| John L. Bowman,
Ph. D. Transportation Systems and Decision Sciences Bowman Research and Consulting 28 Beals Street Telephone:
617-232-8189 |
 |
Project summaries and references
Papers
Other publications and working papers
Sacramento: SACSIM Activity-Based Travel Forecasting Model for SACOG, Featuring DAYSIM—the Person Day Activity and Travel Simulator
Seattle: Activity-Based Model Development for Puget
Sound Regional Council (PSRC)
Planning studies for advanced model development
Last updated on February
23, 2010
Please email site suggestions to: John_L_Bowman@alum.mit.edu
If you find this site of value, please register
here.
Bowman, John L. (1998) The day activity schedule approach to travel demand analysis, Ph.D. Dissertation, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. 185 pages.
Further develops the activity schedule model (see 1995 Thesis), emphasizing (a) the influence of activity accessibility on activity participation, at-home vs on-tour decisions, trip chaining and inter-tour trade-offs, and (b) the influence of lifestyle on activity and activity pattern utility. Includes an empirical implementation of the model system for Portland, Oregon.
Synopsis (PDF) Thesis
(658K PDF)
Bowman, John. L. (1995) Activity based travel demand model system with daily activity schedules, Master of Science Thesis in Transportation, Massachusetts Institute of Technology, 92 pages.
Presents an integrated activity based discrete choice model system of an individual's daily activity and travel schedule, intended for use in forecasting urban passenger travel demand. The system is demonstrated using data from the Boston metropolitan area.
Bradley, Mark, John L. Bowman and Bruce Griesenbeck (2010) SACSIM: An applied activity-based model system with fine-level spatial and temporal resolution, Journal of Choice Modeling (publication pending)
Presents the regional travel forecasting model
system (SACSIM) being used by the Sacramento (California) Area
Council of Governments (SACOG). 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.
Pre-publication draft of paper (249K PDF)
Dong, Xiaojing, Moshe E. Ben-Akiva, John L. Bowman and Joan Walker (2006) Moving from Trip-Based to Activity-Based Measures of Accessibility, Transportation Research Part A, 40(2006), pages 163-180.
Studies the properties and performance of an
accessibility measure derived from the Day Activity Schedule (DAS)
model
system, comparing it with traditional trip-based measures, including
isochrones, gravity-based measures and simpler utility-based measures.
Pre-publication draft of paper (143K PDF)
Bowman, J. L. and M. E. Ben-Akiva (2001) Activity-based disaggregate travel demand model system with activity schedules, Transportation Research Part A, 35(2001), pages 1-28.
A refined and shortened version of Bowman's Master's thesis (see above).
Pre-publication
draft
of
paper
(119K
PDF)
Bowman, John L., Mark A. Bradley, Yoram Shiftan, T. Keith Lawton and Moshe E. Ben-Akiva (1998) Demonstration of an activity based model system for Portland, 8th World Conference on Transport Research, July 12-17, 1998, Antwerp, Belgium.
Reports the first operational implementation, in Portland, Oregon, of the activity-based travel demand model system proposed in 1994 by Ben-Akiva, Bowman and Gopinath.
Pre-publication draft of paper (80K PDF)
Ben-Akiva, Moshe E., and John L. Bowman (1998) Activity based travel demand model systems, in Equilibrium and Advanced Transportation Modeling, P Marcotte and S Nguyen, ed., Kluwer Academic Publishers, 20 pages.
Traces the evolution of disaggregate discrete choice travel demand models toward an activity basis.
Ben-Akiva, Moshe E. and John L. Bowman (1998) Integration of an activity-based model system and a residential location model, Urban Studies, 35(7), pp. 1231-1253.
Presents an integrated discrete choice model system of a household’s residential location choice and its members’ activity and travel schedules.
Pre-publication
draft
of
paper
(562K
PDF)
Ben-Akiva, Moshe., John L. Bowman and Dinesh Gopinath. (1996) Travel demand model system for the information era, Transportation(23), pp. 241-266.
Proposes 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.
Abstract (PDF) Pre-publication draft of paper (not currently available)
Other publications and working papers
Castiglione, Joe,
Brian Grady, John L. Bowman, Mark Bradley and Stephen Lawe (2010)
Building an Integrated Activity-Based and
Dynamic Network Assignment Model, Submitted for presentation at
the 3rd Transportation Research Board Conference on Innovations in
Travel Modeling, May 9-12, 2010, Tempe, Arizona, USA.
