Use of Weigh-in-motion Data for Pavement, Bridge, Weight Enforcement, and Freight Logistics Applications PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Use of Weigh-in-motion Data for Pavement, Bridge, Weight Enforcement, and Freight Logistics Applications PDF full book. Access full book title Use of Weigh-in-motion Data for Pavement, Bridge, Weight Enforcement, and Freight Logistics Applications by Darren G. Hazlett. Download full books in PDF and EPUB format.
Author: Darren G. Hazlett Publisher: ISBN: 9780309481250 Category : Bridges Languages : en Pages : 0
Book Description
Most U.S. state departments of transportation (DOTs) are collecting weigh-in-motion data with a wide variety of sensor types and using them in a variety of applications. Many agencies use WIM data to aid in pavement design, although most are not currently using a Pavement ME (mechanistic-empirical) Design application. WIM for bridge and asset management purposes is used much less often. The TRB National Cooperative Highway Research Program's NCHRP Synthesis 546: Use of Weigh-in-Motion Data for Pavement, Bridge, Weight Enforcement, and Freight Logistics Applications documents how DOTs incorporate weigh-in-motion data into such applications as bridge and pavement design and management, load ratings, weight enforcement support, and freight planning and logistics.
Author: Darren G. Hazlett Publisher: ISBN: 9780309481250 Category : Bridges Languages : en Pages : 0
Book Description
Most U.S. state departments of transportation (DOTs) are collecting weigh-in-motion data with a wide variety of sensor types and using them in a variety of applications. Many agencies use WIM data to aid in pavement design, although most are not currently using a Pavement ME (mechanistic-empirical) Design application. WIM for bridge and asset management purposes is used much less often. The TRB National Cooperative Highway Research Program's NCHRP Synthesis 546: Use of Weigh-in-Motion Data for Pavement, Bridge, Weight Enforcement, and Freight Logistics Applications documents how DOTs incorporate weigh-in-motion data into such applications as bridge and pavement design and management, load ratings, weight enforcement support, and freight planning and logistics.
Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
At hundreds of Weigh in Motion (WIM) stations, State Departments of Transportation collect traffic data every year to support pavement design, to enforce weight restrictions on highways and bridges, and to provide planning data for highway improvements. Reliable WIM data is particularly important to support the procedures in the FHWA Mechanistic Empirical Pavement Design Guide (MEPDG). The purpose of the research is to identify and resolve four related but relatively stand-alone problems associated with WIM data collected by NCDOT. Quality Control: After the NCDOT collects WIM data and converts it from proprietary vendor format to an ASCII text format, the quality of the data must be checked. During the quality control (QC) procedures, tests identify incomplete datasets, out of range values for individual vehicle classes, and other possible data problems. Vehicle class and weight checks generate 0.97% and 6.42% anomalies, respectively thus confirming that NCDOT equipment captured reliable WIM measurements. NC Urban and Rural Truck Traffic Profiles: Knowing the type of traffic by vehicle class by highway functional classification is critical to designing, maintaining and paying for North Carolina highway pavements. Thus, GVW plots by vehicle class and highway functional class are very important. The results indicate that in general, the class 5 and 9 GVW plots for all categories of WIM stations show expected trends. These results may be used by highway planners and pavement designers to quickly determine typical truck traffic profiles in the various NC regions and provide insight into NC truck transportation flows. NC vs. University Of Arkansas WIM QC Analysis: Most highway agencies have the data collection and design groups in different units. While a single software solution is not practical, it is recommended to perform two separate processes where the output of data QC meets the needs and standards of the design process. A comparative analysis between the QC meth.
Author: Wiley D. Cunagin Publisher: ISBN: Category : Transportation Languages : en Pages : 48
Book Description
"This synthesis will be of interest to planners, pavement designers, administrators, and others interested in knowing the actual weights of vehicles using the highways. Information is presented on current uses of weigh-in-motion systems that can obtain the data needed to properly plan and design highways."--Avant-propos.
