We present an integrated activity-based discrete choice model system of an individual’s 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 person’s 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 day’s 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 day’s 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.

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Activity-based disaggregate travel demand model system with activity schedules

A comprehensive travel demand modeling framework is proposed to identify and model the urban development decisions of firms and the mobility, activity, and travel decisions of individuals and households. The framework is also used to develop a system of models that can be used by decisionmakers and planners to evaluate the effects of developments in information technologies and changes in the transportation system. 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, an activity-based model system is presented as the first stage in the development of an operational model system.

Travel demand model system for the information era. in: transport and information systems

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.

Travel demand model system for the information era

This study develops a model of a person’s day activity schedule that can be used to forecast urban travel demand. It is motivated by the notion that travel outcomes are part of an activity scheduling decision, and uses discrete choice models to address the basic modeling problem—capturing decision interactions among the many choice dimensions of the immense activity schedule choice set. An integrated system of choice models represents a person’s day activity schedule as an activity pattern and a set of tours. A pattern model identifies purposes, priorities and structure of the day’s activities and travel. Conditional tour models describe timing, location and access mode of on-tour activities. The system captures trade-offs people consider, when faced with space and time constraints, among patterns that can include at-home and on-tour activities, multiple tours and trip chaining. It captures sensitivity of pattern choice to activity and travel conditions through a measure of expected tour utility arising from the tour models. When travel and activity conditions change, the relative attractiveness of patterns changes because expected tour utility changes differently for different patterns. An empirical implementation of the model system for Portland, Oregon, establishes the feasibility of specifying, estimating and using it for forecasting. Estimation results match a priori expectations of lifestyle effects on activity selection, including those of (a) household structure and role, such as for females with children, (b) capabilities, such as income, and (c) activity commitments, such as usual work levels. They also confirm the significance of activity and travel accessibility in pattern choice. Application of the model with road pricing and other policies demonstrates its lifestyle effects and how it captures pattern shifting—with accompanying travel changes—that goes undetected by more narrowly focused trip-based and tour-based systems. Although the model has not yet been validated in before-and-after prediction studies, this study gives strong evidence of its behavioral soundness, current practicality, potential to generate cost-effective predictions superior to those of the best existing systems, and potential for enhanced implementations as computing technology advances. Thesis Supervisor: Dr. Moshe Ben-Akiva Title: Professor of Civil and Environmental Engineering

https://dspace.mit.edu/bitstream/handle/1721.1/16731/44704881-MIT.pdf?sequence=2

The Day Activity Schedule Approach to Travel Demand Analysis

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 paper's 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.

Activity-Based Travel Forecasting Models in the United States: Progress since 1995 and Prospects for the Future

This paper describes a practical model of non-home-based travel that can be incorporated in existing urban transportation model systems. The model is estimated by using a disaggregate sample of trips drawn from the 1965 home interview survey of the San Francisco Bay Area for the Metropolitan Transportation Commission. The model predicts trip generation, distribution, and mode split with full sensitivity to travel times, costs, and zone characteristics. The paper describes the overall model structure and estimation results. Comparisions with other research on non-home-based travel are drawn and recommendations for future research presented. /Authors/

Disaggregate travel demand models for the san francisco bay area. non-home-based models

Dramatic increases in transit patronage will require a major restructuring of present transit and paratransit operations to achieve integrated regional systems capable of changing as traffic increases and new markets are penetrated. The integration of new public transportation options such as dial-a-ride, jitney, and subscription bus with conventional mass transit promises significantly improved overall levels of service without increased total system costs. Integrated systems and expansion policies require that the individual service and cost attributes of each system component be modeled and the synergisms that result from various service combinations must be evaluated. Integrated system design is significantly more complex than the conventional bus routing and scheduling problem because of the increased number and complexity of available modes. This paper examines a case in which various service policies are evaluated, for parametrically varied demand levels, by using a combination of manual and automated procedures. Major conslusions are that significant economies of scale develop at relatively low levels of increased transit use and that major redesign of system operating policies is required to sustain desirable service levels and costs.

Brian C Kullman

Papers

Disaggregate travel demand models for the san francisco bay area. non-home-based models

Analysis of integrated urban public transportation systems