CT-RAMP: Comprehensive Travel Model ¶
About CT-RAMP
CT-RAMP (Comprehensive Travel-demand forecasting Research And Modeling Platform) is the activity-based travel demand modeling system used in Travel Model Two. It simulates individual and household travel decisions through a comprehensive set of choice models that represent realistic behavioral decision-making processes.
Quick Start Guide ¶
New to Activity-Based Modeling? ¶
Start Here: System Overview provides a comprehensive introduction to activity-based modeling concepts, CT-RAMP’s behavioral foundations, and how it differs from traditional trip-based approaches.
Ready to Understand the System? ¶
Architecture: Technical Architecture details the system design, data flows, and implementation patterns used in CT-RAMP.
Want to Run Models? ¶
Execution: Workflow Guide provides step-by-step instructions for model execution and configuration.
What Makes CT-RAMP Unique? ¶
Activity-Based Foundation ¶
CT-RAMP recognizes that travel is derived from activities, not trips. This fundamental insight leads to:
- Realistic Behavior: Models how people actually make activity and travel decisions
- Household Coordination: Captures joint decision-making within households
- Time-Space Integration: Explicitly considers temporal and spatial constraints
- Policy Sensitivity: Responds to detailed policy variables and scenarios
Comprehensive Model System ¶
CT-RAMP includes 15 integrated model components covering:
Figure: Detailed CT-RAMP model flow diagram showing component interactions and data dependencies
Design Origins ¶
TM2’s design comes from the San Diego CT-RAMP design developed by SANDAG (San Diego Association of Governments). The foundational documentation from this pioneering implementation provides comprehensive technical details about the activity-based modeling approach and estimation procedures.
Original Design Documentation ¶
- SANDAG ABM Model Design - Comprehensive design documentation from the original San Diego CT-RAMP implementation
- SANDAG ABM Model Estimation - Detailed estimation procedures and calibration methodology
These documents provide the theoretical foundation and practical implementation details that informed TM2’s development, offering valuable insights into the behavioral modeling framework and technical specifications.
Technical Framework ¶
Core Systems ¶
Utility Expression Calculator (UEC) Framework ¶
CT-RAMP’s mathematical foundation for all choice modeling:
- UEC Framework Documentation - Comprehensive guide to utility calculation system
- Flexible Specification: Mathematical expressions for choice utilities through Excel control files
- Model Integration: Seamless interface with Java choice model implementations
- Performance Optimization: Efficient calculation for large-scale microsimulation
Value of Time Assignment System ¶
Income-stratified time value framework for mode choice modeling:
- Value of Time Analysis - Complete specification of heterogeneous time value assignment system
- Income Stratification: Four income categories with distinct lognormal value of time distributions
- Tour Type Logic: Conditional value of time selection for individual vs. joint tours
- Mode Choice Integration: Seamless integration with tour and trip mode choice utility calculations
Model Components by Category ¶
Long-term and Coordination Models ¶
These models establish the context for daily travel decisions:
| Component | Purpose | Key Outputs |
|---|---|---|
| Auto Ownership | Vehicle availability decisions | Household auto ownership level |
| Daily Activity Pattern | Household activity coordination | Person-level activity patterns |
Tour Generation Models ¶
These models determine what tours each person will make:
| Component | Purpose | Key Outputs |
|---|---|---|
| Mandatory Tours | Work and school tour generation | Mandatory tour frequency |
| Joint Tours | Multi-person household tours | Joint tour participation |
| Individual Tours | Personal discretionary tours | Individual tour frequency |
Spatial and Temporal Choice Models ¶
These models determine where and when travel occurs:
| Component | Purpose | Key Outputs |
|---|---|---|
| Tour Destination | Primary destination selection | Tour destination zones |
| Tour Mode Choice | Transportation mode selection | Tour primary modes |
| Tour Time-of-Day | Departure and arrival timing | Tour start/end times |
Trip-Level Models ¶
These models add detail about intermediate stops and trip characteristics:
| Component | Purpose | Key Outputs |
|---|---|---|
| Stop Frequency | Intermediate stop decisions | Stop frequencies by direction |
| Stop Location | Stop destination choices | Stop locations and purposes |
| Trip Mode Choice | Trip-level mode decisions | Individual trip modes |
| At-Work Subtours | Tours during work hours | Subtour characteristics |
📊 Output Files & Data Analysis ¶