Author: Muhammad Munum Masud Publisher: ISBN: Category : Electronic dissertations Languages : en Pages : 0
Book Description
Weigh-in-Motion (WIM) technology is one of the primary tools used for pavement management. It can provide essential and accurate truck traffic information, including vehicle class and speed, vehicle count, gross vehicle weight (GVW), single axle (SA) and tandem axle (TA) weights, axle spacing, and the date and time of the event. The State Departments of Transportation (DOTs) gather WIM data for various applications, including highway planning, pavement and bridge design, commercial vehicle weight enforcement, asset management, and freight planning and logistics. Overloaded trucks pose severe challenges to road transport operations. Overloaded trucks can cause more damage to the pavement systems than trucks loaded within legal weight limits. Truck overloading can also lead to severe consequences if involved in a traffic accident. Law enforcement agencies divert potentially overloaded trucks to static scales and issue tickets based on the information collected at a WIM station. Because of the wide range of applications, the data obtained at WIM stations must be accurate, consistent, and reflect actual field conditions.This study addressed four critical concerns related to WIM equipment performance, calibration needs, traffic loading data quality, and applications. Precisely, the current research advanced the state of the practice knowledge about (a) potential factors impacting WIM system accuracy, (b) accuracy and consistency of traffic loading data and calibration needs of WIM stations, (c) revised/modified guidelines for WIM equipment calibration, and (d) estimation of commercial freight tonnage from Gross Vehicle Weight (GVW) data. The research objectives were accomplished by synthesizing and analyzing the WIM performance and traffic loading data available in the Long Term Pavement Performance (LTPP) traffic database and data available through other state DOTs. The WIM sites analyzed in this study are from 30 states within the United States and 3 Canadian provinces. Several factors can affect the WIM system accuracy (i.e., measurement error). The potential site-related factors include road geometry, pavement stiffness, surface distresses, roughness, and climate. Decision tree models were developed in this study to illustrate a potential for estimating the expected WIM measurement error range using information about the WIM site and sensor-related factors. The results show that the sensor array and sensor types are the most important predictors, followed by WIM controller functionality (speed points). The data analysis and results also show that the climate can be important for some sensor types. One can integrate this information with equipment installation and life cycle costs to determine the most reliable and economical WIM equipment while also considering accuracy requirements by WIM data users.One way to evaluate WIM measurement errors is by using the data collected immediately before and after equipment calibration. The limitation of this approach is that the data represent a snapshot in time and may not represent a long-term WIM site performance. Consequently, an alternative approach was needed to characterize temporal variations in WIM data consistency. This study presents a method to estimate WIM system accuracy based on axle load spectra attributes [Normalized Axle Load Spectra (NALS) shape factors]. This analysis's main objective is to determine WIM system errors based on axle loading without physically performing equipment calibration. Using NALS to estimate WIM system accuracy can save a significant amount of time and resources, usually spent on equipment calibrations yearly.Successful WIM equipment calibration can eliminate systematic weight, speed, and axle spacing errors. The suggested changes in current WIM calibration procedures related to truck type (loaded truck), number of truck runs, and truck speed (multiple speed points) can significantly reduce the time and resources needed for successful equipment calibration. Accurate freight tonnage estimates and trends are essential due to their implications on economic, infrastructure development, and transportation policy decision-making. This study presents a practical application of WIM data to estimate freight tonnage and classify commodity types. The payloads computed for Class 9 trucks from GVW data strongly correlated with the average freight tonnage obtained from a commercial data source, i.e., Transearch from the IHS market. The user can independently verify the freight estimates from surveys at locations close to WIM sites.
Author: Publisher: ISBN: Category : Government publications Languages : en Pages : 96
Book Description
This demonstration project allowed Wisconsin Dept. of Transportation to test the overall performance of Bridge weigh in motion equipment as well as develop an entirely new comprehensive and representative truck weight database.
Author: Darren G. Hazlett
Author: Darren G. Hazlett
Author: 
Author: 
Author: Wiley D. Cunagin
Author: Muhammad Munum Masud
Author: David A. Friedrichs
Author: Paul P. Stein
Author: Bruce Aunet
Author: A. T. Papagiannakis
Author: