Sequential Modeling Framework for Optimal Sensor Placement for Multiple Intelligent Transportation System Applications
Publication: Journal of Transportation Engineering
Volume 137, Issue 2
Abstract
Traffic sensors have been deployed for decades to freeways to meet the requirements of various traffic/transportation applications, most noticeably traffic control and traveler information applications. A unique feature of traffic sensor deployment is that it is a continuous and evolving process. That is, with new applications that emerge, additional sensors are usually required to be deployed to meet new requirements. This process is also sequential in nature and the new deployment has to consider existing sensors. In this paper, we propose a modeling framework to capture this sequential decision-making process for traffic sensor deployment. The framework is based on our recent findings that (1) optimal sensor deployment for a single application can be determined by a staged process or, more formally, a dynamic programming (DP) method and (2) new sensor locations for new applications can be optimally solved by the DP method via considering existing sensors. We illustrate the framework using two applications: ramp metering control and travel time estimation. It is found that the proposed scheme can appropriately capture the decision-making process of traffic sensor deployment and can generate optimal sensor placement at any stage by considering sensors that have already been deployed. The model is tested using global positioning system enabled cell phone data and traffic simulation on a real-world freeway route in the San Francisco Bay Area.
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Acknowledgments
The writers would like to thank the three anonymous referees for their insightful comments and helpful suggestions on an earlier version of the paper. This research is partially supported by the California Department of Transportation (Caltrans) through the California PATH program at the University of California, Berkeley.
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Information & Authors
Information
Published In
Journal of Transportation Engineering
Volume 137 • Issue 2 • February 2011
Pages: 112 - 120
Copyright
© 2011 ASCE.
History
Received: May 28, 2009
Accepted: Jun 7, 2010
Published online: Jan 14, 2011
Published in print: Feb 2011
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