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EQUIPMENT FOR COLLECTING TRAFFIC LOAD DATA SUMMARY The traffic load data that are key to the design of pavement structures include truck volumes and the load spectra for those volumes. These data are obtained by counting trucks by class and by weighing a sample of trucks to obtain the load spectra associ- ated with each class of truck. Therefore, data collection equipment must allow for col- lecting both types of data. Weigh-in-motion (WIM) data collection equipment collects both truck volume and load spectra, but the equipment is more expensive to obtain and more difficult to install and operate than equipment that can only count and classify vehicles. Therefore, high- way agencies routinely use a combination of WIM and simpler vehicle classification equipment to collect the data they require for pavement design. This report summarizes the key issues and information needed by a state or other highway operating agency to select the equipment it needs to perform these tasks. It also summarizes the steps that must be taken to ensure that the equipment selected works as intended and that, as a consequence, the data collected accurately describe the vehicle fleet being measured. S.1 BASIC EQUIPMENT NEEDS A combination of permanent and portable data collection is needed to provide the traffic load data required for pavement design. Permanent devices provide more exten- sive datasets and are generally necessary for collecting the data needed to understand changes in traffic patterns associated with different days of the week and months of the year. Portable devices allow flexibility in collecting data and help ensure that data are collected from specific locations of interest. Portable devices also tend to lower the cost of collecting the geographically diverse and site-specific data needed to develop accu- rate pavement design loads. Therefore, a combination of devices--WIM and classification, permanent and portable--are needed to meet their traffic data collection needs for pavement design. Further expanding the need for diversity in the devices that many states will purchase and use is the fact that different technologies have different strengths and weaknesses. Some equipment works nearly flawlessly in rural areas and in moderate environmental
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2 conditions, but that same equipment may work poorly in urban stop-and-go traffic or where snow conditions disrupt driver lane discipline. Other devices work less accu- rately under the best of conditions but can still operate effectively in harsh data collec- tion conditions such as stop-and-go traffic or adverse weather. Making these tradeoffs is the most difficult part of selecting equipment. To make these tradeoffs correctly, and then to ensure that the selected equipment operates as intended, requires knowledge. Required areas of knowledge and necessary decisions and/or actions include the following: · Understanding the equipment's capabilities and limitations; · Understanding the data collection site's characteristics; · Choosing data collection locations that provide the best opportunity for collecting accurate data; · Selecting equipment for each site that can operate effectively in the traffic and environmental conditions present at that site; · Understanding how data collected from two different devices relate to each other (i.e., are the vehicle classes collected by two different classifiers the same, and if not, how do those classes relate to each other?); · Installing the equipment correctly; · Understanding how to test the equipment once it is in place to ensure that it is oper- ating as intended and ensuring that these procedures are followed; · Properly calibrating the equipment after it has been installed; · Understanding preventive and corrective "site" maintenance; · Performing quality control checks on the data produced by those devices; and · Repairing, re-calibrating, or otherwise adjusting the equipment and site conditions if quality assurance checks indicate that problems are occurring. While the choice of sensor technology can affect the accuracy of the data collected as well as the cost and longevity of the data collection installation, a wide body of research shows that technology is only one of many factors that affect the reliability of collected data. In fact, recent work done for the Federal Highway Administration (FHWA) concluded that "In general the differences between devices from different manufacturers were more significant than differences between technologies." The report also stated that "It is more important to select a well designed and highly reli- able product than to narrow a selection to a particular technology."1 This is not to say that technology choice is unimportant. Each technology has specific strengths and weaknesses. Understanding those strengths and weaknesses allows a high- way agency to select equipment that is more likely to work in a specific situation. While different vendors are often capable of designing around a given technology's weaknesses, the odds of obtaining accurate data are certainly increased by taking advantage of spe- cific technology strengths and avoiding known technology weaknesses. At the same time, as noted in the aforementioned FHWA study, some vendors do a poor job of imple- menting specific technologies. In addition, even the best technology from the best ven- dor will not work accurately if the device is poorly installed, maintained, or calibrated. The rest of this report describes an equipment selection process that guides interested parties toward the technologies that have demonstrated (in the literature published to date) specific strengths and away from technologies that have demonstrated specific weaknesses. Note that (1) this review is not universal (some data collection technolo- 1 Field Test of Monitoring of Urban Vehicle Operations Using Non-Intrusive Technologies, FHWA, May 1997, FHWA-PL-97-018, by Minnesota DOT and SRF Consulting.
