16th TRB Planning Applications Conference - 2017 A Utility-Theory Consistent Model of Activity Frequency, Purpose, and, Duration Choices Rajesh Paleti Chaitanya Paleti 16th TRB Planning Applications Conference - 2017 11/28/2018

Activity Based Modeling (ABM) ABM Models – Two major components Planning Stage – frequency, purpose, duration Scheduling Stage – Mode, destination, departure time Work Shopping Discretionary T1 Mins T2 Mins Tn Mins Activity 1 Activity n Activity 2 Three dimensions to the activity-travel choices that people make at the planning stage out-of-home activity participation frequency, activity purpose of the activity episodes, and duration associated with each episode 11/28/2018 2017 TRB Planning Applications Conference

Past ABM Research & Applications Work Shopping Discretionary t1 Mins t2 Mins tn Mins Activity 1 Activity n Activity 2 Frequency Activity Purpose Duration Count Data Models Choice Models Duration Models Poisson’s Models; Negative Binomial Models Multinomial Logistic (MNL) Models Regression/ Hazard Duration Models Consistent with Utility Theory 11/28/2018 2017 TRB Planning Applications Conference

2017 TRB Planning Applications Conference Limitations Activity Frequency, Purpose, and, Duration choices are inter-related in nature Models used to predict frequency and duration are not consistent with Random Utility Theory 11/28/2018 2017 TRB Planning Applications Conference

Current Study Objectives Propose a new modeling framework - a single utility theory consistent model for all the dimensions of activity-time use decisions Demonstrate that the joint model offers superior data fit and prediction accuracy than standard models 11/28/2018 2017 TRB Planning Applications Conference

2017 TRB Planning Applications Conference Virginia NHTS Data 11/28/2018 2017 TRB Planning Applications Conference

2017 TRB Planning Applications Conference Key Empirical Results Higher auto ownership levels, higher income levels, regular internet use lead to more OH activity episodes Presence of children 0 to 5 years, bachelor and higher educational attainment, older age (> 65 years) decrease # of OH activity episodes Several socio-demographics including age, gender, household composition, income, educational attainment, presence of children, auto ownership impact activity purpose and duration Higher expected utility from activity participation will result in more OH activity episodes Statistical Fit Comparison Log-likelihood ratio test and Bayesian Information Criterion (BIC) statistics demonstrate superior data fit in the joint model compared to independent count and MNL models 11/28/2018 2017 TRB Planning Applications Conference

2017 TRB Planning Applications Conference Next Steps Validate the estimated models on 50% data retained for data validation Predict using the models and compare with observed frequency, purpose, and duration choices Compare the model performance with standard models Test for traveler-specific unobserved factors that impact all activity purpose and duration choices  “unobserved heterogeneity” 11/28/2018 2017 TRB Planning Applications Conference

2017 TRB Planning Applications Conference Thank You! For more information: Rajesh Paleti rpaleti@odu.edu Chaitanya Paleti, P.E. Chaitanya.Paleti@ch2m.com 11/28/2018 2017 TRB Planning Applications Conference