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Activity Based Modeling: A Brief Introduction

Activity Based Modeling: A Brief Introduction. Mike Neidhart, PhD, AICP Volusia County MPO. Florida Model Task Force Meeting November 29, 2007. MTF – 2 Track Focus. MTF work can be divided into 2 frames of thought (or tracks/focus)

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Activity Based Modeling: A Brief Introduction

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  1. Activity Based Modeling: A Brief Introduction Mike Neidhart, PhD, AICP Volusia County MPO Florida Model Task Force Meeting November 29, 2007

  2. MTF – 2 Track Focus • MTF work can be divided into 2 frames of thought (or tracks/focus) • Research based on how we can incrementally improve our existing model framework • Research model frameworks/philosophies that are 5-10 years into the future such as incorporation of meso and/or micro models, Activity Based models, etc. • This presentation will be on Activity Based Models

  3. AMB Background • Activity Based Models (ABM) predict travel behavior as a derivative of activities (i.e., derived demand) • Travel decisions are part of a broader process based on modeling the demand for activities rather than merely modeling trips

  4. AMB Background Continued • ABM belongs to the 3rd generation of travel demand models • Trip based 4-step models • Disaggregate trip based models • Activity based models • In ABM the basic unit of analysis is the activities of individuals/households

  5. AMB Background Continued • ABM are based on the theories of Hägerstrand (1970) and Chapin (1974) • Hägerstrand focused on personal and social constraints • Chapin focused on opportunities and choices • Theory is that activity demand is motivated by basic human desires for: survival, ego gratification, and social encounters

  6. Activity Demand • Unfortunately, it is difficult to model activity demand • However, research indicates that household membership moderates activity demand such that: • Households influence activity decisions • Effects differ by household type, size, membership relationship, age, and gender • Children impose significant demands and constraints on others in the household

  7. ABM Approach (slide content: E. Zwerts) • Travel demand is derived from activities that individuals need/wish to perform • Sequence/patterns of behavior, not individual trips, are the unit of analysis • Household and other social structures influence travel and activity behavior • Spatial, temporal, transportation, and interpersonal interdependencies constrain activity/travel behavior

  8. ABM Approach (slide content: E. Zwerts) • Activity based approaches reflect the scheduling of activities in time and space • Activity based approaches aim at predicting which activities are conducted where, when, for how long, with whom, by mode, and ideally also the implied route decision

  9. ABM Paradigms (slide content: G. Jovicic) • ABM rely on the following 5 paradigms: • Travel is a derived demand from activity participation • Focus is on the sequence of activities/events • Activities are both planned within the context of the household • Activities are spread over a 24-hour period in a continuous manner rather than using “peak” and “off-peak” periods • Travel choices are limited in time, space, and by personal constraints

  10. Hypothetical Travel Day Graphic by Goran Jovicic

  11. How To Model Trips (slide content: G. Jovicic) • Trip-based model would model all 7 trips independent of the other trips • Tour-based model would model Tour 1 and Tour 2 independent of each other, while the Work Tour would be modeled as two independent trips • ABM would model the 4 activities and associated trips (work, meeting, shopping, and movie) as part of the same decision process

  12. Criticism of Trip Based Models • Poor forecasting accuracy of trip based models most likely due to the model’s theoretical mis-specification • Trip based 4-step and disaggregate models have a fundamental error – they analyze each trip independently of other trips made by the individual • Trip based models fail to recognize the linkages among trips, between trips, and the activity participation by the individual

  13. Advantages of ABM • Theoretically based on human behavior • Better understanding and prediction of traveler behavior • Based on decision-making choices present in the “real-world” • Use of disaggregate data • Inclusion of time-of-day travel choices

  14. References • Jovicic, G.: Activity Based Travel Demand Modelling: A Literature Study. Danmarks TransportForskning Publishing, Note 8, 2001. • Bowman, J. L. & Ben-Akiva, M.: Activity Based Travel Forecasting. tutorial on activity based travel forecasting taught at conference of same name in New Orleans, Louisiana, June 2, 1996. • Shiftan, Y.; Ben-Akiva, M.; Proussaloglou, K.; deJong, G.; Popuri, Y.; Kasturirangan, K. & Bekhor, S.: Activity Based Modeling as a Tool for Better Understanding Travel Behaviour. Paper presented at the 10th International Conference on Travel Behaviour Research, Lucerne, August 2003. • Zwerts, E. (in cooperation with E. Moons & D. Janssens): Activity-Based Modelling: An Overview. PowerPoint presentation, Limburgs Universitair Centrum, Universitaire Campus, gebouw D, 3590 Diepenbeek, Belgium.

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