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3 gies have undoubtedly been missed) and (2) data collection technology continues to evolve with time. Specific devices may come to market that are either not part of this review or have different attributes from the technologies reviewed in this report. There- fore, highway agencies are reminded to continually review available sources2 that describe equipment performance, to communicate frequently with neighboring states to learn about the performance of their data collection equipment and their experiences with vendors, and to monitor the performance of their equipment to ensure that it oper- ates as intended. S.2 SHORT-DURATION VEHICLE CLASSIFICATION EQUIPMENT The primary technological attributes that should be considered when short-duration vehicle classification equipment is selected include the following: · Whether the vehicle (tire) sensors need to be placed on the road surface or will measure from above or beside the pavement, · The type of vehicle classes that can be collected by the device, · The number of lanes that each device can observe, and · The effects that specific environmental conditions will have on equipment perfor- mance. These attributes are summarized in Table S.1 for the technologies commonly found on the market in 2002. To select equipment, the highway agency must also consider the cost of the equip- ment (capital, operations, maintenance, and other life-cycle cost considerations), the ability to integrate the data collected by a specific device into the state's traffic data management system (how the vendor's data retrieval software/system works and whether it integrates easily with the state's system), and the various support services and assurances offered by specific vendors, including warranties and other guaranties of performance, proof of previous successful performance (independent testing), the level of technical support offered, and the availability of training. In many cases, these additional factors are the deciding factor in equipment selection, especially when two alternative technologies have similar operating characteristics. All of the above factors are interrelated. In addition, each can be the deciding factor in an equipment selection decision. Thus, no single piece of equipment is always the best choice, and no single, simple decision process will lead to the correct equipment choice. The state must weigh the relative importance of these attributes each time it selects equipment. S.2.1 Intrusive or Non-Intrusive Sensors Perhaps the first question that should be asked when deciding between intrusive and non-intrusive equipment is "Can the portable equipment be safely installed in the road- way section in question?" In most cases, intrusive sensors provide more descriptive vehicle classification data than non-intrusive sensors, especially where the sensors pro- vide axle count and spacing information. They are therefore normally better options for portable classification counts than non-intrusive sensors if they can be safely placed on the road surface. 2 On-line resources are provided at the end of this summary, as are references to some conventionally published works.
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TABLE S.1 Short-duration classification technology comparisons
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5 However, if intrusive equipment cannot be safely installed in the roadway, by default, the highway agency must consider non-intrusive3 vehicle classification equipment, even though that equipment places significant constraints on the types of truck classi- fications that can be collected and limits the devices that are available for selection. In some locations, the alternatives to non-intrusive sensors are "no data collection" or "data collection only when full traffic control can be provided." S.2.2 Vehicle Classes Collected The mechanistic-empirical pavement design software (which is being developed under NCHRP Project 1-37A) uses the number of axles by axle configuration as an input to the design process. Therefore, in general, data collection equipment that can collect and classify vehicles by using axle count and axle spacing as inputs is prefer- able over other classification equipment. Ideally, the classification procedure used by a portable counter should match that used by WIM devices in the state. The highway agency can accomplish this by supplying the vendor of a selected device with the clas- sification algorithm used to convert axle count and spacing information into an esti- mate of vehicle classification. It is strongly recommended that the equipment be able to accept the specific classification algorithm that a state has tested and approved. (A highway agency should also test to ensure that the correct algorithm has in fact been installed and is operating as intended.) There are cases in which axle-based truck classes cannot be collected (normally because axle sensors cannot be safely placed on the roadway or because traffic flow is unstable, and axle spacings cannot be accurately measured). Where these conditions are expected, it is acceptable to select portable classification equipment that collects truck volume data using other vehicle classes. This usually means classifying vehicles by overall vehicle length. It is important, however, that the state be able to correlate these classes to those