceEdmonton

13. Parking Location ChoiceEdmonton

14. Parking Location ChoiceEdmonton • Findings: • ANG appears to have influence • driving time differences not included, potential for bias • consider in future location choice modelling

15. Commercial Stop Location ChoiceCalgary commercial vehicle movements • 2005: Hunt, Stefan, McMillan, Abraham, et al • Develop model of ehicles operated for commercial purposes • As opposed to household, personal movements • Includes ‘non-commercial’ non-household purposes (government, not-for-profit) • Comprise 10-15% of total urban traffic

16. Commercial Vehicle Movements • Vehicles operated for commercial purposes • As opposed to household, personal movements • Includes ‘non-commercial’ non-household purposes (government, not-for-profit) • Comprise 10-15% of total urban traffic

17. Commercial Hauling freight for a company Service workers visiting clients Sales meetings Mail Delivering parcels Personal Travel to work Travel to school Shopping Leisure trips Social visits Some Examples

18. Data • 2001 Commercial Movement Study • All commercial movements • Not just freight • Not just trucks • 3,100 establishments in Calgary • 4,300 establishments in Edmonton • 24 hour stop diary • Firmographics • Employment structure • Vehicle fleet

19. Next Stop Location • Assigns location for each subsequent, non-establishment stop on each tour in list • by 13 commercial model segments (industry, vehicle and tour purpose categories) • Monte Carlo, probabilities based on Logit • Single-level Logit among locations (zones) for next stop, total of 1,447 zones in model

20. Next Stop Location Choice Modelattributes in utility function: • Travel gen cost to potential stop location • Travel gen cost for return to establishment from potential stop • Population and employment accessibilities • Land use coefficients (5 land uses) • Average income for households at potential stop • Population and employment size terms • Enclosed Angle

21. Angle Measure

22. Angle Measure and ANGLE = 0 when • starting tour • NEXT STOP = CURRENT STOP

23. Commercial Stop Location ChoiceCalgary

24. Commercial Stop Location ChoiceCalgary

25. Commercial Stop Location ChoiceCalgary 3 4 3 2 4 1 1 2 5 5 base base -ve +ve

26. Commercial Stop Location ChoiceCalgary • Findings: • Enclosed angle has strong influence • Sign changes for different segments • Displaying different spatial patterns • Driving gen cost differences included for next location and base location • Stronger case for directionality influence • Include in future location choice modelling • Expect to find aggregate impacts

27. HBW Intermediate Shopping ChoiceQuebec City • 2005: Thériault • Model decision to make an intermediate shopping stop on trip from work • Consider influence of locations relative to work - home axis • ‘on the way’ vs ‘out of the way’ from work to home

28. Data • 2001 OD Survey • 29,249 workers with fixed workplace (not working at home) • 825 intermediate shopping stops made during HBW trips • 323 to large store • 222 to small shop • 270 to grocery

29. Stop to Shop Choice Modelattributes in utility function: • Gender • Age • Household size • Household auto ownership • Distance from home to central axis (Grande Allee) • Distances from home to workplace • Straight-line • North-south and east-west components separately

30. home straight-line distance north-south component distance Y-axis N workplace east-west component distance X-axis distances from home to work with directionality components

31. Stop to Shop ChoiceQuebec City

32. Stop to Shop ChoiceQuebec City

33. Stop to Shop ChoiceQuebec City

34. Stop to Shop ChoiceQuebec City

35. HBW Intermediate Shopping ChoiceQuebec City • Findings: • Home location relative to central axis has +ve impact – more chaining of shopping with work travel when home location has relatively less nearby • Home to work distance has +ve impact – more ‘on the way’ intermediate opportunities • Directionality components of home to work distance have different impacts • Y-Axis (N-S) +ve linear impact • X-Axis (E-W) –ve logrithmic impact • Perhaps related to highway network, with more high-speed capacity N-S • Travel times & costs not included, potential for bias?

36. Trip Duration InfluencesQuebec City • 2003: Vandermissen, Villeneuve and Thériault • Examine how trip duration is influenced by alignment of trip origin and destination with CBD • Hypothesis 1: Trip duration will decrease as alignment of origin and destination with CBD increases • Hypothesis 2: Influence of alignment with CBD on trip duration will decrease as city becomes less monocentric • ‘directionality’ here is relative to CBD

37. Data • 1991 OD Survey (n=29,046); 2001 OD Survey (n=46,664) • Congested network travel times - from model • Trip purposes • Work • Study • Shopping • Leisure • Other • Traveller characteristics • Gender • Age • Trip Characteristics • Mode • Time of Travel (peak vs off-peak) • Distance from origin to CBD • Distance from destination to CBD

38. CBD Path of trip in street network destination Dperpen origin Measure of Directionality Dperpen is the length of the perpendicular between the destination point and the locus of the straight line passing through the origin of the trip and the CBD

39. CBD Path of trip in street network destination Dperpen origin Measure of Directionality Dperpen is the length of the perpendicular between the destination point and the locus of the straight line passing through the origin of the trip and the CBD Origin and destination are aligned with CBD when Dperpen = 0; As Dperpen increases alignment decreases

40. CBD Path of trip in street network destination Dperpen origin Measure of Directionality Dperpen is the length of the perpendicular between the destination point and the locus of the straight line passing through the origin of the trip and the CBD Origin and destination are aligned with CBD when Dperpen = 0; As Dperpen increases alignment decreases Hypothesis1: Trip duration increases as Dperpen increases

41. Trip Duration Modelindependent variables in regression: • Gender • Age • Mode • Time of travel (peak vs off-peak) • Distance from origin to CBD • Distance from destination to CBD • Dperpen • Measure of directionality of O-D relative to CBD • Increase in Dperpen less aligned with CBD; increase in trip duration • +ve coefficient

42. Trip Duration InfluencesQuebec City

43. Trip Duration InfluencesQuebec City

44. Trip Duration ModelQuebec City • Findings: • Trip duration decreases as alignment of origin and destination with CBD increases • Supports Hypothesis 1 • For full range of trip purposes • More of a network effect, supply vs demand • Combined with other work, this influence is increasing • Potential for reinforcing directionality aspects of choice behaviour

45. Historical Development PatternsQuebec City • 2004: Thériault and Bourel • Examine growth patterns • Axes of development, impact of ‘on the way’ increasing activity at intermediate locations • Role of CBD as reference

46. Data • History of development • Various points starting in 1830 • Range of modal influences • Rail encourages linear patterns in Quebec City Auto encourages more radial expansion in all directions with some clustering along high-speed roads • Configuration of land parcels (normal to river)

47. Historical Development of Quebec City (1) Early 19th Century Old City Core and Villages (2) Mid 19th Century Development of “Faubourgs” (5) 1945 -1960 – Axes confirm Beginning of urban sprawl (3) Turn of 20th Century Extension of “Faubourgs” (6) 1960-1975 – Axes consolidate Peak of urban sprawl – Remote towns (4) 1920 -1945 – Axes appear New Neighbourhoods (7) 1975 - 2000 – Filling gaps Some extension of axes – Suburbanization

48. Historical Development PatternsQuebec City • Findings: • Distinct axes appear • Radial out from CBD • Before sprawl • Consistent with linear impact of ‘on the way’ directionality influence • Also consistent with rail then auto impacts • Parcel orientation also a factor • Difficult to separate influences

49. Recent Employment DynamicsMontréal • 2005: Barbonne • Examine employment patterns 1981 and 2001 • Axes of development, impact of ‘on the way’ increasing activity at intermediate locations • Role of CBD as reference

50. Centrographic analyis suggests elongation of local labour markets Source: Barbonne,2005