Bowman, John L.
(2009) Historical Development
of Activity Based Model Theory and Practice, Traffic Engineering
and Control, Vol. 50 No. 2: 59-62 (part 1), Vol. 50 No. 7: 314-318
(part 2).
Pre-publication
draft
of
paper
(96K
PDF)
Bradley, Mark, John L. Bowman and Bruce
Griesenbeck (2009) Activity-Based
model for a medium sized city: Sacramento, Traffic
Engineering and Control, Vol. 50 No. 2: 73-79.
Pre-publication
draft
of
paper
(56K
PDF)
Bowman, John L. (2009) Population Synthesizers, Traffic Engineering and Control, Vol. 49 No. 9: 342.
A brief note explaining population
synthesizers.
Pre-publication
draft of paper
(11K PDF)
Bowman, John L. and Mark A. Bradley (2008) Activity-Based Models: Approaches used to achieve integration among trips and tours throughout the day, presented at the 2008 European Transport Conference, Leeuwenhorst, The Netherlands, October, 2008.
Compares various integration techniques used by four activity-based models that have been used for travel forecasting in the US, providing conceptual understanding and reasoned discussion of their strengths and weaknesses..
Paper (PDF) Presentation slides (PDF) Presentation script (PDF)
Bradley, Mark.A., John L. Bowman and Bruce Griesenbeck (2007) Development and application of the SACSIM activity-based model system, presented at the 11th World Conference on Transport Research, Berkeley, California, USA, June, 2007.
A condensed version of the 2005 and 2006 ETC papers, with an additional section on application issues.
Bowman, John L., Mark A. Bradley and John Gibb (2006) The Sacramento Activity-Based Travel Demand Model: Estimation And Validation Results, presented at the European Transport Conference, September 18-20, 2006, Strasbourg, France.
A sequel to the 2005 ETC SACOG paper, this paper focuses on several aspects of the model system, including the time-of-day models, equilibration of demand and assignment, base year calibration, and sensitivity tests.
Bowman, John L. and Mark A. Bradley (2006) Upward Integration of Hierarchical Activity-based Models, working paper.
Discusses the importance and difficulty of achieving upward vertical integration in activity based models, and a few techniques used by Bowman and Bradley to achieve it.
Bowman, J.L. and G. Rousseau (2006) Validation of the Atlanta (ARC) Population Synthesizer (PopSyn), white paper presented at the TRB Conference on Innovations in Travel Modeling, May 21-23, 2006, Austin, Texas.
Presents the results of initial base year and backcast validation of the ARC Population Synthesizer (PopSyn).
Bradley, Mark A. and John L. Bowman (2006) A Summary of Design Features of Activity-Based Microsimulation Models for U.S. MPOs, white paper presented at the TRB Conference on Innovations in Travel Demand Modeling, May 21-23, 2006, Austin, Texas.
This short paper provides a concise summary of important design features of various activity-based model systems that had been implemented or recently designed as of May, 2006, for planning agencies in the U.S. The models described are those for Portland, San Francisco, New York, Columbus, Atlanta, Sacramento, Bay Area, and Denver.
Bowman, John L. and Mark A. Bradley (2005) Disaggregate treatment of purpose, time of day and location in an activity-based regional travel forecasting model, European Transport Conference, October 2005, Strasbourg, France.
Presents model system design, data, and partial estimation results of the activity based regional travel forecasting model system for the Sacramento (California) Area Council of Governments (SACOG), as it stood while under development in September, 2005. Emphasis is placed on the techniques employed for effectively disaggregating the treatment of purpose, time and space.
Bowman, John L. (2004) A comparison of population synthesizers used in microsimulation models of activity and travel demand, working paper.
Microsimulation models that forecast the activities and travel of urban populations create synthetic populations and then use them to simulate the behavior of the households and persons in that synthetic population. The features of eight population synthesizers are compared, and suggestions are made for incorporating the best features into future population synthesizers.