used by its WIM system. States are not advised to purchase vehi- cle classification equipment that produces volume estimates that cannot be correlated effectively with their WIM data. S.2.3 Lanes of Data Collected: Operational and Geometric Considerations The next consideration in equipment selection is to understand how many traffic lanes can be monitored by each piece of equipment. For sensors, this normally means determining whether an individual sensor measures one or more lanes, and if more than one lane, whether the data are reported for each lane individually or for all lanes com- bined. For data collection electronics, this means understanding whether the device can accept sensor inputs from more than one lane of traffic simultaneously. Many of the older intrusive technologies (e.g., traditional road tubes) only collect data in the outside lane of a facility when they are used as portable detectors. Others (e.g., fiber-optic cable and the new multi-lane road tubes) can collect inside lane data, but only when special precautions are taken to protect the sensor from being dislodged by traffic in the adjacent lanes. When placed, these sensors must be carefully aligned with the existing lane lines to collect accurate truck volume data. Another concern with axle spaced-based classification counting is that unstable traf- fic flow speed (stop-and-go traffic in particular) makes the output of many devices 3 If the number of these sites is small, the highway agency can also construct "permanent" sensor installations and then rotate data collection electronics among these locations. However, for the purposes of this report, these are considered "permanent" devices and are discussed later in the report.
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6 unreliable. Technologies that can classify correctly without vehicles traveling at a con- sistent speed are therefore required. These tend to use much broader vehicle classifi- cation schemes because these broader schemes are less susceptible to minor errors in length measurement. (Thus, simple length classifiers tend to classify more accurately in congested road sections than do axle sensor-based devices.) Both operational characteristics and the number of lanes to be counted are deter- mined by the geometric configuration of the roadway. In some instances, more accu- rate data for pavement design can be obtained by moving upstream or downstream of a desired data collection location. While this makes the data collection site less site spe- cific, it often allows for placement of data collection sensors on a road section with geo- metric features that are more conducive to accurate classification counting. This is an acceptable practice for use with TrafLoad (which is being developed under NCHRP Project 1-39) and the pavement design software so long as the truck volumes collected provide an accurate measure of the traffic crossing the pavement design section. S.2.4 Environmental Considerations Environmental conditions can degrade the performance of specific technologies, espe- cially when those devices are used in a portable mode. For example, snow decreases vehi- cles' lane discipline and thus badly affects count and classification accuracy for most lane-specific count technologies (although few portable devices are placed during potential snow conditions). Devices that must be taped to the road surface (tape switches, portable fiber-optic cables, portable piezoelectric film or cable) often do not remain in place very long when the sensors must be placed on wet pavement. Thus, in wet conditions, technologies such as road tubes that can be held in place by pavement nails tend to be better choices. Non- intrusive detection devices that are not affected by wet pavement conditions also tend to perform better than these sensors. However, non-intrusive detectors can be affected by other environmental factors. For example, video detectors tend to work poorly when visibility is low (e.g., in heavy snow, glare, dust storms, or fog). They make a poor choice for locations subject to these environmental conditions. Infrared sensors have also been shown to perform poorly when visibility is low. Some acoustic sensors have shown performance degradation in cold weather. S.3 PERMANENT VEHICLE CLASSIFICATION EQUIPMENT For purposes of this report, "permanent" equipment is differentiated from "short- duration" equipment both because permanent equipment requires more resources to initially place and because its counting session can (but does not necessarily have to) last longer. (That is, permanent equipment cannot be quickly placed at a location that has not been prepared, while the short-duration equipment can.) Thus, devices that can be slid in and out of a conduit placed under the pavement are considered permanent because of the effort required to initially install the conduit, even though once that con- duit has been laid, the sensors themselves can be placed or removed quickly. The attributes of the alternative permanent vehicle classification technologies are summarized in Table S.2. As with short-duration classification counters, these attributes are only part of the information required to choose among alternative devices. In many cases, the other considerations in equipment selection (price, vendor support, and war- ranties) are even more important than the characteristics of the specific technologies.
