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CT-RAMP Model Components

Model Components Overview

CT-RAMP consists of 15 integrated model components that work together to simulate individual and household travel behavior. Each component addresses a specific aspect of the travel decision-making process.

Model Component Categories

CT-RAMP components are organized into logical categories based on their role in the travel decision hierarchy:

Long-term and Coordination Models

These models establish the context and constraints for daily travel decisions:

Component Purpose Key Decisions
Auto Ownership Vehicle availability Number of household vehicles
Coordinated Daily Activity Pattern (CDAP) Household coordination Person activity patterns

Tour Generation Models

These models determine what tours each person will make:

Component Purpose Key Decisions
Mandatory Tours Work and school tours Tour frequency by purpose
Joint Tours Multi-person household tours Joint tour participation
Individual Tours Personal discretionary tours Individual tour frequency
At-Work Subtours Tours during work hours Subtour generation

Spatial Choice Models

These models determine where travel occurs:

Component Purpose Key Decisions
Tour Destination Choice Primary destination selection Destination zones and locations

These models determine how travel occurs:

Component Purpose Key Decisions
Tour Mode Choice Primary transportation mode Tour-level mode selection
Trip Mode Choice Trip-level mode decisions Individual trip modes

Temporal Choice Models

These models determine when travel occurs:

Component Purpose Key Decisions
Tour Time-of-Day Departure and arrival timing Tour start and end times

Trip Detail Models

These models add complexity and realism to travel patterns:

Component Purpose Key Decisions
Stop Frequency Intermediate stop decisions Number of stops by direction
Stop Location Stop destination choices Stop locations and purposes

Model Execution Sequence

The components execute in a carefully orchestrated sequence to ensure proper dependencies:

graph TD
    A[Auto Ownership] --> B[CDAP]
    B --> C[Mandatory Tours]
    B --> D[Joint Tours]
    C --> E[Individual Tours]
    D --> E
    E --> F[Tour Destination]
    F --> G[Tour Mode Choice]
    G --> H[Tour Time-of-Day]
    H --> I[Stop Frequency]
    I --> J[Stop Location]
    J --> K[Trip Mode Choice]
    C --> L[At-Work Subtours]

    subgraph "Phase 1: Context"
        A
        B
    end

    subgraph "Phase 2: Tour Generation"
        C
        D
        E
        L
    end

    subgraph "Phase 3: Tour Characteristics"
        F
        G
        H
    end

    subgraph "Phase 4: Trip Details"
        I
        J
        K
    end

    style A fill:#e3f2fd
    style B fill:#f3e5f5
    style F fill:#e8f5e8
    style K fill:#fff3e0

Model Dependencies and Data Flow

Understanding how models depend on each other is crucial for system comprehension:

Data Dependencies

  • Auto Ownership requires: household demographics, accessibility measures
  • CDAP requires: person characteristics, auto ownership results
  • Tour Generation requires: CDAP patterns, person types, accessibility
  • Tour Characteristics require: generated tours, level-of-service data
  • Trip Details require: tour characteristics, stop purposes

Feedback Mechanisms

Some models have iterative relationships:

Accessibility Feedback : Tour destination and mode choice results update accessibility measures

Household Coordination
: Joint decisions influence individual tour generation and characteristics

Capacity Constraints : Transit ridership affects level-of-service for subsequent iterations

Common Model Patterns

All CT-RAMP components share common design patterns:

Choice Model Structure

Most components use discrete choice models with these elements:

Alternative Generation : Define the set of available choices (destinations, modes, times, etc.)

Utility Calculation : Compute the attractiveness of each alternative using utility functions

Probability Calculation : Convert utilities to choice probabilities using logit formulations

Choice Selection : Select alternatives based on computed probabilities and random draws

UEC Integration

Components use the Utility Expression Calculator (UEC) framework:

Utility Specifications : Mathematical expressions defining alternative attractiveness

Parameter Management : Organized storage and access to model coefficients

Logsum Calculation : Generation of accessibility measures for nested choice structures

Model Customization and Configuration

Parameter Customization

Each model component can be customized through:

Utility Function Parameters : Coefficients that control the importance of different factors

Alternative Set Definitions : Which choices are available in different contexts

Segmentation Schemes : How the population is divided for different model applications

Regional Adaptation

Models can be adapted for different regions through:

Local Calibration : Parameter estimation using regional observed data

Alternative Specifications : Regional variations in available choices

Validation Standards : Local benchmarks for model performance

Component Documentation Structure

Each component documentation page includes:

Model Overview

  • Purpose and role in the overall system
  • Key behavioral assumptions and theory
  • Relationship to other model components

Technical Specification

  • Model structure and choice alternatives
  • Utility function specifications
  • Parameter definitions and typical values

Data Requirements

  • Input data sources and formats
  • Required preprocessing and validation
  • Output data products and uses

Implementation Guidance

  • Configuration and setup procedures
  • Calibration and validation approaches
  • Common issues and troubleshooting

Examples and Use Cases

  • Practical applications and scenarios
  • Analysis templates and workflows
  • Interpretation guidance for results

Getting Started with Components

For New Users

  1. Start with Auto Ownership - Foundation model that affects all others
  2. Understand CDAP - Key to household coordination concepts
  3. Follow the execution sequence - Work through models in dependency order

For Technical Users

  1. Review UEC specifications for each component
  2. Understand coordination mechanisms for household interactions
  3. Study integration patterns for system design

For Model Developers

  1. Examine utility functions for specification patterns
  2. Review calibration procedures for parameter estimation
  3. Study validation approaches for quality assurance

Component Navigation

Each component page is self-contained but includes cross-references to related models. Use the dependency diagram above to understand the logical flow between components.

Model Complexity

Components vary in complexity from simple frequency models to sophisticated nested choice structures. Start with simpler components to build understanding before tackling complex spatial choice models.

This overview provides the roadmap for understanding CT-RAMP’s comprehensive modeling system.

Last updated: September 26, 2025