Upload
tu-delft-opencourseware
View
420
Download
1
Tags:
Embed Size (px)
Citation preview
17/4/13
Challenge the future Delft University of Technology
CIE4801 Transportation and spatial modelling
Rob van Nes, Transport & Planning
Spatial modelling: Land use and transportation models
2 CIE4801 Land use and transportation models
Content
• Land use and transportation models (LUT) • UrbanSim • TIGRIS XL • TIGRIS XL Applications
• Choice modelling • Firm location behaviour • Household location behaviour
• Circle of Wegener revisited
3 CIE4801 Land use and transportation models
1.
Land use and transportation models
4 CIE4801 Land use and transportation models
LUT models: Framework
government
labor market
real-estate market
firms
housing market
households
transport model
transport costs, accessibilities demography
commercial buildings
houses
infrastructure
land market
developers
5 CIE4801 Land use and transportation models
1.1
UrbanSim
6 CIE4801 Land use and transportation models
UrbanSim: Modelling approach
• Models choices of decision-makers in a theoretic framework
• Models processes using multinomial or nested logit
• Microsimulation of individual decision-makers
• Dynamically simulate annual time steps
• Models market interactions
• Uses very disaggregrate spatial units
7 CIE4801 Land use and transportation models
8 CIE4801 Land use and transportation models
UrbanSim: Inputs and outputs (per grid cell, 150m x 150m)
INPUT • inhabitants (census data) • land ownership parcels • firms • household travel survey • land use plan • environmental constraints • transportation system
OUTPUT • households • employment by type • real-estate development • real-estate prices
9 CIE4801 Land use and transportation models
UrbanSim: Model structure
Accessibility model determines the accessibility level, depending on traffic model outcomes
Economic & demographic transition model determines creation or loss of households and jobs
Household & employment mobility model determines if households and jobs are moving within the region
Household & employment location model determines the location choices of households and jobs from available vacant real-estate
Real-estate development model determines the type, location, and quantity of new construction by developers
Land price model determines the price of land at each location
t =
t +
1
10 CIE4801 Land use and transportation models
UrbanSim: some results (1/3)
Eugene-Springfield (Oregon, USA)
Employment, 1980
11 CIE4801 Land use and transportation models
Eugene-Springfield (Oregon, USA)
UrbanSim: some results (2/3)
Employment, 1994
12 CIE4801 Land use and transportation models
Eugene-Springfield (Oregon, USA)
UrbanSim: some results (3/3)
Employment change 1980 - 1994
13 CIE4801 Land use and transportation models
1.2
TIGRIS
14 CIE4801 Land use and transportation models
TIGRIS
• Transport Infrastructure Land-use (‘Grondgebruik’) Interaction Simulation
• Developed in the 90’s • Primarily based on expert judgement
• Model structure as well as parameters
• Meant to be a sketch-planning model • GIS-based, incremental development (year by year), dashboard
15 CIE4801 Land use and transportation models
TIGRIS: Flow chart
320 LUTI modelling in the Netherlands
attractions
Figure 1: Interactions in TIGRIS
Submodels in TIGRIS
The attractiveness of a zone is subdivided in attractiveness for living purposes and attractiveness for working purposes (Figure 2). The attractiveness is dependent upon the accessibility of a zone. The attractiveness for living is determined by the number of (vacant) dwellings in the zone and something called ‘living quality’ (e.g. close to beautiful nature areas). This latter variable is comparable to a dummy variable and is designed to take into account the fact that some areas are more (or less) attractive than others. The attractiveness for working purposes is determined by the existing jobs and the developed employment capacity in the zone. Figure 2. Attractions submodel
Land use is characterised by the number of dwellings, available employment capacity, population, jobs and amenities per zone (Figure 3). Land use is determined by autonomous national and regional developments, and the migration of people and firms. Migration is determined on the basis of attractiveness of a zone and the distance to competing zones. Dwelling construction per zone is determined on the basis of demand and a user-specified minimum and maximum number of dwellings. The same applies for the number of available
attraction living
attraction working
living quality
employ-ment
vacancies offices
employ-ment
capacity
dwelling vacancies
dwelling construc-
tion
accessibi-lity
t-1 t-1 t-1 t-1
accessibility
travel impedance
Congestion
mobility
land use
t-1
t-1
16 CIE4801 Land use and transportation models
TIGRIS: Submodels
• Attractiveness of a zone • Living and working
• Land use • Dwellings and industrial/office sites
• Mobility • Congestion
• Car • Travel impedance
• Car and PT • Accessibility
• Amenities, population, jobs
‘equilibrium’
To be used in year t+1
17 CIE4801 Land use and transportation models
TIGRIS: Applications
• Four applications • Randstadrail • Leiden-Haarlem-Amsterdam • Arnhem-Nijmegen • Randstad: Urbanisation beyond 2030
• Primarily used as an explorative model • Unclear role in planning processes
• Evaluation • Not state of the art (no choice modelling) • Not tailored to the questions in practice (e.g. link with economic
analyses)
18 CIE4801 Land use and transportation models
TIGRIS XL: Modelling approach
• Dynamic spatial allocation model • Accessibility influences location choice • Determines effects of infrastructure concepts on land use • Determines effects of spatial planning on transportation • Simulates annual changes • Uses aggregrate zones, no detailed spatial data • Used for policy development, not for evaluation.