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TABLE S.2 Permanent classification technology comparisons (continued on next page)
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TABLE S.2 (Continued)
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9 S.3.1 Choosing Between Intrusive and Non-Intrusive Sensors As with short-duration classifiers, a key consideration is whether conditions require the use of non-intrusive sensors. As with short-duration counts, the primary drawback of non-intrusive sensors is that very few devices directly measure the number and con- figuration of axles. This reduces the accuracy of vehicle classification count informa- tion for the purpose of pavement design. However, there are conditions when this loss of pavement design accuracy is warranted. These conditions occur where pavement or environmental conditions would result in poor performance of intrusive, axle-based classifiers or where location considerations reduce the cost of non-intrusive sensors sig- nificantly relative to the cost of intrusive sensors. For example, non-intrusive sensors are particularly advantageous for locations where lane geometry will soon change. Because they are non-intrusive, changing the focal point (the exact space at which the sensor points and collects data) for most non- intrusive devices is fairly simple. This is not true for most permanently mounted, intru- sive devices. Thus, if a roadway will be restriped as part of an ongoing, long-term con- struction project, the choice of non-intrusive sensors makes sense. With intrusive sensors, the sensors initially placed are generally useless in the new lane configuration (they often cover parts of two lanes) and must be either dug up or abandoned. (Few sen- sors can be dug up and then reused.) It makes far better economic sense to place non- intrusive sensors in such a location, even though the data collected are less precise than desired, rather than either not collect data or purchase and install two complete sets of intrusive sensors. With permanent counter equipment, usually the need for a long-term data collection site makes a highway agency willing to perform the tasks necessary to install sensors in the roadway on all lanes of a facility, regardless of roadway geometry. (For exam- ple, the agency will cut slots in the outside lane pavement to protect lead wires leading to sensors that monitor traffic on the inside lanes.) Thus, unlike with short-duration counts, the geometric configuration of a roadway, by itself, is unlikely to cause a state to select non-intrusive sensors over intrusive sensors. On the other hand, because permanent equipment operates year-round, weather and environmental sensitivity become bigger issues. In locations that experience frequent, heavy snowfall and a resulting decline in driver lane discipline, considerable data can be lost if lane-specific axle sensors are selected. In addition, with sensors that operate year-round, states must determine whether the sensors they select will function in the temperatures expected. For example, piezoceramic cable loses sensitivity in very cold weather. Consequently, states that wish to place sensors in a location that will experi- ence temperatures well below freezing must obtain both documented proof and war- ranties from their vendors that the selected equipment will operate correctly at the expected temperatures. S.3.2 Sensor Longevity and Pavement Condition A second situation in which non-intrusive sensors may be preferable to intrusive sen- sors is where the pavement condition is poor enough now, or will be in the near future, to raise doubts about the expected life of intrusive sensors and/or where the pavement condition could affect the accuracy of those sensors. Poor pavement condition can dramatically shorten the life span of intrusive sensors. This is partly because poor pavement conditions increase vehicle dynamics, which in turn increase the impact loads applied to intrusive sensors. But poor pavement condi- tion also commonly leads to premature failure of the pavement/sensor bond, and the
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10 loss of this bond normally results in a non-functional sensor (and often the loss of the sensor itself, because most sensors cannot be reinstalled). Even if the sensor has not failed, pavement failure around the sensor can lead to the generation of "stray" signals within the sensor. One common form of these signals is "ghost axles" generated in piezoelectric cables when neighboring concrete slabs rock because of failure of the joints between slabs. Stray signals frequently result in mis- classification of vehicles, collection of invalid vehicle records, and ultimately the cre- ation of datasets containing so many invalid data that they become unusable. If the pavement condition at a proposed permanent data collection site is poor, there are three major options: repave the roadway section that will hold the sensor before installing that sensor; choose a non-intrusive sensor whose performance is not affected by pavement condition; or select a