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ILUTE Land use – Transportation Integrated models (The competition to ILUTE) MAMAMIA - module 3 Microsimulation experiences Ilan Elgar

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Page 1: ILUTE Land use – Transportation Integrated models (The competition to ILUTE) MAMAMIA - module 3 Microsimulation experiences Ilan Elgar

ILUTE

Land use – Transportation Integrated models (The competition

to ILUTE)

MAMAMIA - module 3

Microsimulation experiences

Ilan Elgar

Page 2: ILUTE Land use – Transportation Integrated models (The competition to ILUTE) MAMAMIA - module 3 Microsimulation experiences Ilan Elgar

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Introduction

• A sort of definition- Integrated land use-transportation models attempt to predict the dynamics of land use patterns and travel patterns, and their interactions.

• The spatial location of land use constitutes the choice set from which each individual can choose where to perform his activities.

• Land use patterns influence activity travel patterns, through providing opportunities and constituting constraints.

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• The choice of a destination is important for the feasibility of a particular function at a particular location. If there is a shift to a different activity location, there will be a change in land use patterns and as a result a second change to travel behavior.

All the above should have made the field very attractive to research and practice. However…

• Integrated land use-transportation models has always been a weak field of interest in comparison to transport demand, which usually treat land uses as exogenous.

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Why the field is so under appreciated?• It is inherently very complex and thus difficult to

model

• Models require a tremendous amount of data, and time before any test can be performed.

• Models are expensive to implement - a big investment in people, data and equipment is required

• The models support mainly long term and strategic planning decisions. Such decisions are infrequent in most urban areas - the return on investment is potentially low.

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Field Overview

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The first wave –aggregate spatial interaction based models

• Aggregated models

• Without any or with Partial transportation side

• Gravity models

• Lowry, Garin, TOMM, PLUM, ITLUP/DRAM/EMPAL/METROPILUS, IRPUD*, LILT*

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Lowry• Three types of sectors - population, service

employment and manufacturing employment.• Three types of corresponding land uses –

residential, service and industrial.• The model allocates activities to zones according

to the potential of the zone, subject to capacity constraints and maximum density.

• Time treatment- all activities respond to changes in potential in a given period.

TOMM- same model structure, but disaggregated population into a few socio economic groups. Time treatment- only a certain proportion respond in the first year, to account for inertia.

Page 8: ILUTE Land use – Transportation Integrated models (The competition to ILUTE) MAMAMIA - module 3 Microsimulation experiences Ilan Elgar

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The second wave – utility maximizing multinomial logit based models

• Combinations of aggregate and disaggregate

• Modules involving logit and microsimulation

• Elaborated transportation microsimulation

• MEPLAN, TRANUS, BASS/CUF, MUSSA/RUBAN, CATLAS/METROSIM, DELTA, UrbanSim, IMREL, TILT, Uplan

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The third wave – towards activity based, microsimulation models

• Mostly disaggregate

• Microsimulation oriented

• Very focused on activity

• ILUTE, Ramblas, ILUMASS, The Irvine simulation models

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Ramblas• Simulates the whole Dutch population (16m). • input to the model is the distribution of types of HH across

the different kinds of dwellings per zone and the dwelling distribution in the zone. These variables and their changes are external.

• Attributes of zones are variables that can be manipulated by planning.

• The spatial distribution of activities and trips are treated as dependent variables. Thus policy decisions that will affect zone attributes will change activity patterns

• The micro simulation occurs in two steps. In the first agendas are chosen for each simulated individual. In the second step a schedule and location for each activity is being determined.

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MEPLAN

Treatment of space- the state of Oregon and a ring of 50 miles surrounding it, is divided to three space unit types. Each space definition is used in different parts of the model. Each of these forms covers the whole of the model area.

• Grid cells- (14.5m) are 30m*30m in built areas and 300*300 otherwise. Each cell represents only one land use.

• Link tributary areas- containing the O-D of trips feeding the links in the transport system

• Zones- roughly traffic zones (about 3200). Connected to the transport network using centroid connectors

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MEPLAN-CONT.

Treatment of time- the model evolves by yearly steps.

• The characteristics of the system in year t+1 are partly influenced by the conditions in year t.

• Some of the simulation processes evolve through shorter than one year time steps, so they are performed a number of times within a one year period.

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MEPLAN-CONT.

Mechanics of the system- the behavior of individuals and groups is based on utility values. A utility value is a dependent value in a utility function; the utility function is constructed through alternative attributes and individual sensitivities.

Five different categories of utility are defined:

• “Rutility”- allocate aggregate quantities. Attribute variables are either average or zonal, while sensitivity values are typical values for the category of aggregate quantity being allocated

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MEPLAN-CONT.• “Zutility”- used for agent based microsimulation

of individuals and households, the attribute values are average or zonal, but the sensitivity values are specific to the person or HH

• Two other utility values are used for traffic assignments where one is for aggregate zone to zone flows and the other is for path selection of individuals

• “Cutility”- used for microsimulation of land development decisions. The attribute values are cell specific while the sensitivity values are typical values assigned to the developers as a category

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MEPLAN-CONT.

Model structure- The model is constructed of seven separate modules. Each of The modules is connected to the data store component and through it to each of the other components.

This design allows flexibility since it allows different approaches in each component: equilibrium or disequilibrium, aggregate or disaggregate and statistical models or microsimulation

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MEPLAN Modules

1. Regional economics and demographics- provides regional control totals for production and import-export by economic sector, migration etc.

The module requires exogenous forecasts as inputs and includes simple macroeconomic models to assist with trade flow predictions.

The module is a combination of econometric and input-output models

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2. Production allocations and interactions- The module determines the total regional production of all sectors and then allocates them.

Commodities (goods, services, labor and space) flow from production locations to exchange locations to consumption locations.

