Estimation of a Weekend Location Choice Model for Calgary
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Transcript of Estimation of a Weekend Location Choice Model for Calgary
Estimation of a Weekend Location Choice Model for
CalgaryKJ Stefan, City of Calgary
JDP McMillan, City of CalgaryCR Blaschuk, City of Calgary
JD Hunt, University of Calgary
Overall model context
• Weekend Household Activity Model (WHAM)• Personal weekend travel• Tour-based microsimulation model• Emphasis on activities• Partial treatment of household groups• Same household survey as RTM
• Sampling evenly across all 7 days • 2342 weekend households
Overall model context
• Part of a model system for Calgary• Weekday regional travel model (RTM)
• Personal travel• Aggregate model with full nested logit
structure
• Weekday commercial vehicle model (CVM)• Commercial vehicle travel• Tour-based microsimulation model
Model goals
• Part of 24/7 system evaluation• Benefits to all users• Emissions
• Analysis of retail and entertainment facilities
• Microsimulation input• Learning for weekday activity model
Weekday personal
66%
Weekday
commercial
6%
Weekend personal
26%
Weekend
commercial (est.)
1%
Other (est.)
1%
24/7 Model Coverage
Overall model structure
Tour Generation and membership
Tour Purpose
Tour Mode
Trip and stop properties (including
location choice)
Two Types of Tours
• Growing• Stops organically ‘grow’, chosen one
after another
• Hybrid Rubber-banding• Primary Stop chosen• Optional Intermediate Stops• Subsequent stops chosen as with
growing tours
Home
Growing Tours
Stop
Stop
?
Home
Growing Tours
Stop
Stop
Home
Growing Tours
Stop
Stop?
Stop
Home
Growing Tours
Stop
Stop
Stop
Stop
Home
Hybrid Tours
PrimaryStop
Home
Hybrid Tours
IntermediateStop
PrimaryStop
?
Home
Hybrid Tours
IntermediateStop
PrimaryStop
Home
Hybrid Tours
IntermediateStop
Stop
PrimaryStop
?
Home
Hybrid Tours
IntermediateStop
Stop
PrimaryStop
Home
Hybrid Tours
IntermediateStop
Stop
PrimaryStop?
Stop
Tour Purposes
Hybrid Treatment• Out of Town• Serve Passenger• Work• School• Religious/Civic• Exercise
Growing Treatment
• Shopping• Entertainment /
Leisure• Social• Eating
Trip and stop properties
Stop purpose
Stop location
Trip mode
Stop duration
Model estimation
• Two-stage estimation• Location attractors
• Linear regressions by activity• Large number of zonal attributes
• Location choice logit model• Combines attractors with travel and group
information• In progress; auto complete (most
important one at ~65% of trips)
Zonal attributes
• Population and demographic• Age ranges, incomes, car ownership
• Education spaces by level• Employment by 8 industry types• Park in hectares• Special attractors• Land use typology (calculated)
Special attractors
• Institutions:• 3 major post secondary institutions• 3 major hospitals• Airport
• Entertainment:• Arts and Culture District• Stampede, Zoo, Heritage Park
• Big Box retail
Land use types
• 5 land use types:• Low-density• Residential• Commercial (retail)• Industrial• Employment node
• Calculated based on employment and population (mix and density)
Low density
Residential
Commercial
Industrial
Employment node
Attractors – Work
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Industrial employment, industrial zones
Industrial, employment nodes
Industrial, other zones
Wholesale and Transport, industrial zones
Agriculture, Whole., Trans, other zones
Education, all zones
Population, low density zones
Attracted trips (R2=0.575)
Attractors - Work
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Retail, commercial zones
Retail, residential zones
Retail, other zones
Service, commercial zones
Service, employment nodes
Service, hospital sites
Service, residential zones
Service, other zones
Arts and Culture district
Attracted trips (R2=0.575)
Other attractor functions
• Serve Passenger:• Retail, airport, hospitals, education
• School:• Student spaces – especially PSE spaces
• Religious/Civic:• Population (75+, income), education, retail
• Exercise:• Park space, employment, population (65+,
income), student spaces
Other attractor functions
• Shop:• Retail (esp. commercial zones, big box)
• Entertainment/Leisure:• Attractors, population (15-24, income), retail
• Social:• Population (15-34, 65+, income), service,
retail
• Eating:• Retail (commercial, residential), population
Logit estimation
• Combining regressed attractors with travel costs and group properties
• Generalised travel cost (time and distance)
• Presenting one of a set of models• Auto mode• Growing portion of tours only• Represents around 65% of weekend
travel
Home
Primary Stop
Stop
Stop
Stop
Growing tour or hybrid tour after primary stop
Home
Stop
Stop
StopTo cost
Primary Stop
Home
Stop
Stop
StopTo cost
Return cost
Primary Stop
Home
Stop
Stop
StopTo cost
Return cost
Enclosed angle
Primary Stop
Home
Stop
Stop
StopTo cost
Return cost
Enclosed angle
Attractor
Primary Stop
Auto Stop Location Parameters
Next stop location choice model; To Cost Parameters(absolute t-statistics in brackets)
-0.12 -0.1 -0.08 -0.06 -0.04 -0.02 0 0.02 0.04
1 person (16.87)
2 persons (17.8)
3 persons (8.77)
income <$35K (2.86)
1 pers trip, age < 25 (1.99)
1 pers trip, age 25-29 (4.96)
shop trips (4.33)
social and entertainment trips(1.73)
Parameter value
Auto Stop Location Parameters
Next stop location choice model; Return-to-Home Cost Parameters(absolute t-statistics in brackets)
-0.06 -0.05 -0.04 -0.03 -0.02 -0.01 0
1 person (9.08)
2 persons (2.04)
3+ persons (3.7)
num kids 5-8 (2.53)
num kids 9-13 (2.32)
num nondriving adults (3.27)
num seniors 75+ (2.39)
shop trips (15.6)
Parameter value
Example groups
• One adult (30+)• One adult, one kid (8)• Two adults• Two adults, two children (8 and 12)• One adult, one senior (82,
nondriving)
-0.12
-0.1
-0.08
-0.06
-0.04
-0.02
0
One
adu
lt
One
adu
lt,
one
kid
Tw
o ad
ults
Tw
o ad
ults
, tw
oki
ds
Adu
lt,
seni
or
Gen
eral
ized
cos
t
To
Return
Example trips
• One adult:• <25, shop• 25-29, entertainment• 30+, shop• 30+, eating• Low income, 30+, entertainment
-0.08
-0.07
-0.06
-0.05
-0.04
-0.03
-0.02
-0.01
0
<25,
sho
p
25-2
9,en
tert
ainm
ent
30+,
sho
p
30+,
eat
ing
30+,
ente
rtai
nmen
t,lo
w in
com
e
Gen
eral
ized
cos
t
To
Return
Auto Stop Location ParametersNext stop location choice model; all parameters
(absolute t-statistics in brackets)
-0.05 0 0.05 0.1 0.15 0.2
Enclosed angle (7.78)
Attractor; shop (14.77)
Attractor; social (6.22)
Attractor; eating (5.54)
Attractor; entertainment(2.49)
Attractor; rubberbandingtype stops (1.77)
Parameter value
Auto Stop Model
• Sensible results• Costs lest significant for social trips• Return to home costs important, but
not as important as to costs• Less mobile members of group add to
costs of location choices
Next Steps
• Estimate growing tour location choice models for remaining modes (bike and ‘other’)
• Estimate models for primary stop and intermediate stop location choices
QUESTIONS
• Please Use Microphone