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A Model of Within-Households Travel A Model of Within-Households Travel Activity Decisions Capturing Interactions Activity Decisions Capturing Interactions

Between Household HeadsBetween Household Heads

A Model of Within-Households Travel A Model of Within-Households Travel Activity Decisions Capturing Interactions Activity Decisions Capturing Interactions

Between Household HeadsBetween Household Heads

Renni Anggraini, Dr.Theo Arentze, Prof.H.J.P. Timmermans

Presented at DDSS ’06 Conference, 4-7 July 2006, Heeze, The Netherlands

Urban Planning Group

Faculty of Architecture, Building & Planning

Technische Universiteit Eindhoven (TU/e)

The Netherlands

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Activity-based approachActivity-based approachActivity-based approachActivity-based approach

Travel is derived from the demand for activities that individual needs to perform

Sequences or a pattern of behavior is the relevant unit of analysis, not individual trips

Household and other social structures influence travel and activity behavior

Spatial, temporal, transportation, and interpersonal interdependencies constrain activity-travel behavior

Activity-based approach reflect the scheduling of activities in time and space

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ALBATROSSALBATROSSALBATROSSALBATROSS

Albatross: A Learning-based Transportation Oriented Simulation System (Arentze and Timmermans, 2000)

One of the fully operational activity-based models

Developed for the Dutch Ministry of Transportation, Public Work and Water Management as the operational system for transport demand forecasting

Two major components defining a schedule for each individual for fixed and flexible activities

Decision tree as a formalism to model the heuristic choice

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Limitation of AlbatrossLimitation of AlbatrossLimitation of AlbatrossLimitation of Albatross

Household decision making process is not fully captured in terms of:

Activity allocationTask allocationCar allocationJoint travelActivity participation

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ObjectivesObjectivesObjectivesObjectives

To elaborate and expand Albatross in the context of household level decision making focusing on maintenance activities and related travel

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Choice FacetsChoice FacetsChoice FacetsChoice Facets

Activity generationTask allocationTrip-chainingResource allocation and Mode

choice

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Activity GenerationActivity GenerationActivity GenerationActivity Generation

The model predicts the maintenance activities conducted in a household for a given day

The result is a description of activities performed at the household level for a particular day

The activities are a selection of an exhaustive list of maintenance activities considered by households

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Task AllocationTask AllocationTask AllocationTask Allocation

m1 m2 ... mn

P1 x11 x12 ... x1n RT1 = x11 + x12+…+x1n

P2 x21 x22 ... x2nRT2 = x21 + x22+…+x2n

CT1= x11 +x21 CT2= x12 +x22 ... CTn= x1n +x2n T = RT1+RT2

Table 1. Matrix representation of task allocation pattern

Table 2. Example of task allocation matrix pattern

m1 m2 m3 m4

P1 1 0 1 0 2

P2 0 1 0 1 2

1 1 1 1 4

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Trip-chaining choicesTrip-chaining choicesTrip-chaining choicesTrip-chaining choices Trip-chaining decision as a choice between yes/no linking

a given pair of activities.

The existence of other activities (if any) take into account

Trip-chaining choices description:

otherwise

jwithlinkednotisiifcij 1

0

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Trip-chaining choicesTrip-chaining choicesTrip-chaining choicesTrip-chaining choices

Every ij pair of trip-chaining variables must meet the following logical constraints: cij = cji

If cij =1 and cjk =1 then cik =1 (for every 3rd activity k)

If cij =0 and cjk =0 then cik =0 (for every 3rd activity k)

m1 m2 m3 m4 O1 O2 O3

m1 1 0 0 0 1 0 0

m2 1 0 1 0 0 1

m3 1 0 0 0 0

m4 1 0 0 1

O1 1 0 0

O2 1 0

O3 1

Table 3. Matrix representation of activities performed

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Trip-chaining choicesTrip-chaining choicesTrip-chaining choicesTrip-chaining choices

m1 m2 m3 m4 O1 O2 O3

m1 1 0 0 0 1 0 0

m2 0 1 0 1 0 0 1

m3 0 0 1 0 0 0 0

m4 0 1 0 1 0 0 1

O1 1 0 0 0 1 0 0

O2 0 0 0 0 0 1 0

O3 0 1 0 1 0 0 1

Table 4. Matrix activities performed to identify # of tours

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Identify the activity combinations 1. m1, O1

2. m2, m4, O3

3. m3

4. m2, m4, O3

5. O1, m1

6. O2

7. m2, m4, O3

1. m1, O1

2. m2, m4, O3

3. m3

4. O2

The possible activity combinations P1

P2

P1

P2

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Resource Allocation & Mode ChoiceResource Allocation & Mode ChoiceResource Allocation & Mode ChoiceResource Allocation & Mode Choice

Households classification can be grouped into: Drivers > Cars Drivers = Cars Cars > Drivers No cars

Some variables take into account (gender role, work status, income, & complexity of the activity agenda,etc)

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Some factors influencing resource allocation and mode choice: The activity-travel conducted either jointly or independently If one agent does not use car, the other agent can freely use Both agents possible choose not to use the car

Mode choice set assigned to # of tours scheduled for the household-day:

Resource Allocation & Mode ChoiceResource Allocation & Mode ChoiceResource Allocation & Mode ChoiceResource Allocation & Mode Choice

},...,,{ 21 zvvvV

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Decision TreesDecision TreesDecision TreesDecision Trees

Some methodso C4.5 : Information Gaino CART : Gini-Indexo CHAID : Chi-Square

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Overview properties of Tree Induction Overview properties of Tree Induction AlgorithmsAlgorithms

Overview properties of Tree Induction Overview properties of Tree Induction AlgorithmsAlgorithms

Property C4.5 CART CHAID

Type of splits multiway binary multiway

Allow groupings of attribute values

yes yes yes

Can handle continuous var.

yes yes no

Split criterion Information gain ratio Gini-index Significance value of chi-

square

Use growing/pruning strategy

yes yes no

Use different cases for pruning

no yes

Pruning criterion Predicted number of errors

Misclassification cost complexity of the tree

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Further ResearchFurther ResearchFurther ResearchFurther Research

Involving all activities, not only maintenance activities

Expanding it into much broader choice facets such as travel participation and activity participation, duration of time, time of day, and route choice

Estimating the empirical analysis by using decision tree induction method

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ConclusionsConclusionsConclusionsConclusions

The system explicitly describes what maintenance activities perform and who performs which task

The organization of activities in trip chains resulting in the number and activity composition of tours that each agent carries out during the day

Modeling resource allocation and mode choice allow a better integration of various facets in activity-travel decisions

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Thank you for your attention

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Review of Existing ApproachesReview of Existing ApproachesReview of Existing ApproachesReview of Existing Approaches

Srinivasan, S., and Bhat, C.R., (2005). Investigating the in-home and out-of-home maintenance activity generation by examining the duration time invested by male-female household heads.

Zhang, J., Timmermans, H., Borgers, A., 2005

Investigating the task allocation and time use spent by male and female

Ettema, D., and Van der Lippe, T., 2006

Investigating the household heads interaction by using three hypotheses: traditional role expectations, higher qualified job, low accessibility

etc