Exchange locations (fictitious) represent the places where prices for those commodities are being set. Prices for each commodity in each zone are updated based on demand and supply

The allocation to locations is being done through logit models that take into account the exchange prices and the transportation costs.

The ability of labor supply to change in each zone beyond certain limits in a given year is constrained.

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3. Household Allocations Module- determines for each year:

• Changes in HH and members characteristics • Specific sensitivities • HH actions regarding home location • Car ownership change • Employment and school status and location for

each HH member

The module works through microsimulation of each HH member in each time period

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4. Land development Module- determines the changes from one year to the next.

• The supply of built space is fixed for a given year.

• Other modules determine the prices of different spaces in each zone based on supply; the land development model has to adjust the quantity of space in the zone over time in response to price changes.

• The process is done for each grid cell.

• Logit models determine whether a cell will be redeveloped, if so into what type of space and the quantity of the new development in the cell.

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5. Commercial movements Module- determines truck movement during a representative workday for each year.

• A fully disaggregate list of truck movement is synthesized providing: – vehicle type– start and end links– starting time

– commodity carried for each truck

The origin and destination of each truck is randomly attributed to particular grid cell that have a consistent space type with the shipped commodity

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6. Household travel Module- creates a list of specific individual trips during a representative workday for each year.

• For each trip: – start and end links – starting time– tour mode – vehicle occupancy if auto mode

The process starts with scheduling of activities for each household member (first activity pattern then duration).

Each home based and work based tour is considered separately.

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7. Transport supply Module- determines transportation network loadings given transport demands from household and commercial travel modules.

• It uses a micro assignment at the level of the individual vehicle and traveler.

• Primary mode of trip dictates which network links are available for the trip.

• In the first stage of the trip assignment an aggregated zone to zone assignment is done. The equilibrium set of links is the starting point of the micro simulation assignment.

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UrbanSim

Treatment of space-location is determined using grid cells of 150 by 150 meters, the cell size can be modified

• The location grid allows explicit cross referencing of other spatial features including planning and political boundaries such as city, county, traffic zones, and urban growth boundaries, as well as environmentally sensitive areas

• Each cell is classified according to its main development type and the density of the development in it

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UrbanSim cont.

The data store represents each household in the metropolitan area as an individual object, with the primary characteristics relevant to modeling location and travel behavior: – household size– number of workers– presence of children– household income, etc

• The household list is synthesized by integrating census household-level data.

• Employment is represented in the data store as individual records for each job and its employment sector.

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• The data store maintains an explicit accounting of real estate and occupants, linking individual households to individual housing units, and individual jobs to job spaces.

• When jobs or households are predicted to move, the space they occupy is flagged as becoming vacant, and when they are assigned to a particular housing unit or job space, that space is reclassified as occupied.

• The integrated data store of households, jobs, land, and real estate is what the model components update over time.

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• Some of the models, such as the economic and demographic transition models, are aggregate, nonspatial models. Other components, such as location choice, are discrete choice models of an agent making choices about alternative locations.

• Inputs to the model include:– base year data store– control totals derived from regional economic forecasts

from an external macroeconomic model– travel access indicators derived from external travel

demand models – scenario policy assumptions regarding development

constraints arising from land use plans – environmental constraints etc.

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• The individual modules are: – An accessibility module which predicts the pattern of

accessibility by auto ownership level – An Economic and Demographic Transition Module predicts the

creation or loss of households and jobs by type – Household and Employment Mobility module predicts the

movement of households or jobs within the region – Household and Employment Location Choice module predicts

the location choices of households and jobs from the available vacant real estate

– Real Estate Development module, the location, type, and quantity of new construction and redevelopment by developers

– Land Price module determines the price of land at each location

The Model Coordinator, manages the individual model components and handles the scheduling and implementation of events.

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UrbanSim cont.• The model interprets the cumulative impact of

the policies by reflecting the most restrictive policies that apply to a given grid cell.

• In addition to development constraints, the scenario inputs include regional control totals from the external macroeconomic models and assumptions about the space utilization rates (such as square feet per employee for different development types).

• Transportation policy assumptions are incorporated in the external transportation model and are embedded in the travel time and utility outputs from the travel model that UrbanSim uses to calculate accessibility

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UrbanSim cont.The link between the model and the Travel Demand Model System is two way. Different accessibility values from the travel model will influence the decisions agents make resulting in different travel demand. This new demand will feed back into the travel model.

The external travel models provide travel times and utilities to the Accessibility Model.

The travel model is run to simulate a typical day every 5 years. This is due to the long running time of the model and the slow change in its products.

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Problems of integrated land use – transportation models

• Many models remain aggregate in nature and therefore are more of entropy maximization models than discrete choice utility maximization models.

• The field is behind in applying state of the art spatial choice models

• The behavioral and theoretical foundations of the field are still weak. Theory has been mostly borrowed instead of developed to specifically address the questions the field faces.

• Models are often criticized as being black-box models because of their complexity

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Questions• The behavior of search- does individuals are

really utility maximizers? (full knowledge, variety searching etc.)

• Business establishments- Should there be microsimulation of firms? (How do firms appear and disappear? How can we model the variety in firm sizes, production functions, management?)

• Motivations- Activities do not arise of their own, they arise out of motivations to satisfy different needs. Should we model motivations?

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• Perception of space- How do agents perceive location alternatives in space? How does the knowledge and accuracy of location vary across space? Is there a strong relation between distance and search cost (could it be used as a filter alternative)?

• Sensitivities- Does a long exposure to an alternative changes sensitivities to the attributes of that alternative? Do campaigns have effects on sensitivities in the long or short run and what are those effects?

• Public agencies- Hunt’s suggestion is to introduce an authority agent.

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The End

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