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1)-The Basic Features : Agent-Based Microsimulation Model Continuous Time Representation

5)- Activity Generation, Allocation and Location Household Based Activity Generation: Poisson Regression / Negative Binomial Regression / Inter-Activity Hazard Models for Shopping, Recreational Activities etc. Regression Models for Serve-Dependent Activities etc.

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1)-The Basic Features : Agent-Based Microsimulation Model Continuous Time Representation

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  1. 5)-Activity Generation, Allocation and Location • Household Based Activity Generation: • Poisson Regression / Negative Binomial Regression / Inter-Activity Hazard Models for Shopping, Recreational Activities etc. • Regression Models for Serve-Dependent Activities etc. • Household Based Activity Allocation: • Rule-Based Allocation Model • Generalized Linear Latent and Mixed Model (Multilevel-multivariate Latent Variable Model); Multivariate Ordered Probability Model • Tour-Based Activity Location Choice Model Considering Potential Utility of Possible Locations. • Activity Generation-Allocation-Location Selection Processes are in General Project Based. • Scheduler Adjusts the Project-Specified Episode Attributes based on the Dynamic Interactions with the Environment • 1)-The Basic Features: • Agent-Based Microsimulation Model • Continuous Time Representation • Dynamic Interactions among the Model Components • Event-Driven Sequential Process • Provision of Feedback and Learning • 2)-The Component Steps: • From Projects to The Scheduler  Skeleton Schedule • From Scheduler to The Projects  Updating Perception of the Environment • The Projects, The Individual and The Household  Generation and Allocation of Activities  Formation of Weekly-Daily Agenda • The Scheduler and The Dynamic Traffic Microsimulator ---- Dynamic Scheduling and Rescheduling  Daily Scheduling Time Frame with Weekly Rescheduling Option AN INTEGRATED DYNAMIC MODEL FOR ACTIVITY-BASED TRANSPORTATION PLANNING AND POLICY ANALYSIS K. M. Nurul Habib & Eric J. Miller • 6)-Activity Scheduling and Rescheduling • The Provisional Activity Scheduling is based on Rule-Based Methods as in TASHA with Tour-Based Model Choice Model (See Miller & Roorda, 2003). • Activity Rescheduling model uses the Concept of Activity Utility to Determine Priority, Flexibility and Precedence. The Corresponding Mode Choice Correction is Based on Rules • The Utility of Activity Episodes is Based on Dynamic Utility with Multiple Prior Concept (Habib & Miller, 2005) • Activity Utility has Two Components: Goal and Process Utility 3)-The Planning Horizon: Typical Week The ILUTE Component • Inter-Day Activity Reallocation captures the day-to-day dynamics + Goal Utility Process Utility Utility • 4)-Daily Skeleton Schedule Formation: • Hazard-Based Duration Models for Daily Routine Activities—Ensuring the Incorporation of Policy Variables at this Level • Iterative Microsimulation of Start-Time and Duration of the Skeleton Components from the Modelled Duration Distributions. • The Typical Daily Skeleton Schedule Components are: Work/School and Night Sleep • Function of the Project Type & Attributes • Function of Time, Starting from The Project Generation  Models the Stress To Compel Execution or Deletion Dynamically Determines Priority, Flexibility and Precedence • Function of the Activity Type & Attributes • Function of the Episode Duration • Explicitly Recognizes the Uncertainty and Risk Aversion Attitude • 7)-Concluding Remarks • The Unscheduled Episodes in the Daily Agenda Enters in the Following Day Agenda and may Remain as Latent Activity Demand for the Following Days It Ensures the Day-to-Day Dynamics of Activity Generation Process • Dynamic Traffic Microsimulator Ensures the Consideration of Within-Day Dynamics in Activity Scheduling Process • Activity Scheduling-Rescheduling Process is Hybrid The Scheduling Process is Rule-Based but the Rescheduling Process Considers Utility-Based Priority and Precedence Measurements. • The Econometric Methods of Generating Activity Episodes and Attributes Ensure Policy Sensitivity by Incorporating Policy Variables Skeleton Component Distribution for Part-Time Workers-Hazard Model, (Habib & Miller, 2005) Skeleton Component Distributions for Full-Time Workers-Hazard Model, (Habib & Miller, 2005) The Daily Activity/Travel Scheduler

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