19 CIE4801 Land use and transportation models
TIGRIS XL: inputs and output
INPUT • zones • inhabitants • car ownership • employment levels • services • captives and non-captives • population growth factors • spatial development policies • coarse infrastructure network
OUTPUT • households by type • employment by type • real-estate development • real-estate prices • trips • travel times • safety & environment
20 CIE4801 Land use and transportation models
Functional design of TIGRIS XL
Regional Labor Market demand Labor market regional
workforce
Firms / jobs Transport market households /
persons
Real estate market
Office space/ Industrial zones Land market houses
Housing market
demography
CO
RO
P re
gion
s zo
nes
21 CIE4801 Land use and transportation models
Modules TIGRIS XL
• Demography - module addressing basic demographic developments
• Land market - simplistic, excludes role of land-owner and project developers
• Housing market - behavioral choice model estimated on housing market survey
• Labor market - calibration on period 1986-2000
• Transport module - integration of land-use modules with LMS
22 CIE4801 Land use and transportation models
Land market, role of government
TIGRIS XL can model different levels of government influence on the spatial development:
• Regulated development (‘directed allocation’)
spatial developments can only take place on planned locations
• Free market development (‘free allocation’)
spatial developments following preferences of households and firms. The developments are restricted by availability of land
23 CIE4801 Land use and transportation models
Household choices
SStay Move
Household X
Intra COROP Other COROP
Zones (1308)
24 CIE4801 Land use and transportation models
Household move/stay choice
Explanatory variables
• Household size
• Employment
• Household income
• Age head of household
• Zone type classification (urban to rural)
• Vacant houses in region
• Accessibility current location
25 CIE4801 Land use and transportation models
Household location choice
Explanatory variables
• Number of vacant houses in a zone
• Average price of houses in a zone
• Zone type classification (urban – rural, 5 categories)
• travel time (travel time between old and new location)
• Accessibility location
• Zone characteristics (water, services, green, population density, etc.)
26 CIE4801 Land use and transportation models
Firm choices
Identification of economic sectors is important, because these sectors show different location preferences and responses to transport measures.
Sectors in TIGRIS XL are:
• Agriculture
• Industry
• Logistics
• Retail sector
• Other consumer services
• Business services
• Government
27 CIE4801 Land use and transportation models
Firm location choice
Explanatory variables • Accessibility employees
• Population in a region
• Accessibility business
• Accessibility freight
• Agglomeration
• Urbanization
• Relative share of sector in a region
28 CIE4801 Land use and transportation models
Accessibility variables
Utility based accessibility measures for (so-called logsum measures)
• Accessibility by household type
• Accessibility of firms for commuters
• Accessibility of firms for business
29 CIE4801 Land use and transportation models
1.3
TIGRIS XL: Applications
30 CIE4801 Land use and transportation models
TIGRIS XL: Randstad
inner region
Amsterdam
Utrecht
Rotterdam
Den Haag
What are the consequences on land use and traffic when there is development - in the outer region; or - in the inner region
31 CIE4801 Land use and transportation models
Randstad: results land use
Developing in outer region Developing in inner region
0 0 - 2500
2500 - 5000 5000 - 7500
7500 - 10000 > 10000
increase in houses 2010 - 2030
32 CIE4801 Land use and transportation models
Randstad results transportation
Developing in outer region Developing in inner region
congestion 2010 - 2030
33 CIE4801 Land use and transportation models
TIGRIS XL Trend scenario
Working population (15-64)
34 CIE4801 Land use and transportation models
% per jaar
0.72 of meer
0.48 tot 0.72
0.27 tot 0.48
0.00 tot 0.27
-0.31 tot 0.00
-0.58 tot -0.31
-0.98 tot -0.58
minder dan -0.98
Industry Logistics Retail
Other consumer Business services Government services
Jobs
Results trend scenario
35 CIE4801 Land use and transportation models
0 20 40 60 8010km206 - 250000
250001 - 500000
500001 - 750000
750001 - 1000000
1000001 - 1250000
0 10 20 30 405km
206 - 250000
250001 - 500000
500001 - 750000
750001 - 1000000
1000001 - 1250000
1250001 - 1500000
morning peak rest of the day
Accessibility of jobs for households (by car)
36 CIE4801 Land use and transportation models
0 20 40 60 8010km462 - 100000
100001 - 200000
200001 - 300000
300001 - 400000
400001 - 500000
Accessibility of jobs for households (by public transport)
37 CIE4801 Land use and transportation models
0 20 40 60 8010km
192 - 250000
250001 - 500000
500001 - 750000
750001 - 1000000
1000001 - 1250000
1250001 - 1500000
morning peak rest of the day
0 20 40 60 8010km
206 - 250000
250001 - 500000
500001 - 750000
750001 - 1000000
1000001 - 1250000
1250001 - 1500000
1500001 - 1917866
Accessibility of employees for firms (by car)
38 CIE4801 Land use and transportation models
0 20 40 60 8010km
462 - 100000
100001 - 200000
200001 - 300000
300001 - 400000
400001 - 500000
500001 - 639338
Accessibility of employees for firms (by public transport)
39 CIE4801 Land use and transportation models
Appointed concentration areas
Application concentration scenario
40 CIE4801 Land use and transportation models
Population Results concentration scenario
41 CIE4801 Land use and transportation models
Population – concentration vs. trend Results concentration scenario
42 CIE4801 Land use and transportation models
Arbeidsplaatsen per jaar
508 of meer
200 tot 508
38 tot 200
0 tot 38
-68 tot 0
-164 tot -68
-437 tot -164
minder dan -437
Jobs – concentration vs. trend
Results concentration scenario
43 CIE4801 Land use and transportation models
2.1
Choice modelling: firm location behaviour
44 CIE4801 Land use and transportation models
Factors influencing location choice of firms
• Characteristics of the firm • Size • Growth • Age • Sector
• Characteristics of the location • Vicinity of infrastructure • Accessibility of the market and of employees • Neighborhood of other firms
45 CIE4801 Land use and transportation models
Aggregated approach: All firms in a zone
Disaggregated approach: Individual firms
SHPmigration92less then 5 employeesover 5 employees
firms92.txt Events0 - 56 - 2526 - 50
51 - 100
101 - 978
46 CIE4801 Land use and transportation models
Data available in the Netherlands
• LISA National information system of employment, contains information on the whole firm population
• LMS National model system, contains information on accessibilities
• GIS Geographic information system, contains information on location of railways, freeways, etc.
