Thomas Rossi

Modeling Time-of-Day Choice in Context of Tour- and Activity-Based Models

Understanding the variations in travel by time of day is essential to predicting transportation system performance and air quality impacts of the transportation sector. As tour- and activity-based modeling procedures become more commonplace, the need for accurate time-of-day modeling procedures that are sensitive to changes in policies or travel conditions, such as congestion, that affect time-of-day choices, is clear. FHWA recently conducted a research project to develop new methods of modeling travel by time of day that are sensitive to these concerns. One of the products of this project is a time-of-day choice modeling procedure designed to be applied within tour- or activity-based travel modeling processes. This procedure was designed to be compatible with most existing tour- and activity-based models in the United States. The time-of-day choice model is estimated by using household activity survey data and transportation level-of-service information from the highway network. This procedure was tested...

Tour Based Travel Demand Modeling in the U.S.

Abstract The premise of this paper is that tour-based modeling is a reasonable near-term alternative to the traditional four-step process. Tour based modeling is a step toward activity-based modeling, which treats travel as a demand derived from the desire for activities. Activity-based modeling has a stronger theoretical basis than tour-based modeling. It has the potential to become the next generation of model systems, but it is still not a practical alternative for agencies in the U.S. Tour based models have already been implemented in urban areas and can be further implemented in a short period of time.

Recent Practices in Regional Modeling of Nonmotorized Travel

TRB Special Report 288: Metropolitan Travel Forecasting: Current Practice and Future Direction identified treatment of nonmotorized travel in regional models as one of eight modeling deficiencies and also as an advanced modeling practice. However, that report and other existing literature provided little information about recent practices. This paper reviews the current practice of incorporation of nonmotorized travel in regional travel demand models in the United States, especially the models of large metropolitan planning organizations developed over the past decade. Overall, some progress with the representation of nonmotorized travel in regional models has been made. This paper discusses and summarizes modeling approaches, including the variables and data used, data issues, and lessons learned; summarizes the major issues and challenges that modelers face when they incorporate nonmotorized travel into regional travel demand models; and makes recommendations for future improvements to models. Recent examples of different approaches to modeling of nonmotorized travel in regional models are also presented. The pros and cons of each approach, including their different data needs and different abilities to evaluate policies and planning scenarios, are discussed. When deciding on the approach that they will take to modeling of nonmotorized travel, agencies need to know the data requirements, model development efforts, and policy sensitivities desired. In the trip-based modeling framework, further enhancements can be made through the use of more refined zone systems and more accurate measurement of variables, although the activity-based modeling approach is more promising. Regardless of the approach taken, targeted and enhanced data on nonmotorized travel and nonmotorized travel infrastructure are greatly needed.

Innovative Methods for Collecting Data and for Modeling Travel Related to Special Events

The Maricopa Association of Governments (MAG) is the designated metropolitan planning organization for the Phoenix, Arizona, metropolitan area. In collaboration with local transit agencies and local jurisdictions, MAG developed a successful proposal to compete for FTA Alternatives Analysis Discretionary Program Section 5339 funds. The proposal included development of the special events model and special events data collection. The importance of this task was highlighted by the success of the introduction of light rail transit in the region. The need for better understanding and forecasting of transit markets required in-depth study and modeling of planned special events in the region. Special events patrons constituted a significant portion of light rail ridership and overall regional travel demand. This paper focuses on the first results of this effort, including the completed special events data collection and some preliminary data analysis results. The special events surveys used advanced data collection techniques that allowed better data expansion and processing and ultimately will facilitate development of advanced special events travel demand forecasting models. The paper discusses survey design, survey instruments, counting and interviewing processes, organizational issues, and data expansion procedures.

Method of Successive Averages Versus Evans Algorithm: Iterating a Regional Travel Simulation Model to the User Equilibrium Solution

The results of comparative tests of two methods for iterating a regional travel demand model system are presented. Model iteration is necessary to ensure consistency between model input and output speeds, as required by current federal legislation. Two methods were tested: the Evans algorithm and the method of successive averages. A series of tests using alternative assignment techniques was conducted for each method. Criteria for evaluating the iteration methods included convergence error, average highway speeds compared with observations, highway vehicle miles traveled compared with Highway Performance Monitoring System estimates, transit boardings compared with observations, and computer running time. It was concluded that the Evans algorithm performed the best, primarily on the basis of superior computational efficiency, although good results were obtained by using the method of successive averages. Use of the Evans algorithm is recommended, embedded within a formal assignment restart, for iterating the model system. Multiple iterations of highway assignment should be used in the initial model loop and all-or-nothing assignments in subsequent iterations of the modeling chain.

An Integrated, Validated, and Applied Activity-Based Dynamic Traffic Assignment Model for the Baltimore-Washington Region

The paper discusses the integration process and initial applications of a new model for the Baltimore-Washington region that integrates an activity-based travel demand model (ABM) with a dynamic traffic assignment (DTA) model. Specifically, the integrated model includes InSITE, an ABM developed for the Baltimore Metropolitan Council, and DTALite, a mesoscopic DTA model. The integrated model simulates the complete daily activity choices of individuals residing in the model region, including long-term choices, such as workplace location; daily activity patterns, including joint household activities and school escorting; activity location choices; time-of-day choices; mode choices; and route choices. The paper describes the model development and integration approach, including modeling challenges, such as the need to maintain consistency between the ABM and DTA models in terms of temporal and spatial resolution, and practical implementation issues, such as managing model run time and ensuring sufficient convergence of the model. The integrated model results have been validated against observed daily traffic volumes and vehicle-miles traveled (VMT) for various functional classes. A land-use change scenario that analyzes the redevelopment of the Port Covington area in Baltimore is applied and compared with the baseline scenario. The validation and application results suggest that the integrated model outperforms a static assignment-based ABM and could capture behavioral changes at much finer time resolutions.

Issues in Expanding the Denver Regional Activity-Based Model for Statewide Modeling in Colorado

This paper discusses the activity- and tour-based model developed for the Denver Regional Council of Governments in Colorado with respect to two major issues that underlie its expansion to a statewide travel model: managing short- and long-distance travel within a single model and accounting for overnight travel. In a statewide model, the issues are interconnected to the modeling of closed and nonclosed tours. Closed tours are those that begin and end at the same location during the travel day (i.e., home). Although nonclosed tours typically are not modeled in regional activity- and tour-based models, or they are modeled with relatively simple procedures, they are more important in statewide models to accommodate overnight travel. Some long-distance travel involves an overnight stay at a location other than the traveler’s home. Such nonclosed tours, which begin or end the day at a location other than home, must be modeled explicitly in a statewide model. In this paper, required adjustments are identified for key activity- and tour-based model components, and the impacts of the explicit modeling of nonclosed tours for the tour mode choice model are presented.