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17 CHAPTER 2 TYPES OF EQUIPMENT This chapter presents an introductory summary of the types of equipment that are available for collecting classification counts and for weighing vehicles in motion. For this purpose, the authors categorize equipment by the type of data collected: ⢠Short-duration portable vehicle classification counts; ⢠Continuous (long-duration) vehicle classification counts; ⢠Short-duration, weigh-in-motion (WIM) data; and ⢠Continuous (long-duration) WIM data. In addition, the classification technologies are further dif- ferentiated by whether the sensors are placed in or on the road- way surface (intrusive sensors) or whether they are placed above or beside the roadway (non-intrusive). Vehicle classifi- cation can be performed using either intrusive or non-intrusive sensors, although the style of sensor used affects the data available for classifying vehicles and thus the definition of vehicle categories into which vehicle counts are placed. On the other hand, current WIM technologies all require on-surface or in-pavement sensors. 2.1 VEHICLE CLASSIFICATION Vehicles can be classified using any one of several cate- gorization schemes, and alternative schemes often use dif- ferent characteristics to differentiate between vehicles. The most common classification schemes are based on ⢠Number and spacing of axles, ⢠Total vehicle length, ⢠Body or trailer type, ⢠Vehicle weight, or ⢠Engine/fuel type. Most technologies can collect some but not all of these dif- ferent characteristics. Thus, if a specific classification scheme is required, it is important to select a data collection tech- nology that can collect the vehicle characteristics that define that scheme. Similarly, if a specific technology must be used because of some other constraint (such as environmental factors or pavement condition), it is important to understand the restrictions that the use of that technology places on the classification scheme. For example, use of two conventional inductive loops in series (dual loops) allows for classification based on overall vehicle length, but does not allow for classi- fication using the FHWAâs 13-category, axle-based scheme. 2.1.1 Short-Duration Classification Counts Short-duration counts are the most common of all classi- fication counts. Prior to the mid-1980s, classification counts were almost always collected manually by roadside observers. Visual observation allows a wide variety of classification schemes, including those based on body type and those based on vehicle configuration and number of axles. However, because manual observation is expensive, highway agencies have transitioned to automated data collection. Since the mid- 1980s, most classification data have been collected using portable sensors placed on top of the roadway surface. This choice of technology means that most classification counts now use axle- or length-based classification schemes. How- ever, further advancements in technology, as well as limita- tions in the more traditional data collection technologies, have encouraged highway agencies and vendors to experi- ment with portable versions of non-intrusive sensors. Short-duration classification counts are collected at a wide variety of locations. In addition to collecting accurate data, the technology used for short-duration counts must be easily moved from location to location, be easy and safe to place, have portable power supplies that can keep the equipment operating for the periods desired, and be relatively inexpensive. Short-duration counts are most commonly collected for peri- ods of 24 or 48 hours, although some highway agencies attempt to collect as many as seven consecutive days of such data. Portable sensors that are commonly used for collecting vehicle classification data include ⢠Road tubes, ⢠Piezoelectric sensors, ⢠Fiber-optic cable, ⢠Portable inductance loops, and ⢠Magnetometers. The first three of these types of sensor provide information sufficient for use when classifying vehicles into the FHWAâs 13-category system, but inductance loops and magnetometers
do not. The primary advantages of these three technologies are that they are relatively inexpensive to purchase, are easy and inexpensive to place, and are capable of providing the information required for most uses. The technologiesâ biggest drawback is that they are generally designed to operate in low- and moderate-volume rural settings. In congested conditions, where vehicles are accelerating or decelerating while crossing the sensors, or where vehicles are tailgating each other, these sensors often have accuracy problems caused by an inability to measure axle spacings correctly or to distinguish between closely spaced vehicles. (For example, in congested condi- tions, two closely spaced cars are often reported incorrectly as a single, four-axle, combination truck.) In addition, on higher- volume roadways, even the most quickly installed sensors require the presence of full traffic control in order to protect the staff placing the sensors. The need for traffic control sig- nificantly increases the cost of portable data collection and can entirely prevent short-duration classification data collec- tion where staff are not able to safely place sensors. Research is currently being performed on the development of non-intrusive sensors specifically designed for collecting truck volume information on high-volume urban roadways. The Minnesota Department of Transportation has recently begun testing these devices. In order to increase staff safety, eliminate the need for traf- fic control for each count, and allow data collection on high- volume roadways, some highway agencies place sensors per- manently in the ground at high-volume locations, but only collect data at these locations periodically. In these cases, the data collection electronics usually âroveâ from sensor location to sensor location. This allows short-duration counts to be made quickly and inexpensively by simply connecting the rov- ing electronics to existing permanently mounted sensors. This option reduces the cost and danger of placing sensors when- ever counts are required, but it entails a high capital cost for initial purchase and installation of a large number of sensors. 