Type of Document Master's Thesis Author Paradkar, Rajan Author's Email Address firstname.lastname@example.org URN etd-01302002-231629 Title Alternative Methodology To Household Activity Matching In TRANSIMS Degree Master of Science Department Civil Engineering Advisory Committee
Advisor Name Title Hobeika, Antoine G. Committee Chair Baik, Hojong Committee Member Rakha, Hesham Ahmed Committee Member Keywords
- Activity Based Modeling
- CART Algorithm
Date of Defense 2001-06-15 Availability unrestricted AbstractTRANSIMS (Transportation Analysis and Simulation System) developed at the Los Alamos National Laboratory, is an integrated system of travel forecasting models designed to give transportation planners accurate and complete information on traffic impacts, congestion, and pollution. TRANSIMS is a micro-simulation model which uses census data to generate a synthetic population and assigns activities using activity survey data to each person of every household of the synthetic population. The synthetic households generated from the census data are matched with the survey households based on their demographic characteristics. The activities of the survey household individuals are then assigned to the individuals of the matched synthetic households. The CART algorithm is used to match the households. With the use of CART algorithm a classification tree is built for the activity survey households based on some dependent and independent variables from the demographic data. The TRANSIMS model assumes activity times as dependent variables for building the classification tree.
The topic of this research is to compare the TRANSIMS approach of using times spent in executing the activities as dependent variables, compared to match the alternative of using travel times for trips between activities as dependent variables i.e. to use the travel time pattern instead of activity time pattern to match the persons in the survey households with the synthetic households. Thus assuming that if the travel time patterns are the same then we can match the survey households to the synthetic population i.e. people with similar demographic characteristics tend to have similar travel time patterns.
The algorithm of the Activity Generator module along with the original set of dependent variables, were first used to generate a base case scenario. Further tests were carried out using an alternative set of dependent variables in the algorithm. A sensitivity analysis was also carried out to test the affect of different sets of dependent variables in generating activities using the algorithm of the Activity Generator. The thesis also includes a detailed documentation of the results from all the tests.
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