Intelligent Pavement for Traffic Flow Detection – Phase II

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https://hdl.handle.net/11299/135748

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Title

Intelligent Pavement for Traffic Flow Detection – Phase II

Authors

Yu, Xun

Published Date

2012-09

Publisher

Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota

Type

Report

Abstract

This project is the extension of a Northland Advanced Transportation System Research Laboratory (NATSRL) FY09 project, titled as “Intelligent Pavement for Traffic Flow Detection”, which aims to explore a new approach in detecting vehicles on a roadway by making a roadway section as a traffic flow detector. Sections of a given roadway are paved with carbon-nanotube (CNT) enhanced pavement; the piezoresitive property of carbon nanotubes enables the pavement to detect the traffic flow. Meanwhile, CNTs can also work as reinforcement elements to improve the strength and toughness of the concrete pavement. The proposed sensor is expected to have a long service life with little maintenance and wide-area detection capability. In the FY09 project, lab tests demonstrated that CNT based cement composite can detect the mechanical stress levels for both static and dynamic loads. In the FY10 project, the research was extended to cement mortar, which has much higher mechanical strength and more useful in real applications. The effects of water level and CNT doping levels on the piezoresistivity of the composites were also studied. Preliminary road tests were performed for the evaluation of this new traffic sensor.

Keywords

Traffic detector

Vehicle detectors

Carbon nanotube

Composite pavements

Piezoresistive

Resistivity method

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Research Reports

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CTS 12-30

Funding information

Department of Mechanical and Industrial Engineering, University of Minnesota Duluth; Northland Advanced Transportation Systems Research Laboratories, University of Minnesota Duluth

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Yu, Xun. (2012). Intelligent Pavement for Traffic Flow Detection – Phase II. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/135748.

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