2.1.2 Continuous Classification Counts Equipment that works well for short-duration classifica- tion counting often is a poor choice for continuous data col- lection over longer periods of time. Technologies that use sensors mounted on the surface of a roadway usually are not able to operate for extended periods of time without having the sensors reinstalled because the traffic has loosened them from their original placements. Continuous counts require a long-lived sensor installation. In addition, continuous count devices require power and communications capabilities that are far different from portable devices. Portable counts nor- mally are collected using battery power, with the counts down- loaded manually from the data collection electronics to a lap- top computer or data transfer device. Long-duration counts, however, require electrical power, usually from electric power service or from solar cells, as well as telephone communica- tions for downloading data. 18 As a consequence, data collection efforts at permanently placed, continuous count locations tend to be far more capi- tal intensive than are those of short-duration counts. Contin- uous counts usually use sensors that require traffic control or heavy equipment (such as a bucket truck and a trenching machine) for placement and are made by counting devices that are stored in installed, locked cabinets rather than chained to nearby utility poles. However, once these devices are placed, they are designed to operate with relatively little staff intervention except for periodic maintenance. The most common data collection technologies for con- tinuous classification data collection are in-pavement sensors based on dual-inductance loops or piezoelectric (ceramic) cables. Limitations in these two technologies, and the recog- nition that more classification data are needed, have led to a significant increase in the number of technologies available for conducting continuous vehicle classification counts. In particular, considerable advances have been made in the devel- opment of non-intrusive technologies, which use sensors that are not physically placed in the roadway itself but which mon- itor traffic from above or beside the road. Non-intrusive sen- sors have the advantage of allowing sensor placement with no lane closure (for roadside sensors) or with a less disruptive closure (for overhead-mounted sensors). They also have the advantage of not being subject to the impact of traffic loads or to the stresses that result from pavement interaction with the environment. However, non-intrusive sensors have limitations. The fore- most limitation is that it is more difficult to detect and count the axles on passing vehicles with non-intrusive sensors than with intrusive sensors such as the piezo cable. Because axle counts by type of axle are generally required for accurately estimating pavement loads, data collected with non-intrusive sensors usually require at least one extra data manipulation step (based on assumptions) when used for pavement load determination. This step involves converting the vehicle classes collected with the non-intrusive technologies into a vehicle classification scheme compatible with the vehicle classes that are collected using available WIM technologies. Finally, even the newest technologies have difficulty cor- rectly classifying vehicles in stop-and-go traffic and when vehicle separation is small. These conditions make it extremely difficult to separate tailgating cars from multi-unit trucks and make it very difficult to measure vehicle length and axle spac- ing correctly. These limitations are a primary reason why most states have only modest amounts of classification data for urban roadways. 2.2 WIM DATA 2.2.1 Short-Duration WIM Two technologies, capacitance mats and BL-style piezo- electric sensors, are commonly used in the United States for high-speed (i.e., on-highway) portable WIM data collection.
Both technologies involve mounting a sensor on top of exist- ing pavement. This action requires a temporary lane closure and often work by more than one person. While the basic technique of placing sensors on top of the roadway is essential for collecting WIM data in a truly portable mode (i.e., at any site that meets the physical requirements for acceptable sensor operation), there is a system performance problem that limits the accuracy of high-speed portable WIM scales. Because the sensor is physically on top of the roadway sur- face, a bump is created as the tire of each axle mounts the weight sensor. This bump causes two physical effects, each of which is detrimental to WIM system accuracy. The first effect is the additional dynamic motion imparted on the vehi- cle being weighed. This motion makes it much harder for the WIM system to accurately estimate the static weight applied by each axle. The second physical effect is that the need to climb over this bump causes the tire itself to flex, absorbing some of the horizontal force from impact with the bump. This tire flex force is transmitted to the weight sensor, causing addi- tional bias and noise in the measurement process. The result of these physical phenomena is that portable WIM rarely achieves the same level of accuracy as a correctly placed permanent scale. This does not mean that weights col- lected using portable scales are not useful in the traffic load estimation process, but it does mean that highway agencies must be particularly careful to calibrate portable scales each time they are placed on the roadway and to monitor the data produced after scales have been calibrated to ensure that the system is producing reliable results. The need to calibrate every time portable sensors are placed also reduces the difference in the total costs associated with data collection using permanently mounted sensors and using portable sensors. Without calibration, data collected by por- table scales will be significantly less accurate than data pro- duced by permanent scales. Because of the limitations in truly portable WIM systems, some state highway agencies use one of two methods for col- lecting short-duration WIM data. One method involves the use of low-speed (off-highway) WIM scales or portable static scales. The other method relies on permanently mounted weight sensors and portable data collection electronics. In the first method, conventional, portable static scales (loadometers) or low-speed portable WIM scales (usually bending plates or capacitance pads) are used for portable weight data collection. These traditional technologies require flat areas (such as a parking area of a rest stop) where the scales can be laid out and trucks diverted over the scales. Trucks are either stopped on these scales or driven at slow speeds over the scales. These