Vovsha, Peter, Mark A. Bradley and John L. Bowman (2004) Activity-based travel forecasting models in the United States: Progress since 1995 and Prospects for the Future , presentation at the EIRASS Conference on Progress in Activity-Based Analysis, May 28-31, 2004, Vaeshartelt Castle, Maastricht, The Netherlands.
Describes activity-based travel forecasting model systems implemented or under development in Portland, San Francisco, New York, Columbus and Atlanta, explaining attempts to incorporate behavioral realism, discussing issues that interfere with their acceptance in practice, and suggesting a research agenda relevant to implementation of practical activity-based models.
Bowman, John L. (2003) Logit kernel (or mixed logit) models for large multidimensional choice problems: identification and estimation, presented at the European Transport Conference, October 3-5, 2005, Strasbourg, France, 2005, and at Transportation Research Board Annual Meeting, Washington, D.C., January, 2004.
Presents an identification rule and
insights for estimation of the class
of error component logit kernel models.
These are logit kernel (or mixed logit) models involving
heteroscedasticity and subsets of alternatives with shared unobserved
attributes. A case study
demonstrates the specification, identification and estimation of the
type of
model for which EC is useful—one with large choice set and a choice
outcome
consisting of two or more variables considered simultaneously.
Bowman, John L., Dinesh Gopinath and Moshe Ben-Akiva (2002) Estimating the probability distribution of a travel demand forecast, working paper.
Presents a practical method for estimating the probability distribution of a travel demand forecast. Given a forecast of any variable of interest, such as revenue or ridership, the approach identifies independent sources of uncertainty, estimates a probability distribution of each source, estimates the sensitivity of the variable to each source, and then combines the effects. A case study is presented in which the probability distribution of a revenue forecast is developed for a new transit system.
Bradley, Mark A. , John L. Bowman and T. Keith Lawton (1999) A Comparison of Sample Enumeration and Stochastic Microsimulation for Application of Tour-Based and Activity-Based Travel Demand Models, European Transport Conference, September 1999, Cambridge, UK.
Bowman, John L., and Moshe E. Ben-Akiva (1999) Incorporating Activity Utility, At-home Activities and Lifestyle in an Activity-based Travel Demand Model, working paper.
A shortened version of Bowman's Ph.D. dissertation (see above).
Bowman, John L.,
and Moshe E. Ben-Akiva (1997) Activity
based travel forecasting, in Activity-Based Travel Forecasting
Conference, June 2-5, 1996: Summary, Recommendations and
Compendium of
Papers, New Orleans, Louisiana. USDOT
report #DOT-T-97-17, 32 pages.
An examination of the theory underlying activity based travel forecasting models, and the classification of the differences among modeling approaches, provide a framework that is used to compare six important examples.
Bowman, John L.
(2009) Activity Model Development Experiences,
TMIP
Webinar,
June
18,
2009.
This presentation is for those who are
considering a move to activity-based models. It describes an
activity-based model, starting from the familiar trip-based model
framework. Then it explains the basic development approaches,
tasks and roles; mentions keys to success; and offers suggestions for
proceeding.
Presentation slides
(1466K PDF) Presentation
script (48K PDF)
Bowman, John L.
(2009) Activity-Based Models: 1994-2009,
presented at the MIT ITS Lab, Cambridge, Massachusetts, March
10, 2009.
Presentation
slides (1318K PDF) Presentation
script
(29K
PDF)
Bowman, John L.
(2008) How is an Activity-Based Model Set
Developed? presented at the Chicago Metropolitan Agency for
Planning Symposium on Developing and Implementing an Activity-Based
Travel Demand Model, August 27, 2008.
A pre-cursor of the TMIP webinar on activity model development (see above).
Presentation
slides
(1458K
PDF) Presentation
script
(56K
PDF)
Bowman, John L.
(2008) The Day Activity Schedule Approach of
Bowman, Ben-Akiva and Bradley: 1994-2008, presented at
the Transportation Research Board Innovations in Travel Modeling
Conference, June 22-24, 2008.
Traces the development of the day activity schedule approach from its birth at MIT in 1994 through its real-world implementations as of 2008. Includes slides from early presentations. Emphasizes the original concepts and findings, as well as enhancements that have occurred since then.
Presentation slides (940K PDF) Presentation script (26K PDF)
Bowman, John L.