47 CIE4801 Land use and transportation models
Vicinity of infrastructure
48 CIE4801 Land use and transportation models
Accessibility Logsum business trips:Logs / <None>
< 6.5
6.5 - 7.0
7.0 - 7.5
7.5 - 8.0
> 8.0
railway
motorway
Study area
0 3 6 9 121.5
Kilometers
49 CIE4801 Land use and transportation models
Neighborhood of other firms
specialization / diversity
50 CIE4801 Land use and transportation models
Specialization Railway
Highway
PS Business Services Rb <7.5 minutes
< 0.5
0.5 - 1.0
1.0 - 1.5
> 1.5
51 CIE4801 Land use and transportation models
Diversity Railway
Highway
Diversity Index Range Band <7.5 minutes
0.750001 - 1.060000
0.500001 - 0.750000
0.440001 - 0.500000
0.030000 - 0.440000
52 CIE4801 Land use and transportation models
Firm location choice model
Stay Move
Firm
Location 1 …… Location N
move probability
location probability
53 CIE4801 Land use and transportation models
Move probability
stay
move0 1 2 3 4
0
(1/ ) ...fi
fi f f f i
V
V Gr Age Sec Accβ β β β β
=
= + + + + +
Gr = firm growth Age = firm age Sec = firm sector Acc = location accessibility
firm characteristics location characteristics
movemove
move stay move
exp( ) 1exp( ) exp( ) 1 exp( )
fifi
fi fi fi
VP
V V V= =
+ + −
f – firm index i – location index
54 CIE4801 Land use and transportation models
54
Estimted parameters Firm mobility
-6.000 -5.000 -4.000 -3.000 -2.000 -1.000 0.000 1.000 2.000
CONSTANT
FIRM CHARACTERISTICS
Log of size
Grow th rate
1 / age
INDUSTRY SECTOR
Finance
Business services
Government
Education
Health service
General Services (ref.)
ACCESSIBILITY
α-location; near trainstation
β-location; near trainstation & highw ay onramp
γ-location; near highw ay onramp
ρ-location; neither
URBANISATION ECONOMIES
Logsum business and commuting trips
LOCALISATION ECONOMIES
Diversity w ithin < 7,5 min.
Specialisation w ithin < 7,5 min.
Significant Non significant
Move probability Parameter estimates
55 CIE4801 Land use and transportation models
Location probability
location1 2 ...sij s ij s jV Dist Accβ β= + +
Dist = relocation distance Acc = location accessibility
s – firm sector index i – current location index j – new location index
locationlocation
location
exp( )exp( )
sijsij
sijj
VP
V=∑
56 CIE4801 Land use and transportation models
56
-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5
MIGR A T ION A TTR IB UTE
D is tance to orig inal loc.[km1/2]
A C C ES S IB ILIT Y A TTR IB UTE
near s tation
near s tation & onramp
near onramp
neither
UR B ANIS A T ION EC ONOMIES
Log sum bus iness and commuting trips
LOC A LIS A T ION EC ONOMIES
D ivers ity firms within 7,5 min.
S pecialisation firms within 7,5 min.
C OMPET ING DES T INA T IONS
C entrality parameter Teta
Signif icant Non signif icant
Location probability Parameter estimates (sector Business)
57 CIE4801 Land use and transportation models
57
Location probability Parameter estimates (sector Finance)
-2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0
MIGR A T ION A TTR IB UTE
D is tance to orig inal loc.[km1/2]
A C C ES S IB ILIT Y A TTR IB UTE
near s tation
near s tation & onramp
near onramp
neither
UR B ANIS A T ION EC ONOMIES
Log sum bus iness and commuting trips
LOC A LIS A T ION EC ONOMIES
D ivers ity firms within 7,5 min.
S pecialisation firms within 7,5 min.
C OMPET ING DES T INA T IONS
C entrality parameter Teta
Signif icant Non signif icant
58 CIE4801 Land use and transportation models
Location choice companies (result of a more recent study)
• For the choice to consider another location characteristics of companies themselves are dominant
• For the location choice accessibility attributes play a role.
• Main accessibility attributes: • Distance to original location • Distance to freeway on-/off-ramp • Distance to railway station
• financing, education, catering • Accessibility by car
• business, financing, manufacturing, logistics, trading and retail
M. De Bok, 2007
59 CIE4801 Land use and transportation models
2.2
Choice modelling: Household location behaviour
60 CIE4801 Land use and transportation models
Household location choice model
Stay Move
Household
Location 1 …… Location N
move probability
location probability
61 CIE4801 Land use and transportation models
Location probability
location1 2 3 ...hij h ij h j h jV Dist Acc Ethβ β β= + + +
Dist = relocation distance Acc = location accessibility Ethn = similarity ethnical background
h – household type index i – current location index j – new location index
locationlocation
location
exp( )exp( )
hijhij
hijj
VP
V=∑
62 CIE4801 Land use and transportation models
Relocation distance
Workplacehead
Olddwelling
dmaxdmax
95%
63 CIE4801 Land use and transportation models
63
Location accessibility
64 CIE4801 Land use and transportation models
64
Other factors
65 CIE4801 Land use and transportation models
Location choice households (result of a more recent study)
• Characteristics of house and neighbourhood are dominant
• Accessibility plays a limited role: • Distance to previous house • Distance to work by car
• More advanced modelling provides more insight • Distance to station (for household without a car)
B. Blijie & De Vries, 2006
66 CIE4801 Land use and transportation models
Some overall conclusions
• Shift towards disaggregated approaches (individual firms and households)
• Relocation distance is preferably small • Accessibility plays a role in the location choice behavior
• Accessibility is relevant for the location choice of firms, not in the decision to move
• Best accessible locations may not be preferred by households
67 CIE4801 Land use and transportation models
3.
