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Data Collection for Measuring Performance of Integrated Transportation Systems

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Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 144))

Abstract

More than ever, traffic congestion is plaguing our heavily populated metropolitan areas. Transportation professionals have recognized that we cannot build our way out of this ever-increasing congestion. The challenge over the next decade is to get more out of the existing transportation system by improving its productivity. To address this challenge, we must evolve into “system managers”: agencies and individuals who manage the system through operational strategies, complemented by targeted expansion investments. The concept of system management has been embraced by many agencies at both state and federal levels. For example, the California Department of Transportation (Caltrans) and most of its stakeholders adopted the concept of the System Management pyramid, as depicted in Fig. 3.1. The foundation of system management is “System Monitoring and Evaluation”. This foundation provides support for a variety of informed investment decisions.

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Acknowledgments

The authors thank Kai Leung of Caltrans’ Division of Traffic, Paul Chiu, James Lau, and Lindy Cabugao with Caltrans District 4, Sonja Sun, Don Dean, and Greg Larson of Caltrans’ Division of Research and Innovation, Frank Burton of Samtrans, Fanping Bu, Yue Li, and Scott Johnston of California PATH, Guoyuan Wu, Offer Grembek, Amy Wang, Peter Lau, Joe Liu, and Yao Ma of University of California at Berkeley for their contributions and support toward the Parsons T2 Lab.

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Correspondence to Wei-Bin Zhang .

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The paper is dedicated to the memory of former PATH director Robert E. Parsons.

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© 2010 Springer Science+Business Media, LLC

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Zhang, WB., Skabardonis, A., Li, M., Li, J., Zhou, K., Zhang, L. (2010). Data Collection for Measuring Performance of Integrated Transportation Systems. In: Barceló, J., Kuwahara, M. (eds) Traffic Data Collection and its Standardization. International Series in Operations Research & Management Science, vol 144. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-6070-2_3

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