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Minnesota Department of Transportation (Mn/DOT) needs improved traffic monitoring tools to optimally allocate road maintenance and improvement resources. In particular, the department needs a method of including vehicle and axle weights with portable traffic logging equipment. The cost of existing Weigh-in-Motion (WIM) equipment prevents widespread use in locations where only temporary monitoring is needed. This project was a survey of the suppliers of portable WIM systems, allowing a few systems to be moved between locations of interest. There were four candidate systems found and studied, of which two are recommended for further evaluation. Both systems appear to meet the needs Mn/DOT established and local testing will allow a final decision on their suitability.

The Minnesota Local Road Research Board, MnDOT, and SRF performed an evaluation of a portable weigh-inmotion (WIM) system at several locations throughout Minnesota. The system was developed at the University of Minnesota-Duluth and offers roadway designers a low-cost method for obtaining vehicle load distribution data across the state's road network. To deploy the system, the weigh pads of the system were temporarily affixed sensors across the roadway lanes. As vehicles passed over the weigh pads, pressure sensors within the pads detected the weight of vehicles and the system recorded the data for later analysis. Traditional methods for travel monitoring generate traffic volume and classification data, but weigh-in-motion systems give designers a more accurate idea of current and projected traffic loading demands. SRF's testing provided implementation refinements that were incorporated into the system. During the two-year deployment process, the portable WIM system was installed under a wide array of environmental conditions to demonstrate the system's capabilities. Data generated by the system was analyzed. The Final Report details system deployment, calibration, and system accuracy.

Conventional methods for detecting vehicles for permanent travel monitoring stations have relied on detecting physical attributes of vehicles without correlating these with the specific vehicles and/or motor vehicle freight operators. However, by using a license plate reader camera, information can be gathered and cross referenced to other known data related to the specific vehicle assigned to the license plate. This could provide additional tools for enforcing overweight vehicles or targeting enforcement communication with freight carriers that consistently violate weight limits. The analysis conducted during this project compared machine-read license plates to manually collected license plates. The license plates were read as vehicle travelled highway speeds in a generally uncontrolled environment. Analysis is also provided that correlates hours of direct sunlight with accuracy of the automated reader. A second analysis was conducted as an effort to improve the accuracy of the Minnesota Department of Transportation's weigh-in-motion classification scheme and bring it in line with the Department's classification scheme for automatic traffic recorder stations (sites with axle-based detection that do not collect weight information).

Weigh-In-Motion (WIM) system tends to go out of calibration from time to time, as a result generate biased and inaccurate measurements. Several external factors such as vehicle speed, weather, pavement conditions, etc. can be attributed to such anomaly. To overcome this problem, a statistical quality control technique is warranted that would provide the WIM operator with some guidelines whenever the system tends to go out of calibration. A mixture modeling technique using Expectation Maximization (EM) algorithm was implemented to divide the Gross Vehicle Weight (GVW) measurements of vehicle class 9 into three components, (unloaded, partially loaded, and fully loaded). Cumulative Sum (CUSUM) statistical process technique was used to identify any abrupt change in mean level of GVW measurements. Special attention was given to the presence of auto-correlation in the data by fitting an auto-regressive time series model and then performing CUSUM analysis on the fitted residuals. A data analysis software tool was developed to perform EM Fitting and CUSUM analyses. The EM analysis takes monthly WIM raw data and estimates the mean and deviations of GVW of class 9 fully loaded trucks. Results of the EM analyses are stored in a file directory for CUSUM analysis. Output from the CUSUM analysis will indicate whether there is any sensor drift during the analysis period. Results from the analysis suggest that the proposed methodology is able to estimate a shift in the WIM sensor accurately and also indicate the time point when the WIM system went out-of-calibration. A data analysis software tool, WIM Data Analyst, was developed using the Microsoft Visual Studio software development package based on the Microsoft Windows® .NET framework. An open source software tool called R.NET was integrated into the Microsoft .NET framework to interface with the R software which is another open source software package for statistical computing and analysis.

Installing permanent in-pavement weigh-in-motion (WIM) stations on local roads is very expensive and requires recurring costs of maintenance trips, electricity, and communication. For county roads with limited average daily traffic (ADT) volume, such a high cost of installation and maintenance is rarely justifiable. One solution to bring WIM technologies to local roads is to utilize a portable WIM system, much like pneumatic tube counters used in short-duration traffic counts. That is, a single unit is reused in multiple locations for few days at a time. This way, WIM data is obtained without the cost of permanent in-pavement WIM stations. This report describes the results of a two-year research project sponsored by the Minnesota Department of Transportation (MnDOT) to develop a portable WIM system that can be readily deployed on local roads. The objective of this project was to develop a portable WIM system that would be used much like a pneumatic tube counter. The developed system is battery operated, low cost, portable, and easily installable on both rigid and flexible pavements. The report includes a sideby- side comparison of data between the developed on-pavement portable WIM system and an in-pavement permanent WIM system.

