• ♦Manual Notice 2001-1
• ►1. Traffic Estimation and Forecasting
  • ♦1. Overview
  • ►2. Traffic Data Collection and Reporting
    • ♦Overview
  • ►3. Automatic Traffic Recorder Volume Data
    • ♦ATR Data Collection
    • ♦ATR Data Analysis
    • ♦ATR Data Reporting
  • ►4. Accumulative Count Recorder Traffic Data
    • ♦ACR Data Collection
    • ♦ACR Data Analysis
    • ♦ACR Data Reporting
  • ►5. Highway Performance Monitoring System Traffic Data
    • ♦Overview
    • ♦HPMS Data Collection
    • ♦HPMS Data Analysis
    • ♦HPMS Data Reporting
  • ►6. Five Year Count Program
    • ♦Overview
    • ♦Five Year Count Data Collection
    • ♦Five Year Count Data Analysis
    • ♦Five Year Count Data Reporting
  • ►7. Vehicle Classification Data
    • ♦Vehicle Classification Data Collection
    • ♦Vehicle Classification Data Analysis
    • ♦Vehicle Classification Data Reporting
  • ►8. Truck Weigh-in-Motion Data
    • ♦Weigh-in-Motion Data Collection
    • ♦Weigh-in-Motion Data Analysis
    • ♦Weigh-in-Motion Data Reporting
  • ►9. Vehicle Speed Data
    • ♦Vehicle Speed Data Collection
    • ♦Vehicle Speed Data Analysis
    • ♦Vehicle Speed Data Reporting
  • ►10. Long-Term Pavement Performance Data
    • ♦Overview
    • ♦Long-Term Pavement Performance Data Collection
    • ♦Long-Term Pavement Performance Data Analysis
    • ♦Long-Term Pavement Performance Data Reporting
  • ►11. Border Trend Traffic Data
    • ♦Overview
    • ♦Border Trend Traffic Data Collection
    • ♦Border Trend Traffic Data Reporting
  • ♦12. Traffic Data for Special Projects
  • ►13. Off-System Traffic Data
    • ♦Off-System Traffic Data Collection
    • ♦Off-System Traffic Data Analysis
    • ♦Off-System Traffic Data Reporting
  • ►14. Permanent ATR Locations by District
    • ♦ATR Locations
  • ►15. Vehicle Classification Count Locations
    • ♦Count Locations
  • ►16. Speed Data Collection Sites
    • ♦Speed Collection Sites
  • ►17. Long-Term Pavement Program Site Locations
    • ♦Pavement Program Sites
  • ►18. Texas 6 Vehicle Classification Figures
    • ♦Texas 6 Vehicle Classifications
  • ►19. FHWA Vehicle Classification Figures
    • ♦FHWA Vehicle Classifications
• ▼2. Urban Travel Demand Forecasting
  • ►1. Overview
    • ♦Forecasts Guide Planning
  • ▼2. Texas Travel Demand Model Package
    • ♦Overview
    • ♦Trip Generation
    • ♦Trip Distribution
    • ♦High Occupancy Vehicle (HOV)
    • ♦Traffic Assignment
  • ►3. Travel Demand Modeling Process
    • ♦Overview
    • ♦Traffic Analysis Zones, Districts, and Sectors
    • ♦Network Development
    • ♦Trip Generation Data Development
    • ♦Trip Distribution Data Development
    • ♦Model Calibration
    • ♦Model Validation
  • ►4. Travel Demand Model Output
    • ♦Overview
  • ►5. Air Quality Conformity Modeling
    • ♦Overview
    • ♦Air Quality Conformity Modeling Process and Programs
  • ►6. Travel Demand Forecasting Organization
    • ♦Responsible Organizations
  • ►7. Travel Demand Modeling Procedures
    • ♦Review and Update
• ►3. Project Level Traffic Data Development
  • ►1. Feasibility Studies
    • ♦Overview
    • ♦Traffic Data Provided
  • ►2. Advanced Planning
    • ♦Overview
    • ♦Traffic Data Provided
  • ►3. Environmental Documentation
    • ♦Overview
    • ♦Traffic Data Provided
  • ►4. Project Design
    • ♦Overview
    • ♦Geometric Design
    • ♦Traffic Data Provided
  • ►5. Pavement Design
    • ♦Overview
    • ♦Traffic Data Provided
  • ►6. Bridge Design
    • ♦Overview
    • ♦Traffic Data Provided
  • ►7. Signalized Intersection Design
    • ♦Overview
    • ♦Traffic Data Provided
  • ►8. Traffic Data for Special Projects
    • ♦Transportation Commission Requests
    • ♦Project Calls
    • ♦Major Investment Studies
    • ♦Traffic Data Provided
  • ►9. Traffic Data and Forecast Request Procedures
    • ♦Requested Information
• ►4. Database Management
  • ►1. Overview
    • ♦Functional Responsibilities
  • ►2. Data File Creation/Maintenance
    • ♦Texas Reference Marker
    • ♦State Railroad File
    • ♦RI File
    • ♦Accident File
    • ♦Highway Performance Monitoring System
    • ♦HPMS Mileage Certification
    • ♦Linear Reference System
  • ►3. Mapping
    • ♦State Base Map Updates - Data Collection

