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ARTICLE
Inverse Analysis of Origin-Destination matrix for Microscopic Traffic Simulator
Computer Modeling in Engineering & Sciences 2017, 113(1), 71-87. https://doi.org/10.3970/cmes.2017.113.068
Abstract
Microscopic traffic simulations are useful for solving various traffic- related problems, e.g. traffic jams and accidents, local and global environmental and energy problems, maintaining mobility in aging societies, and evacuation plan- ning for natural as well as man-made disasters. The origin-destination (OD) matrix is often used as the input to represent traffic demands into traffic simulators. In this study, we propose an indirect method for estimating the OD matrix using a traffic simulator as an internal model. The proposed method is designed to output results that are consistent with the input of the simulator. The method consists of the following steps: (1) calculating link traffic volume from the OD matrix, and (2) updating the matrix. The estimated matrix is updated iteratively until it converges to a predefined tolerance level. Numerical experiments are then conducted using the proposed method on a grid network and on a representation of an actual road network. Finally, we discuss the characteristics of the proposed method and the non-negative constraint for the traffic volume.Keywords
OD estimation, inverse problem, traffic simulation, Levenberg-Marquardt method, iterative method.
Cite This Article
APA Style
Abe, K., Fujii, H., Yoshimura, S. (2017). Inverse Analysis of Origin-Destination matrix for Microscopic Traffic Simulator. Computer Modeling in Engineering & Sciences, 113(1), 71–87. https://doi.org/10.3970/cmes.2017.113.068
Vancouver Style
Abe K, Fujii H, Yoshimura S. Inverse Analysis of Origin-Destination matrix for Microscopic Traffic Simulator. Comput Model Eng Sci. 2017;113(1):71–87. https://doi.org/10.3970/cmes.2017.113.068
IEEE Style
K. Abe, H. Fujii, and S. Yoshimura, “Inverse Analysis of Origin-Destination matrix for Microscopic Traffic Simulator,” Comput. Model. Eng. Sci., vol. 113, no. 1, pp. 71–87, 2017. https://doi.org/10.3970/cmes.2017.113.068

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