(2008) From Theory To Practice: What can we
learn from our U.S. experience? presented at the Transportation
Research Board Annual Meeting Task Force on Moving Activity-based
Approaches into Practice, January 13, 2008.
A retrospective examination of the activity-based model development projects sponsored by regional planning agencies in the United States. The presentation takes a project by project look at the innovations that occurred, then considers why some projects were more successful than others.
Presentation
slides
(331K
PDF) Presentation
script
(14K
PDF)
SACSIM is a regional travel forecasting model system, developed in 2005 and implemented in 2006 for the Sacramento (California) Area Council of Governments (SACOG). The system features an integrated econometric microsimulation of personal activities and travel (DAYSIM) with a highly disaggregate treatment of the purpose, time of day and location dimensions of the modeled outcomes. Here are various technical documents produced during the development and implementation of SacSim and DaySim. They provide a very detailed description of the model system. However, they are historical documents and may differ in some cases from the model’s initial or current implementation.
Package of all the
following documents (3000K Zip file)
Design and planning documents (pdf
files)
Preliminary
design
report
(2002)
Addendum
(2003)
Technical
memo
1—Model
System
Design
(early
2005) The best design overview of
DaySim
Phase
2
Working
Paper
2.1
(June
2005)
Models (pdf files)
Technical
memo
2—Population
Synthesizer
Technical
memo
4—Mode
Choice
Technical
memo
5—Intermediate
Stop
Location
Technical
memo
6—Day
Pattern
Activity
Generation
Technical
memo
7—Time
of
Day/Activity
Scheduling
Technical
memo
8—Usual
and
Tour
Destination
Technical
memo
9—Household
Auto
Availability
Technical
memo
11—Impedance
and
Accessibility
Effects
DaySim program (pdf files)
Technical
memo
3—Design
of
Model
System
Application
Software
Technical
memo
10—DaySim05
Documentation
SacSim (pdf files)
Application
of
an
Activity-Based
Travel
Model
of
the
Sacramento
Region
(SacSim)
September 21, 2006 draft
Sacramento
Activity-Based
Travel Simulation Model (SACSIM07): Model Reference
Report November 2008 review draft
Report
of
the SacSim Improvement Program Peer Review Panel November 2008
Papers
(pdf
files)
Bowman,
John
L.
and
Mark
A.
Bradley (2005) Disaggregate treatment of
purpose,
time of day and location in an activity-based regional travel
forecasting model,
European Transport Conference, October 2005, Strasbourg, France.
Bowman,
John
L.,
Mark
A.
Bradley
and John Gibb (2006) The Sacramento
activity-based travel demand model:
estimation and validation results, European Transport
Conference,
September 2006, Strasbourg, France.
Bradley,
Mark, John L. Bowman and
Bruce Griesenbeck (2010) SACSIM:
An
applied activity-based model system with fine-level spatial and
temporal resolution, Journal of Choice Modeling (publication
pending)
Puget Sound Regional Council
(PSRC) is implementing an activity-based travel demand model system,
using an enhanced version of DAYSIM. When completed, it
will be integrated with the PSRC UrbanSim land use model within the
OPUS software environment. While the new model system was being
designed, a preliminary version consisting of an activity generator was
integrated with the existing four-step model. This hybrid model
system is being used while the full AB model system is under
development. Here are technical documents that have been produced
during this project
.
Activity
generator
estimation,
calibration
and
user
guide
(2008)
Activity
Model
Work
Plan & Activity Generation Model: Work Plan Report
(2008)
Development
and
Implementation
of an Activity-Based Transport Model System: Report
1: Design Issues and Their Resolution
(2009)
Planning studies for advanced model
development
Planning and design studies have been
conducted for the Southern California Association of Governments (SCAG)
and for the Tampa Bay region of Florida. Here are the reports
from those studies.
Tampa
Bay
region
(2008)
SCAG
(2009)
Software
The discrete response models in the above
papers and projects were all estimated with
ALOGIT software. ALOGIT can be
used to estimate very large MNL and nested logit models required in
practical
transportation and other choice model applications.
The latest version, ALOGIT 4, can use simulation methods to
estimate logit models with random parameters (ie, mixed logit,
error-components
logit, logit kernel). For
information about ALOGIT see http://www.alogit.com. For information about potential
discounts, email John_L_Bowman@alum.mit.edu.