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Section 2: Texas Travel Demand Model Package

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Overview

TPP uses the Texas Travel Demand Model Package (Texas Package) to prepare travel forecasts for urban areas in Texas. It is a set of computer modules based on the traditional four-step travel demand forecasting process that includes trip generation, trip distribution, mode choice, and traffic assignment. The Texas Package contains three models: trip generation, trip distribution, and traffic assignment. A mode choice model is not used due to the modest public transportation systems in most Texas urban areas, although Houston, Dallas-Fort Worth, San Antonio, and Austin have developed mode choice models for use in their areas.

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Trip Generation

The trip generation module used in the Texas package is TRIPCAL5© (version September 1999). TRIPCAL5© is a multifunctional program that estimates trip productions and attractions for up to ten trip purposes and 9,999 traffic analysis zones. This program includes features that allow input of user-specified data or use of default models for the disaggregation of data at the traffic analysis zone level (TAZ). Program options include trip production models, trip attraction models, disaggregation models, multiple trip purposes, and user-selected data inputs.

The sub-programs within TRIPCAL5© are designed to use the socioeconomic data normally used in trip generation. The trip production models use estimates of the number of households stratified by household size and or household income or auto ownership for each zone. Trip attraction models employ estimates of each zone’s employment stratified by employment type and area type. The specific data elements recommended for running TRIPCAL5© include population, number of households, median household income, and number of employees in the basic, service, and retail categories for each traffic analysis zone.

Trip Purposes. Up to 10 trip purposes may be used in TRIPCAL5© with specific trip rates for each. Typical trip purposes include:

• home-based work
• home-based school
• home-based shopping
• home-based other
• non-home-based work
• non-home-based other
• truck and taxi
• external-local.

For most urban areas in Texas the following trip purposes are used:

• home-based work
• home-based non-work
• non-home-based
• truck and taxi
• external local

Trip Productions. Three trip production models are included in TRIPCAL©:

• A Two-Way Cross-Classification Model, which allows trip rates stratified for up to six categories for each independent variable.
• A Three-Way Cross-Classification Model, which allows trip rates to be stratified for up to six categories for two of the independent variables and up to four categories for the third independent variable.
• A Linear Regression Model with up to six independent variables.

The recommended trip production model is a Two-Way Cross-Classification Model with person trips (or auto-driver trips) per household cross-classified by up to six row categories and up to six column categories. Although the program is developed to allow the user to input any independent variables for the cross-classification model, the recommended independent variables are median household income and household size.

Trip Attractions. Five trip attraction models are available to estimate trip attractions:

• A Two-Way Cross-Classification Model may be selected and attraction trip rates stratified for up to six categories for each independent variable.
• A Three-Way Cross-Classification Model with trip rates stratified for up to six categories for two of the independent variables and up to four categories of the third independent variable.
• A Cross-Classification/Regression Model with trip rates stratified for up to 24 generation areas by households and employment type.
• A Linear Regression Model with up to six independent variables.
• A Two-Tier Regression Model with six independent variables.

The recommended trip attraction model is a regression type cross-classification model for each trip purpose stratified for up to 24 generation areas. The recommended independent variables are employment and households.

Disaggregation Models. Disaggregation models in TRIPCAL5© produce planning year estimates of the number of households classified by household size, household income, or auto ownership for each traffic analysis zone. These estimates are required in trip production. For any of these three variables (household size, household income, or auto ownership), the base year marginal distribution of each zone, a disaggregation curve for the urban area, or defaults built into the model may be used.