Circle of Wegener revisited
68 CIE4801 Land use and transportation models
Build Choice
location users
Move
Activities
Ability to travel
Choice trip
Choice destina-
tion Choice mode
Choice route/time
Travel time & costs
Accessibility
Attractiveness
Choice location
investors
Choice processes
69 CIE4801 Land use and transportation models
Empirical evidence?
• Databases of observed behaviour
• Observed or generated choice alternatives
• Formulating choice models (logit models)
• Estimating perception factors or weights
• Resulting models of attributes having significant weights
70 CIE4801 Land use and transportation models
Location choice investors
• Different decision makers thus different objectives • Project developers • Authorities
• I’ve got no empirical evidence for this type of choice, however…
• Given the bi-level nature of the decision problem they should consider the choice behaviour of (future) users of the location
71 CIE4801 Land use and transportation models
Location choice companies
• For the choice to consider another location characteristics of companies themselves are dominant
• For the location choice accessibility attributes play a role.
• Main accessibility attributes: • Distance to original location • Distance to freeway on-/off-ramp • Distance to railway station
• financing, education, catering • Accessibility by car
• business, financing, manufacturing, logistics, trading and retail
M. De Bok, 2007
72 CIE4801 Land use and transportation models
Location choice households
• Characteristics of house and neighbourhood are dominant
• Accessibility plays a limited role: • Distance to previous house • Distance to work by car
• More advanced modelling provides more insight • Distance to station (for household without a car)
B. Blijie & De Vries, 2006
73 CIE4801 Land use and transportation models
Trip choice
• To travel or not to travel…..
• No impact of accessibility • Recall constant number of trips per day
• Although, for some trip purposes an effect has been found, still having a minimal impact
Willigers & De Bok, 2009
74 CIE4801 Land use and transportation models
Destination choice
• Distance/time has a substantial impact: the larger the distance (or the longer the time), the lower the probability of choosing the destination (assuming similar attractiveness of the destinations)
• Car accessibility is usually dominant, except for households without a car
• Alternative modes improve accessibility, however, net impact on total attractiveness is limited
Ortúzar & Willumsen, 2001
75 CIE4801 Land use and transportation models
Mode choice
• Clear role of mode availability • Recall impact of ‘captiveness’
• Clear role for quality (travel times) of each mode
• However, preferences for specific modes play a major role too! • Recall impact of ‘captiveness’
Ortúzar & Willumsen, 2001
76 CIE4801 Land use and transportation models
Route choice
• Clear role of travel time
• In public transport different weights for trip time elements • 2.2*Ta+1.5*Tw+Ti+2.3*Twt+5.9*Nt+1.1*Te
• Train trips are in fact multi-modal (80% of train travellers uses another mode to travel to or from the station)
• Consequence of multimodality……….
77 CIE4801 Land use and transportation models
Main components utility function multi-modal route choice
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Trip parts U5lity components
Sta5on type indicators
In-‐vehicle 5mes
Frequency related
Parking and BTM costs
Mode and service indicators
Ac5vity-‐end
Train part
Home-‐end S. Hoogendoorn-Lanser, 2005
78 CIE4801 Land use and transportation models
Conclusion
• There is empirical evidence for the mechanism in Wegener’s circle
• However, in nearly every choice situation many other factors play a role, and often quite dominantly
• Often simple and more specific accessibility indicators are significant: • distance to former location, distance to freeway
• Mechanism is stronger for car accessibility, however: • Increasing car usage leads to congestion, thus making other
locations more attractive