John L. Bowman

Activity-based disaggregate travel demand model system with activity schedules

We present an integrated activity-based discrete choice model system of an individuals activity and travel schedule, for forecasting urban passenger travel demand. A prototype demonstrates the system concept using a 1991 Boston travel survey and transportation system level of service data. The model system represents a persons choice of activities and associated travel as an activity pattern overarching a set of tours. A tour is defined as the travel from home to one or more activity locations and back home again. The activity pattern consists of important decisions that provide overall structure for the days activities and travel. In the prototype the activity pattern includes (a) the primary - most important - activity of the day, with one alternative being to remain at home for all the days activities; (b) the type of tour for the primary activity, including the number, purpose and sequence of activity stops; and (c) the number and purpose of secondary - additional - tours. Tour models include the choice of time of day, destination and mode of travel, and are conditioned by the choice of activity pattern. The choice of activity pattern is influenced by the expected maximum utility derived from the available tour alternatives.

Travel demand model system for the information era

The emergence of new information technologies and recent advances in existing technologies have provided new dimensions for travel demand decisions. In this paper we propose a comprehensive travel demand modeling framework to identify and model the urban development decisions of firms and developers and the mobility, activity and travel decisions of individuals and households, and to develop a system of models that can be used by decision makers and planners to evaluate the effects of changes in the transportation system and development of information technologies (e.g. various tele-commuting, tele-services and Intelligent Transportation Systems).The implementation of an operational model system based on this framework is envisioned as an incremental process starting with the current “best practice” of disaggregate travel demand model systems. To this end, we present an activity-based model system as the first stage in the development of an operational model system.

Activity Based Travel Demand Model Systems

Stated simply, the motivation for activity based travel demand modeling is that travel decisions are activity based.

SACSIM: An applied activity-based model system with fine-level spatial and temporal resolution

Abstract This paper presents the regional travel forecasting model system (SACSIM) being used by the Sacramento (California) Area Council of Governments (SACOG). Within SACSIM an integrated activity-based disaggregate econometric model (DaySim) simulates each residents full-day activity and travel schedule. Sensitivity to neighborhood scale is enhanced through disaggregation of the modeled outcomes in three key dimensions: purpose, time, and space. Each activity episode is associated with one of seven specific purposes, and with a particular parcel location at which it occurs. The beginning and ending times of all activity and travel episodes are identified within a specific 30-minute time period. Within SACSIM, DaySim equilibrates iteratively with traditional traffic assignment models. SACSIM was calibrated and tested for a base year of 2000 and for forecasts to the years 2005 and 2035, and was subjected to a formal peer-review. It was used to provide forecasts for the Regional Transportation Plan (RTP) and continues to be used for various policy analyses. The paper explains the model system structure and components, the integration with the traffic assignment model, calibration and validation, sensitivity tests, model application and Federal peer review results. We conclude that it is possible to create and apply a regional demand model system using parcel-level geography and half-hour time of day periods. Experiences thus far have pointed to major benefits of using detailed land use variables and urban design variables, but also to new challenges in providing parcel-level land use inputs for future years.

Activity-Based Travel Forecasting Models in the United States

This paper focuses on the use of activity based models in practice for urban and regional planning in the United States (U.S.). In addition to projects that have been carried out, also recognized is work done in a variety of research settings, both inside and outside the U.S. that will assist in the choice of activity based models in the future. Regional planning in the U.S. is at a critical stage with the adoption of activity based models accelerating. The papers goal is to provide an opportunity to review the types of modeling developments that have been successfully implemented. Also discussed are factors that remain as hindrances to the acceptance of activity based models for planning by U.S. government agencies.

Testing Spatial Transferability of Activity-Based Travel Forecasting Models

This paper reports results from the second phase of a two-phase FHWA-sponsored project to test and demonstrate empirically the transferability of activity-based model (ABM) systems between regions. With data obtained from the 2008–2009 National Household Travel Survey, researchers estimated ABMs simultaneously for 13 metropolitan regions in seven U.S. states. Statistical tests were used to test transferability, including tests of regional differences in the model coefficients, likelihood ratio tests of model equivalence, and transferability indexes, which measure the degree of model differences. In addition, differences in prediction sensitivity between locally estimated and transferred models were tested. The project overall found evidence in favor of transferability. It also found that parameters associated with land use, logsum accessibilities, and travel time and cost caused the biggest problems with transferability. Finally, the study found that transferring within a state or between regions with similar urban density improves transferability. This paper presents the data, models, and testing methods used in the project and includes details of all tests and results related to the improved transferability associated with model transfers from regions within the same state or with similar urban density. The conclusion of the study was that agencies considering transfer of an ABM from another region would do well to find a region within the same state or with similar urban density that has a model that is well supported by a large household travel survey data set.

Comparison of Four-Step Versus Tour-Based Models for Prediction of Travel Behavior Before and After Transportation System Changes

The main objective of this study was to examine the performance of the Mid-Ohio Regional Planning Commission trip-based and tour-based frameworks in the context of three specific projects started and completed within the past 20 years in the Columbus, Ohio, metropolitan area. Region- and project-level comparisons of the performance of the trip- and tour-based models were made for three scenario years: 1990, 2000, and 2005. The region-level analysis was undertaken in the context of four travel dimensions on the basis of data availability and observed data to model output compatibility. These four dimensions were vehicle ownership, work flow distribution, work flow distribution by time of day, and average work trip travel time. The tour-based model performed better overall than the trip-based model for all four dimensions. The project-level comparative assessment of the predicted link volumes from the trip-based and the tour-based models was undertaken according to the observed link counts and roadway functional class. The results did not show any clear trends according to the performance of the models by functional class or year.