Special Generators. Trip production and trip attraction models are for average or usual conditions and development types. Certain developments, however, are considered unique and are considered special generators. For each identified special generator within an urban area, trip productions and attractions are considered separately using individual trip production and attraction rates for that generator. The special generator model input data (see Table 2-1) are more detailed that the usual zone input data. Common special generators include:

• major regional amusement parks
• major sports facilities
• major regional airports
• military bases
• colleges, universities, communities colleges
• high schools

Additional information for high schools and universities/colleges that should be obtained if at all possible includes:

• number of students who drive to school
• number of students who walk to school
• number of students who ride public transportation to school
• number of students with jobs (high school only).

Anchor: #BGBFIJFGTable 2-1. Special Generator Information

Data Item	Description
Employment Type	The type of employment at the special generator: basic, service, or retail
Zone Number	Traffic analysis zone where the special generator is located
Name	Name of special generator
Hours of Operation	Number of hours in operation during a normal weekday
Total Employment	Total number of persons (full and part time) employed at the special generator
On Base Military	If special generator is a military base, this is the total number of military personnel living on base.
Off Base Military	If special generator is a military base, this is the number of military personnel living off base.
Off Base Civilians	If special generator is a military base, this is the number of civilian employees who live off base and work on base.
Number of Shifts	The number of work shifts at the special generator.
Employees per Shift	Number of employees per work shift.
Student Enrollment	If special generator is a school, this is the total number of students enrolled in the school.
Living On-Campus	If special generator is a school, this is the total number of students living on campus.
Hospital Beds	If special generator is a hospital, this is the total number of hospital beds in the hospital.
Number of Flights	If special generator is an airport, this is the number of flights per day served at the airport.
Airline Passengers	If special generator is an airport, this is the number of deplaning passengers per day.

Trip Balancing. Trip productions and attractions, including external trips, must balance within each area. TRIPCAL5^© contains an option that allows regional control of total trip productions or attractions for each trip purpose. The trips are then scaled to the control total. There is also an option to balance trip productions to attractions, or attractions to productions. Generally, trip attractions are balanced to productions for each trip purpose.

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Trip Distribution

TPP uses the ATOM II^© (version September 1999) module, a spatially disaggregate trip distribution modeling technique, to perform trip distribution. ATOM II^© loosely parallels the gravity model in its basic formulation, but contains an interaction constraint option that limits the number of attraction zones eligible to receive productions from a given zone. It is considered a spatially disaggregate technique in that it provides for the assignment of spatial attributes to zonal activities rather than concentrating zonal activity within a zone cen0037 centroid.

ATOM II^© requires the zonal trip productions and attractions by trip purpose produced in trip generation and the zone-to-zone travel times for the minimum time paths estimated using the highway network and 24-hour speeds. Additional input required includes: a zonal parameter that provides the distance in minutes of travel time from the center point of the zonal centroid to the nearest network point on the perimeter of the zone, estimates of the trip length frequency distribution by trip purpose, and estimates of bias factors by trip purpose.

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High Occupancy Vehicle (HOV)

An HOV module is available in the Texas package. The Texas HOV model combines adaptations of three models: a travel time ratio model, a logic model, and a travel time savings model. Together the three models use an area’s travel demand model data to estimate the shift in corridor travel to the HOV. The final results are a weighted average from the three individual models.

The input required for the Texas HOV model includes the expected percent transit and the average auto occupancy at the sector level. Options to input auto occupancy estimates by separation and the expected percent trips by school bus are available.

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Traffic Assignment

The technique used for traffic assignment is the Texas Large Network Package. This package accommodates 4,800 zones, 20,000 links, and a maximum link impedance of 10.23 minutes. A program within the model set provides an iterative cycle of assignments with capability to adjust link impedance between assignment iterations. This balancing capability is accomplished by a comparison of the previously assigned link volume with the link capacity. Where a link is over- or under-assigned, the original link impedance is adjusted prior to the next assignment iteration.

Input into the assignment program includes a network; specific link data such as direction, speed, and number of lanes; and a trip table that is the product of trip distribution. An option also exists to input turn penalties at entrance and exit ramps to prevent the program from assigning short trips to major freeways.