lower-cost intrusive sensor technology recognizing that the life span of that sensor will be fairly short. The last of these options is often a cost-effective way of collecting a valuable data- set needed for very accurate pavement design, but it requires acknowledgment that the sensor will be lost in a shorter period than most states expect their permanent equip- ment to last. It also means that great care must to be taken to (1) review data from the device placed at this location to ensure that it works accurately when it is originally placed and then (2) identify when sensor accuracy starts to degrade as the pavement condition continues to deteriorate. Therefore, in these conditions, added quality con- trol and data review are needed both when the sensor is first installed and then as the device continues to operate. Pavement condition also changes how a highway agency might view the tradeoffs between sensor cost and performance. Poor pavement condition will significantly change the life-cycle of all intrusive technologies. (For example, in some cases sensors will fail before they reach their expected life because of pavement condition.) When pavement condition is poor or even marginal, paying more for a longer lived sensor makes no sense because the sensor failure will not be a function of the sensor itself. Con- sequently, pavement life should be considered when the life expectancy of a permanent site is computed, and the cost/performance decision should be adjusted accordingly. S.3.3 Vehicle Classes Collected As with short-duration counts, the preferred vehicle classification scheme for per- manent classifiers is axle based, which means that, all things being equal, intrusive, axle sensor-based classifiers are the preferred technology for meeting the pavement design guide requirements for traffic load data. In fact, use of equipment that provides truck vol- umes that follow the same classification scheme as the state's WIM devices results in the most accurate traffic load datasets possible and is recommended whenever practical. However, many of the functions for which permanent classification data are collected (e.g., seasonal adjustment of short-duration counts) require only two or three classes of trucks. Therefore, having permanent classifiers that collect only three or four classes of vehicles is acceptable when axle-based classifiers are not practical or cost-effective. Selecting a classifier technology that does not use the same classification algorithm as the WIM scales selected requires a careful determination of how the classification schemes of these alternative devices correlate. S.4 WEIGH-IN-MOTION EQUIPMENT It is not possible to provide a simple decision process for selecting WIM equipment. In general, each highway agency must determine its own tradeoffs among the cost of
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11 equipment and its installation, the cost of calibration, the expected life span of the WIM sensor, and the expected life span (and structural performance) of the pavement into which the equipment will be placed. These technical considerations must also be exam- ined in light of the compatibility of the data retrieval capabilities offered by specific ven- dors, how well those capabilities integrate with existing data collection software, the warranties and other guaranties of performance offered with the equipment, the perfor- mance history of that equipment and its vendor, and the support services offered by the vendor. Key technology considerations are summarized in Table S.3. An important addi- tional consideration is whether the equipment offered by a vendor has been indepen- dently evaluated and found to meet the ASTM E 1318 WIM performance standards. S.4.1 Technology Choice Versus Location Choice The primary key to the success of any WIM system's use is the location of the axle weighing sensors. Because vehicle dynamics play such a significant role in the force actually applied by any given axle at any given point on the roadway, the selection of the location used to weigh trucks is often more important than the choice of a specific technology to ensure accurate axle weight data. The placement of a scale in rough, uneven pavement will result in poor quality weight data, regardless of the WIM tech- nology selected. Similarly, if the pavement condition at a WIM site deteriorates after a scale has been installed, the performance of that scale can be expected to deteriorate as well, regardless of the technology selected. Some scale sensor technologies rely on the structural strength of the pavement in which they are supported. When these sensors are placed in weak pavement (i.e., pave- ment that flexes), the accuracy of these sensors tends to degrade. Similarly, when the strength of the pavement changes with environmental conditions (usually because of changing moisture content or temperature), sensor performance can be expected to change, and calibration drift frequently occurs. Consequently, where weight data are needed for thinner, flexible pavements subject to changing strength