Comprehensive Output Documentation
Complete field-level specifications and data dictionaries:
🔄 Model-to-Data Flow ¶
Understanding how CT-RAMP model components produce output data files:
| Model Component | Output File | Documentation |
|---|---|---|
| Population Synthesis | householdData_[iter].csv |
📄 Household Data |
| Person Classification | personData_[iter].csv |
📄 Person Data |
| Workplace/School Location | wsLocResults_[iter].csv |
📄 Location Results |
| Model Component | Output File | Documentation |
|---|---|---|
| Mandatory Tours | indivTourData_[iter].csv |
📄 Individual Tours |
| Individual Tours | ↪️ Same file | Work, School, University, Discretionary tours |
| Joint Tours | jointTourData_[iter].csv |
📄 Joint Tours |
| Model Component | Output File | Documentation |
|---|---|---|
| Stop Frequency | indivTripData_[iter].csv |
📄 Individual Trips |
| Trip Mode Choice | ↪️ Same file | Trip-level mode decisions |
| Joint Trip Processing | jointTripData_[iter].csv |
📄 Joint Trips |
📈 Data Analysis Integration ¶
From Models to Analysis
Model Components → Learn how decisions are made
Output Files → Examine what decisions were made
Data Dictionaries → Verify data integrity and meaning
🎯 Quick Navigation ¶
| I want to… | Go to… |
|---|---|
| Understand how tours are generated | Model Components |
| Analyze tour data from model runs | Output File Specifications |
| Validate field definitions and codes | Data Dictionaries |
| Map survey data to CTRAMP format | Individual Tours or Joint Tours |
Execution and Coordination ¶
The Execution System manages:
- Dependency Resolution: Automatic model sequencing based on data requirements
- Household Coordination: Joint decision-making across household members
- Performance Optimization: Parallel processing and intelligent caching
- Quality Assurance: Comprehensive validation and error checking
Scale and Performance ¶
Computational Scale ¶
Modern CT-RAMP implementations in the Bay Area handle:
- Population: 1+ million households, 2.5+ million persons
- Geography: 40,000+ micro-zones, 1,500+ traffic zones
- Travel: 10+ million tours, 25+ million trips annually
- Time Resolution: Half-hourly periods with peak spreading
Data Requirements ¶
Comprehensive input data enables realistic microsimulation:
- Input Data: Population, land use, networks, accessibility
- Output Data: Individual travel patterns, household coordination
- Validation Data: Observed behavior for calibration
Comprehensive Output Documentation
For detailed field-level specifications of all CTRAMP output files including data dictionaries, validation rules, and survey integration guidance, see the CTRAMP Output File Specifications. Essential for data analysis and survey data mapping.
Integration with Travel Model Two ¶
CT-RAMP operates as the demand forecasting component in Travel Model Two:
Upstream Integration - UrbanSim: Provides land use forecasts and synthetic population - Network Processing: Highway and transit network preparation - Accessibility Calculation: Level-of-service matrix generation
Downstream Integration
- Network Assignment: CT-RAMP trips loaded onto transportation networks
- Feedback Mechanisms: Congested travel times update accessibility measures
- Validation and Reporting: Model results compared to observed patterns
Getting Started by User Type ¶
For Model Users ¶
- System Overview - Understand activity-based modeling concepts
- Model Components - Learn what each model does
- Execution Workflow - Run models step-by-step
- Output Analysis - Interpret and use model results
For Model Developers ¶
- Architecture - Technical implementation details
- UEC Framework - Utility calculation system
- Configuration - Model setup and customization
- Examples - Development templates and patterns
For Policy Analysts ¶
- Overview - Behavioral foundations and policy sensitivity
- Validation - Model performance and limitations
- Examples - Analysis templates and use cases
- Troubleshooting - Common issues and solutions
Support Resources ¶
Documentation ¶
- Comprehensive Guides: Detailed model component documentation
- UEC Framework: Utility calculation system and implementation details
- User Examples: Practical analysis templates and workflows
Quality Assurance ¶
- Validation Framework: Model performance metrics and benchmarks
- Troubleshooting: Common issues and resolution strategies
- Configuration Management: Setup and customization guidance
Next Steps
- New to CT-RAMP? System Overview
- Ready to run models? Execution Workflow
- Need technical details? Architecture or UEC Framework
- Want examples? Usage Examples
Model Complexity
CT-RAMP is a sophisticated microsimulation system. We recommend starting with the System Overview to understand the behavioral foundations before diving into technical implementation details.
Last updated: September 26, 2025