Abstract
The micro-simulator of individuals’ daily travel, PCATS, and a dynamic network simulator, DEBNetS, are integrated to form a simulation system for urban passenger travel. The components of the simulation system are briefly described, and three areas of on-going system improvement are described, i.e., (i) introduction of stochastic frontier models of prism vertex location, (ii) adoption of a fine grid system for quasi-continuous representation of space, and (iii) use of MCMC algorithms to handle colossal choice sets. Application case studies demonstrate that micro-simulation is a practical approach for demand forecasting and policy analysis, especially in the area of demand management.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Arentze, T., A. Borgers, F. Hofman, S. Fujii, C. Joh, A. Kikuchi, R. Kitamura, H. Timmermans and P. van der Waerden (2001). Rule-based versus utility-maximizing models of activity-travel patterns: A comparison of empirical performance, In D. Hensher (ed.) Travel Behaviour Research: The Leading Edge, Elsevier Science, Oxford, pp.569–583.
Beckman, R.J., K.A. Baggerly and M.D. McKay (1996). Creating synthetic baseline populations, Transportation Research A, 30A, 415–429.
Chiang, J., S. Chib and C. Narasimhan (1999). Markov Chain Monte Carlo and models of consideration set and parameter heterogeneity, Journal of Econometrics, 89, 223–248.
Damm. D. (1982). Parameters of activity behavior for use in travel analysis, Transportation Research, 16A(2), 135–148.
Hägerstrand, T. (1970). What about people in regional science?, Papers of the Regional Science Association, 24, 7–21.
Hajivassiliou, V., D. McFadden and P. Ruud (1996). Simulation of multivariate normal rectangle probabilities and their derivatives: theoretical and computational results, Journal of Econometrics, 72, 85–134.
Hazelton, M.L., S. Lee and J.W. Polak (1996). Stationary states in stochastic process models of traffic assignment: a Markov Chain Monte Carlo approach, In J.-B. Lesort (ed.) Proceedings of the 13thInternational Symposium on Transportation and Traffic Theory, Pergamon, Oxford, pp. 341–357.
Fujii, S., A. Kikuchi and R. Kitamura (2000). A micro-simulation analysis of the effects of transportation control measures to reduce CO2 emissions: a case study in Kyoto City, Traffic Engineering, 35(4), 11–18 (in Japanese).
Fujii, S., M. Okushima, A. Kikuchi and R. Kitamura (1998). Development of a network flow simulator and evaluation of travel time, In the Proceedings of the 17thAnnual Meeting of the Japanese Society of Traffic Engineers, pp. 694–695 (in Japanese).
Fujii, S., Y. Otsuka, R. Kitamura and T. Monma (1997). A micro-simulation model system of individuals’ daily activity behavior that incorporates spatial, temporal and coupling constraints, Infrastructure Planning Review, 14, 643–652 (in Japanese).
Iida, Y., M. Iwabe, A. Kikuchi, R. Kitamura, K. Sakai, Y. Shiromizu, D. Nakagawa, M. Hatoko, S. Fujii, T. Morikawa and T. Yamamoto (2000). Micro-simulation based travel demand forecasting system for urban transportation planning, Infrastructure Planning Review, 17, 841–847 (in Japanese).
Kawata, H., Y. Iida and Y. Shiromizu (1999). Case study of evaluation for comprehensive transportation policy, The Proceedings of the Infrastructure Planning Review Annual Meeting, 22(1), 511–514 (in Japanese).
Kikuchi, A., S. Fujii and R. Kitamura (2001). Evaluation of transportation policies by micro-simulation of individuals’ behaviors on a coordinates system, City Planning Review, 36, 577–582 (in Japanese).
Kikuchi, A., S. Fujii, Y. Shiromizu and R. Kitamura (2000). Calibration of DEBNetS on a large-scale network, In the proceedings of the 20thAnnual Meeting of the Japanese Society of Traffic Engineers, Tokyo, pp. 49–52 (in Japanese).
Kikuchi, A, Y. Kato, T. Macuchi, S. Fujii and R. Kitamura (2002). Improvement and verification of dynamic traffic flow simulator “DEBNetS”, Infrastructure Planning Review, 19 (in press, in Japanese).
