Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/23864
Title: Automated collection of mixer truck operations data in highly dense urban areas
Authors: Lu, M
Shen, X
Chen, W 
Keywords: Automation
Concrete
Construction management
Data collection
Global positioning
Simulation
Tracking
Trucks
Urban areas
Vehicles
Issue Date: 2009
Publisher: American Society of Civil Engineers
Source: Journal of construction engineering and management, 2009, v. 135, no. 1, p. 17-23 How to cite?
Journal: Journal of construction engineering and management 
Abstract: Our research has investigated the feasibility of directly sourcing autonomous operations data from a construction-vehicle positioning system, so as to enable productivity analysis and simulation modeling in the practical context of ready mixed concrete production and delivery. In this paper, we first review research efforts related to applying radio frequency identification tags and global positioning system for tracking construction resources and acquiring operations data in the field. We then describe the technical design and system components of an automated data collection (ADC) solution to accumulating concrete delivery operations data, which is extended from a construction-vehicle positioning system tailored for highly dense urban areas. We further elaborate on how our ADC system captures, transforms, and analyzes data of mixer truck operations. Truck-tracking experiment results based on field trials are presented to demonstrate the usefulness of data sourced from our ADC system with respect to: (1) analyzing truck-waiting time versus truck-unloading time on site; and (2) predicting truck's plant-to-site travel time. In conclusion, the ADC solution resulting from this research not only allows sophisticated analysis of mixer truck resource utilization at concreting sites situated in highly dense urban areas, but also provides an accumulation of input data that will enable concrete plant operations simulation modeling.
URI: http://hdl.handle.net/10397/23864
ISSN: 0733-9364
EISSN: 1943-7862
DOI: 10.1061/(ASCE)0733-9364(2009)135:1(17)
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