This project focused on the enhancement and evaluation of a battery-less wireless weigh-in-motion (WIM) sensor for improved enforcement of road weight restrictions. The WIM sensor is based on a previously developed vibration energy harvesting system, in which energy is harvested from the vibrations induced by each passing vehicle to power the sensor. The sensor was re-designed in this project so as to reduce its height, allow it to be installed and grouted in an asphalt pavement, and to protect the piezo stacks and other components from heavy shock loads. Two types of software interfaces were developed in the project: a) An interface from which the signals could be read on the MnDOT intranet b) An interface through a wireless handheld display Tests were conducted at MnRoad with a number of test vehicles, including a semi tractor-trailer at a number of speeds from 10 to 50 mph. The sensor had a monotonically increasing response with vehicle weight. There was significant variability in sensor response from one test to another, especially at the higher vehicle speeds. This variability could be attributed to truck suspension vibrations, since accelerometer measurements on the truck showed significant vibrations, especially at higher vehicle speeds. MnDOT decided that the final size of the sensor was too big and could pose a hazard to the traveling public if it got dislodged from the road. Hence the task on evaluation of the sensor at a real-world traffic location was abandoned and the budget for the project correspondingly reduced.

Bull-Converter/Reporter is a software stack for Weigh-In-Motion (WIM) data analysis and reporting tools developed by the University of Minnesota Duluth for the Minnesota Department of Transportation (MnDOT) to resolve problems associated with deployment of multi-vendor WIM systems in a statewide network. These data tools have been used by the MnDOT Office of Transportation System Management (OTSM) since their initial delivery in 2009. The objective of this project was to expand the current conversion capabilities of BullConverter to include more raw data formats from different companies and the current BullReporter functions to include new analysis and reporting capabilities. Data analysis needs change over time; and the members of the OTSM WIM section identified several new functions that would increase efficiency and improve quality of WIM data. This report describes the new reporting and conversion functions implemented in this project.

A complete portable weigh-in-motion (PWIM) system consists of a pair of weigh-pads (one for upstream and the other for downstream), a controller which translates raw load signals to WIM data, and an optional external battery pack. The weigh-pad dimensions are one foot wide and 24 feet long, covering two lanes. This document describes how to install and remove weigh-pads using the recommended tools and setup of the controller. The operation of controller that includes initial setup and calibration is described step-by-step. The controller stores WIM data in the controller hard disk using a comma separated values (CSV) format; the details of the CSV file naming convention and column formats are described.

Building a WIM system around polymer piezoelectric film sensors, called BL sensors, costs only a fraction of the traditional WIM system built around crystalline-quartz piezoelectric sensors called Lineas sensors. However, BL sensors are highly sensitive to temperature, which limits the accuracy of weight measurements. The objective of this research was to investigate the performance of BL sensors head-to-head with Lineas sensors by installing a BL WIM system and collecting data from the same highway. After the test site installation, pavement temperatures were recoded as part of each vehicle record from both Lineas and BL sensor-based WIM stations. The analysis of data collected over 10 months showed that temperature dependency of BL sensors can be removed in terms of average but not variance. More specifically, the average of axle weights after temperature-based calibration was about the same for both BL and Lineas sensors, but the variance was much higher for BL sensors. In conclusion, if BL sensors are used, pavement temperatures must be recorded as part of vehicle records. Then, the weights calibrated based temperature would be as accurate as Lineas sensors in terms of the average but not variance.

Presently, the Office of Transportation Data & Analysis (TDA) at the Minnesota Department of Transportation (Mn/DOT) manages 29 Vehicle Classification (VC) sites and 12 Weigh-in-Motion (WIM) sites installed on various Minnesota roadways. The data is collected 24/7 from all sites, resulting in a large amount of data. The total amount of data is expected to substantially grow with time due to the continuous accumulation of data from the present sites and future expansion of sites. Therefore, there is an urgent need to develop an efficient data management strategy for dealing with the present needs and future growth of this data. The solution proposed in this research project is to develop a centralized data warehouse from which all applications can acquire the data. The objective of this project was to develop software for creating a VC/WIM data warehouse and example applications that utilize it. This project was successfully completed by developing the software necessary to build the VC/WIM data warehouse and the application software packages that utilize the data. The main contribution of this project is that it provides a single access point for querying all of the Mn/DOT's WIM and VC data, from which many more applications can be developed without concerns of proprietary binary formats.