characteristics, selection of a WIM technology that separates the weight sensor from the pavement through the use of some type of frame is a good idea. However, the pavement must be thick enough to hold the frame. Where the pavement cannot support accurate WIM data collection, the highway agency should consider moving the data collection site to a location at which the WIM can function accurately. Finally, as with permanent vehicle classifiers, the highway agency should consider expected pavement life when determining the life expectancy of a WIM site, as well as the implications of that life span for the WIM technology for that site. That is, the agency should not spend a lot of money on a WIM device and installation where the pavement will not support accurate weighing for more than 1 year. Similarly, more expensive, longer lived WIM scales should be considered for placement in high-quality pavement, where these devices can be expected to operate accurately for many years. S.4.2 Portable Versus Permanent Scale Deployment Ideally, as with classifiers, WIM equipment selection would be divided into both per- manent and portable devices, because WIM data are also needed both at geographically diverse locations and over long periods at some locations to measure seasonal and day- of-week changes in vehicle characteristics. Because dynamic vehicle motion dramat- ically affects WIM sensor output, each scale must be calibrated to each of the specific locations where the weighing sensors are placed. Site-specific calibration is the only way
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TABLE S.3 Weigh-in-motion technology comparisons
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13 that the dynamic effects of the pavement leading to the scale sensor can be accounted for in the WIM scale calibration. The need for site-specific calibration means that portable scales must be calibrated each time they are placed on the road surface. This roughly doubles the cost of setting up a portable weighing session because calibration often takes as much staff time as (if not more staff time than) portable sensor placement and pick up. When these calibration costs are accounted for, many highway agencies find that portable WIM becomes cost prohibitive relative to the use of "short-term permanent" WIM (placing WIM sensors permanently in the ground, but only collecting data from the sensors periodically for moderately short periods). S.4.3 Temperature Sensitivity Some WIM systems are sensitive to temperature. Piezoceramic and piezopolymer sensors are both temperature sensitive (i.e., their signal strength for a given axle force changes with temperature). While some vendors have developed compensation algo- rithms to account for temperature sensitivity, these technologies are at a disadvantage when placed in environments that include quickly changing temperatures. Because the strength of asphalt pavements also changes as environmental conditions change, the technologies that rely on direct structural support from the pavement itself will perform less consistently in these pavements than at locations where the pave- ment's strength characteristics will not change (e.g., thicker asphalt and concrete sec- tions). Also more successful will be WIM technologies whose axle sensor support is not affected by changing environmental conditions. S.4.4 Scale Sensor Width, Accuracy, and Installation Effects The larger the size of the scale sensor, the longer a tire is in contact with the sensor and the longer the period during which force is measured. This provides an accuracy advantage to wider sensors in comparison with narrow sensors. (Note, however, that if the scale grows too wide, such as with some bridge WIM installations, multiple vehi- cles will be on the sensor at the same time, thus degrading weighing accuracy.) Very narrow sensors also permit tires to "bridge" the sensor, meaning that at no point is the entire weight of the tire supported solely by the sensor. This decreases the sensitivity of the sensor and makes weighing accuracy more sensitive to environmental changes in pavement strength. A significant advantage of narrow strip sensors is that installation is far easier and takes considerably less time than for wider sensors. As a result, these sensors tend to be less expensive to install. They also tend to be less expensive per sensor than wider sensors. S.4.5 Number and Location of Sensors The most common means of reducing inaccuracy in weighing caused by vehicle dynamics is to weigh an axle at more than one location as it moves along a road. Increas- ing the number of weight sensors used by a WIM device (when those sensors are placed in series) allows a more complete analysis of vehicle dynamics and, consequently, pro- vides a better estimate of each axle's static weight. Thus, in general, the larger the num- ber of sensors placed in series on the roadway, the more accurate the system will be. In addition, having multiple sensors allows the failure of at least one sensor without the loss