Kikuchi, A., A. Kobata, S. Fujii and R. Kitamura (2000). A mode and destination choice model on a GIS database: from zone-based toward coordinates-based methodologies of spatial representation, Infrastructure Planning Review, 17, 841–847 (in Japanese).
Kikuchi, A., T. Yamamoto, K. Ashikawa and R. Kitamura (2001). Computation of destination choice probabilities under huge choice sets: application of Markov Chain Monte Carlo algorithms, Infrastructure Planning Review, 18(4), 503–508 (in Japanese).
Kikuchi, A., R. Kitamura, S. Kurauchi, K. Sasaki, T. Hanai, T. Morikawa, S. Fujii and T. Yamamoto (1999). Effect Analysis of Transportation Policies using Micro-Simulation Method-A Case Study of Toyota City-, The Proceedings of the Infrastructure Planning Review Annual Meeting, 22(1), 817–820 (in Japanese).
Kitamura, R., C. Chen and R. Narayanan (1998). The effects of time of day, activity duration and home location on travelers’ destination choice behavior, Transportation Research Record, 1645, 76–81.
Kitamura, R. and S. Fujii (1998). Two computational process models of activity-travel behavior, In T. Gärling, T. Laitila and K. Westin (eds.) Theoretical Foundations of Travel Choice Modelling, Pergamon Press, Oxford, pp. 251–279.
Kitamura, R., S. Fujii, A. Kikuchi and T. Yamamoto (1998). Can TDM make urban transportation “sustainable”?: A micro-simulation study, Paper presented at International Symposium on Travel Demand Management, Newcastle, UK.
Kitamura, R., S. Fujii, T. Yamamoto and A. Kikuchi (2000). Application of PCATS/DEBNetS to regional planning and policy analysis: Micro-simulation studies for the Cities of Osaka and Kyoto, Japan, In the Proceedings of Seminar F, European Transport Conference 2000, pp. 199–210.
Kitamura, R., T. Yamamoto, K. Kishizawa and R.M. Pendyala (2000). Stochastic frontier models of prism vertices, Transportation Research Record, 1718, 18–26.
Kitamura, R., T. Yamamoto, K. Kishizawa and R.M. Pendyala (2001). Prism-based accessibility measures and activity engagement, Paper presented at the 80thAnnual Meeting of the Transportation Research Board, Washington, D.C., January.
Nishida, S., T. Yamamoto, S. Fujii and R. Kitamura (2000). A household attributes generation system for long-range travel demand forecasting with disaggregate models, Infrastructure Planning Review, 17, 779–787 (in Japanese).
Pendyala, R.M., T. Yamamoto and R. Kitamura (2002). On the formation of time-space prisms to model constraints on personal activity-travel engagement, Transportation, 29(1), 73–94.
Schmidt, P. and A. Witte (1989). Predicting criminal recidivism using split population survival time models, Journal of Econometrics, 40, 141–159.
Yamamoto, Y., R. Kitamura and R.M. Pendyala (2002). Comparative analysis of time-space prism vertices for out-of-home activity engagement on working days and non-working days, Submitted to Geographical Analysis.
Yamamoto, T., R. Kitamura and K. Kishizawa (2001). Sampling alternatives from a colossal choice set: an application of the MCMC algorithm, Transportation Research Record, 1752, 53–61.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer Science+Business Media, Inc.
About this chapter
Cite this chapter
Kitamura, R., Kikuchi, A., Fujii, S., Yamamoto, T. (2005). An Overview of PCATS/DEBNetS Micro-simulation System: Its Development, Extension, and Application to Demand Forecasting. In: Kitamura, R., Kuwahara, M. (eds) Simulation Approaches in Transportation Analysis. Operations Research/Computer Science Interfaces Series, vol 31. Springer, Boston, MA. https://doi.org/10.1007/0-387-24109-4_14
Download citation
DOI: https://doi.org/10.1007/0-387-24109-4_14
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-24108-1
Online ISBN: 978-0-387-24109-8
eBook Packages: Business and EconomicsEconomics and Finance (R0)