data collection techniques tend to be labor intensive (because trucks must be directed over the scales), and they result in fairly small datasets in com- parison with high-speed WIM data collection. Also, they dis- rupt the truck traffic stream (which must be diverted off the roadway and over the scales), and drivers are likely to assume 19 they are being used for weight enforcement. Hence, these col- lection locations may be avoided by illegally overloaded trucks, resulting in biased results. However, these technologies are acceptable for truck weight data collection where truck volumes are light, where only a small sample is required, and where truck evasion is difficult because of limited opportu- nity for trucks to by-pass the scale site. The second method uses portable electronics with perma- nently mounted WIM sensors that allow weight sensors to be flush mounted with the roadway. This eliminates the bump that occurs with surface-mounted sensors and results in a bet- ter environment for collecting accurate axle weights, but it does not ensure accurate WIM data. Even in this type of por- table operation, calibration is required prior to starting data collection, and care should be taken to ensure that pavement deterioration over time has not created bumps at the joint between sensors and roadways. This type of site is less costly to operate than a continuously operated WIM site (because one set of data collection electronics is used for several data collection sites and because permanent power and commu- nications are not needed and therefore do not need to be con- structed). However, the initial capital cost is higher than for truly portable WIMâa factor that the highway agency con- siders when deciding where to collect WIM data. 2.2.2 Continuous WIM Because of the physics problem noted above for portable equipment, the majority of research and development in WIM has been done for permanently installed weight sensors. Five technologies are currently in common use throughout the United States. Other sensor designs are under active develop- ment. The most common permanently mounted weight sen- sors are ⢠Bending plates, ⢠Hydraulic load cells, ⢠Piezoceramic cables, ⢠Piezopolymer cables, and ⢠Piezoquartz sensors. Other sensor technologies that are either in more limited use or are still under development include ⢠Permanently mounted capacitance mats, ⢠Permanently mounted capacitance strips, ⢠Fiber-optic cables, ⢠Subsurface strain-gauge frame, and ⢠Bridge or culvert WIM. All of the systems are designed to have sensors perma- nently installed in or under the roadway. This results in less dynamic vehicle motion and less impact force on sensors than for surface-mounted sensors, which in turn results in more accurate weighing conditions and longer sensor life.
The various sensor technologies were developed either to take advantage of particular material properties (to reduce the cost of the sensor and/or installation) or to provide a spe- cific advantage to the signal-processing algorithm that con- verts sensor output into an estimate of axle weight. Each sen- sor technology has its own strengths and weaknesses. No one sensor is best for every WIM application. For example, both the piezoelectric cable and fiber-optic cable sensors are specifically designed to require a relatively small pavement cut for sensor installation. This results in a fast and relatively low-cost sensor installation. However, these sensors are so small that at no time during the weighing process is the entire tire (axle) that is being weighed isolated on the sensor. Thus, both of these technologies suffer from signal noise because of the fact that, during the weighing process, the axle weight is partially supported by the pave- ment that surrounds the sensor. Each vendor takes into account the selected sensorâs strengths and weaknesses when designing a WIM system. The means for accounting for specific weaknesses has a great deal to do with how well specific sensors work in given installa- tions. Because vendors often take different approaches to sensor installation design and signal processing, the perfor- mance of a specific sensor technology can vary widely from vendor to vendor. In some cases, the conditions at a specific WIM site directly (and negatively) coincide with the partic- ular weakness of a given sensor technology. In these cases, even the best vendor responses to handling those weaknesses may not allow sensors to work correctly. A good example is temperature sensitivity. Temperature- sensitive WIM sensors are not good choices for WIM sites where temperatures change rapidly. Although such sensors are used with temperature compensation algorithms, often based on some type of autocalibration technique, these adjustments cannot be made fast enough to maintain scale accuracy in 20 areas with rapid temperature changes, such as those experi- enced in mountain passes and in the Southwestern deserts. Environmental and site conditions (pavement condition, temperature, wind, grades, etc.) play a large role in the per- formance of any WIM system, regardless of sensor technol- ogy. A high-speed WIM system will not work accurately if the site selected for weighing is not conducive to weight data collection. ASTM specification E 13181 provides specific guidance on the pavement conditions needed for accurate WIM system performance. This guidance stipulates a pave- ment that is ⢠Flat (no horizontal or vertical curves), ⢠Smooth (no bumps or other surface conditions that cre- ate vehicle dynamics), ⢠Strong (to reduce pavement flex underneath the WIM sensor), and ⢠In good condition. WIM sites should also be sites where vehicles are travel- ing at fairly constant speeds (i.e., not accelerating or decel- erating), are not changing lanes frequently, and have good lane discipline. If these conditions are met, then the trucks being weighed are likely to have relatively modest dynamic motion. They will tend to track correctly in their lanes (and will hit the weight sensors as expected), and the speeds mea- sured and used in various signal-processing algorithms will be accurate. All of these factors improve the performance of any WIM system, regardless of sensor technology. 1 American Society of Testing Materials, Annual Book of ASTM Standards 2000, Sec- tion 4, Construction, Volume 04.03, Designation: E 1318âStandard Specification for Highway Weigh-In-Motion (WIM) Systems with User Requirements and Test Method, ASTM, 100 Barr Harbor Drive, West Conshohocken, Pennsylvania, 19428-2959.