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14 of all WIM capability. Unfortunately, each extra scale sensor increases the cost of the WIM system. Therefore, multi-sensor WIM systems tend to use less expensive, narrow strip sensors. Most multi-sensor systems marketed in the United States place two scale sensors in series in the roadway. However, some vendors of wider bending plate sensors achieve a similar weighing-in-series effect by staggering their half-lane sensors (weighing first one side of the truck, and then the other side of the truck), rather than placing them side- by-side. This, too, measures a greater range of the truck's dynamic motion, increasing the scale's ability to account for vehicle dynamics. Several European WIM tests have shown that further advances in WIM system accu- racy can be obtained by using even more sensors. To date, the use of three or more sen- sors in series has not been adopted in the United States for production weighing. S.4.6 Location of the Sensor Relative to the Pavement Surface Field tests to date have shown that the most accurate WIM systems have sensors that are mounted flush with the existing road surface. Sensors that sit on top of the pave- ment create their own bump (even a very small bump is bad) that increases vehicle dynamics, which in turn decrease sensor accuracy. Sensors that are entirely covered by pavement are affected by changes in pavement strength associated with changes in environmental conditions. Changes in pavement profile (such as rut formation) that decrease the smoothness of the transition from the pavement surface to the WIM sen- sor surface cause impact loads and increased vehicle dynamics, both of which con- tribute to loss of WIM system accuracy. S.5 ADDITIONAL GENERAL GUIDANCE While it is important to select technologies that can operate in the conditions in which they are installed, a successful data collection program will also incorporate all of the attributes presented below. Some of these attributes have not been mentioned in the preceding sections but are explained more fully in the other chapters. · Make sure that the equipment selected can collect data that meet the users' requirements. · For permanently placed equipment, match the design life of the equipment to the (remaining) design life of the location (pavement) where it will be installed. · Make sure that the equipment selected can operate accurately at the location where data are required. · Budget the necessary resources to install, calibrate, operate, and maintain the equipment, including site preventive and corrective maintenance. (Under-funded programs often collect poor data because the programs sacrifice quality for quan- tity, thereby collecting "data" that are mostly noise, not information.) · Develop, use, and maintain a quality assurance program. This includes making sure that equipment is properly calibrated when first installed, that data produced by that equipment are regularly checked for quality, and that identification of sus- pect data or equipment performance results in an investigation of the cause and either confirms accurate system performance or results in repairs, replacement, or removal of the malfunctioning equipment. · Select equipment that has passed an independent performance test (such as ASTM E 1318) and for which vendors are willing to supply warranties of performance.
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15 · Make sure that the staff installing the equipment are fully trained in the installation of that equipment and that they understand the factors that affect its performance. · Maintain a preventive and corrective maintenance program to ensure that data col- lection equipment reaches its expected life and that the data provided are accurate. S.6 RESOURCES S.6.1 Paper Reports American Society of Testing Materials, Annual Book of ASTM Standards 2000, Section 4, Construc- tion, Volume 04.03, Designation: E 1318--Standard Specification for Highway Weigh-In-Motion (WIM) Systems with User Requirements and Test Method. Middleton, D., Jasek, D., and Parker, R., "Evaluation of Some Existing Technologies for Vehicle Detection," Project Summary Report 1715-S. Texas Transportation Institute, September 1999. McCall, B., and Vodrazka Jr., W.C., States Successful Practices Weigh-In-Motion Handbook, Cen- ter for Transportation Research and Education (CTRE), Iowa State University, December 15, 1997, http://www.ctre.iastate.edu/research/wim_pdf/index.htm. Skszek, Sherry, State-of-the-Art Report on Non-Traditional Traffic Counting Methods, Final Report #503, Arizona Department of Transportation, October 2001. S.6.2 On-Line Resources (accessible as of June 20, 2003) The Vehicle Detector Clearinghouse at New Mexico State University http://www.nmsu.edu/~traffic/. FHWA's Demonstration Project 121 web site on Weigh-in-Motion Technology http://www.ornl. gov/dp121/ maintained by Oak Ridge National Laboratory. The European Weigh-in-Motion of Axles and Vehicles for Europe (WAVE) project web site, http:// wim.zag.si/wave/. The Minnesota Guidestar Non-Intrusive Traffic Detection Tests http://www.dot.state.mn.us/guidestar/ projects/nitd.html.