Micro-simulation of daily activity-travel patterns for travel demand forecasting

Ryuichi Kitamura; Cynthia Chen; Ram M. Pendyala; Ravi Narayanan

doi:10.1023/A:1005259324588

Micro-simulation of daily activity-travel patterns for travel demand forecasting

Ryuichi Kitamura, Cynthia Chen, Ram M. Pendyala, Ravi Narayanan

Research output: Contribution to journal › Article › peer-review

163 Scopus citations

Abstract

The development and initial validation results of a micro-simulator for the generation of daily activity-travel patterns are presented in this paper. The simulator assumes a sequential history and time-of-day dependent structure. Its components are developed based on a decomposition of a daily activity-travel pattern into components to which certain aspects of observed activity-travel behavior correspond, thus establishing a link between mathematical models and observational data. Each of the model components is relatively simple and is estimated using commonly adopted estimation methods and existing data sets. A computer code has been developed and daily travel patterns have been generated by Monte Carlo simulation. Study results show that individuals' daily travel patterns can be synthesized in a practical manner by micro-simulation. Results of validation analyses suggest that properly representing rigidities in daily schedules is important in simulating daily travel patterns.

Original language	English (US)
Pages (from-to)	25-51
Number of pages	27
Journal	Transportation
Volume	27
Issue number	1
DOIs	https://doi.org/10.1023/A:1005259324588
State	Published - 2000
Externally published	Yes

Keywords

Daily activity-travel patterns
Forecasting
Micro-simulation
Synthetic travel patterns

ASJC Scopus subject areas

Civil and Structural Engineering
Development
Transportation

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10.1023/A:1005259324588

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@article{b5fb0e3efe5142849ac10924f94bbab8,

title = "Micro-simulation of daily activity-travel patterns for travel demand forecasting",

abstract = "The development and initial validation results of a micro-simulator for the generation of daily activity-travel patterns are presented in this paper. The simulator assumes a sequential history and time-of-day dependent structure. Its components are developed based on a decomposition of a daily activity-travel pattern into components to which certain aspects of observed activity-travel behavior correspond, thus establishing a link between mathematical models and observational data. Each of the model components is relatively simple and is estimated using commonly adopted estimation methods and existing data sets. A computer code has been developed and daily travel patterns have been generated by Monte Carlo simulation. Study results show that individuals' daily travel patterns can be synthesized in a practical manner by micro-simulation. Results of validation analyses suggest that properly representing rigidities in daily schedules is important in simulating daily travel patterns.",

keywords = "Daily activity-travel patterns, Forecasting, Micro-simulation, Synthetic travel patterns",

author = "Ryuichi Kitamura and Cynthia Chen and Pendyala, {Ram M.} and Ravi Narayanan",

note = "Funding Information: This study was supported by the Los Alamos National Laboratory through a contract to the Institute of Transportation Studies, University of California at Davis, by the National Science Foundation through a grant to the National Institute of Statistical Sciences for the project “Measurement, Modeling and Prediction for Infrastructural Systems” (DMS 9313013), and the Japanese Ministry of Education, under the Grant-in-Aid for Scientific Research (B)(2) to Kyoto University. The authors are grateful to the Southern California Association of Governments who provided the data used in this study.",

year = "2000",

doi = "10.1023/A:1005259324588",

language = "English (US)",

volume = "27",

pages = "25--51",

journal = "Transportation",

issn = "0049-4488",

publisher = "Springer Netherlands",

number = "1",

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TY - JOUR

T1 - Micro-simulation of daily activity-travel patterns for travel demand forecasting

AU - Kitamura, Ryuichi

AU - Chen, Cynthia

AU - Pendyala, Ram M.

AU - Narayanan, Ravi

N1 - Funding Information: This study was supported by the Los Alamos National Laboratory through a contract to the Institute of Transportation Studies, University of California at Davis, by the National Science Foundation through a grant to the National Institute of Statistical Sciences for the project “Measurement, Modeling and Prediction for Infrastructural Systems” (DMS 9313013), and the Japanese Ministry of Education, under the Grant-in-Aid for Scientific Research (B)(2) to Kyoto University. The authors are grateful to the Southern California Association of Governments who provided the data used in this study.

PY - 2000

Y1 - 2000

N2 - The development and initial validation results of a micro-simulator for the generation of daily activity-travel patterns are presented in this paper. The simulator assumes a sequential history and time-of-day dependent structure. Its components are developed based on a decomposition of a daily activity-travel pattern into components to which certain aspects of observed activity-travel behavior correspond, thus establishing a link between mathematical models and observational data. Each of the model components is relatively simple and is estimated using commonly adopted estimation methods and existing data sets. A computer code has been developed and daily travel patterns have been generated by Monte Carlo simulation. Study results show that individuals' daily travel patterns can be synthesized in a practical manner by micro-simulation. Results of validation analyses suggest that properly representing rigidities in daily schedules is important in simulating daily travel patterns.

AB - The development and initial validation results of a micro-simulator for the generation of daily activity-travel patterns are presented in this paper. The simulator assumes a sequential history and time-of-day dependent structure. Its components are developed based on a decomposition of a daily activity-travel pattern into components to which certain aspects of observed activity-travel behavior correspond, thus establishing a link between mathematical models and observational data. Each of the model components is relatively simple and is estimated using commonly adopted estimation methods and existing data sets. A computer code has been developed and daily travel patterns have been generated by Monte Carlo simulation. Study results show that individuals' daily travel patterns can be synthesized in a practical manner by micro-simulation. Results of validation analyses suggest that properly representing rigidities in daily schedules is important in simulating daily travel patterns.

KW - Daily activity-travel patterns

KW - Forecasting

KW - Micro-simulation

KW - Synthetic travel patterns

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JO - Transportation

JF - Transportation

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Micro-simulation of daily activity-travel patterns for travel demand forecasting

Abstract

Keywords

ASJC Scopus subject areas

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