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41 CHAPTER 4 A PROCESS FOR SELECTING EQUIPMENT Each of the technologies discussed in Chapters 2 and 3 has quality of the data collected and reduce the overall cost of the strengths and weaknesses for collecting classification and data collection effort. weight data. Under the right conditions, most of the tech- nologies can collect data of the quality needed for estimating traffic loads for the pavement design software. However, 4.1 DATA COLLECTION NEEDS each of these technologies can perform very poorly when The traffic data needs for the pavement design software are placed in environments that are not conducive to the tech- being addressed in detail under other tasks of NCHRP Project nology being used or when used incorrectly. 1-39. These needs require capability to collect the following: As a consequence, the state highway agencies most suc- cessful at data collection own and operate more than one type Short-duration (48-hour) classification counts on roads of vehicle classification and/or WIM equipment. Different and road segments where traffic loads will be needed, types of equipment are used in different operating environ- Long-term classification counts (i.e., data collected for ments. This helps ensure the quality of data that are collected, more than 1 year) at a limited number of locations around but also forces understanding of and accounting for minor dif- the state, and ferences in data supplied by different devices. (For example, WIM data collection at a limited number of locations. some agencies use dual-inductance loops to collect length- based truck classification data on urban freeways but axle These capabilities are consistent with the general agency sensor-based counters to collect classification data on rural counting needs identified in the FHWA's Traffic Monitoring roads. Special studies are needed to correlate these two data Guide as meeting the needs of a wide variety of users. collection schemes. But through the use of detectors placed to The specifics of the required data collection efforts are collect traffic operations data, these simple correlation stud- divided into vehicle classification issues, location issues, and ies provide access to large amounts of important truck count count duration issues. information that could not be collected otherwise.) Selecting technologies (and vendors) requires careful analy- sis of three different types of information: 4.1.1 Classification Issues Data collection needs of users, A good starting point when examining data collection Data handling requirements and capabilities of the high- equipment is the type of classification scheme the equipment way agency, and is capable of providing. Axle-based classifications are pre- Characteristics of available makes or models of equip- ferred for pavement design purposes, but length classification ment (e.g., cost, reliability, and data provided). is acceptable when axle classes cannot be reliably collected. Truck characteristics (overall length, axle spacing, etc.) Within each of these general subject areas are a variety of tend to differ from state to state. Each state highway agency important issues. It is each agency's responsibility to explore should have an algorithm they have tested and certified that these issues and to balance the advantages and disadvantages can correctly convert axle count and spacing information into of each technology when selecting equipment both in general accurate vehicle classification. Can this algorithm be imple- and for specific data collection implementations. mented with the proposed equipment? If not, what flexibility The material presented below briefly describes the issues is offered by the vendor in the classifications supported, and that need to be considered when agencies select equipment for how do those classes correlate with the FHWA's 13 classes vehicle classification and/or truck weight data collection. In or the classification system used by the state highway agency? addition, Chapter 5 presents a series of best practices recom- Finally, if a classification algorithm other than the one tested mendations that describe tasks needed to ensure the collection and approved by the highway agency must be used, the agency of reliable, accurate traffic data. Adoption of these practices, must thoroughly test the new algorithm. Acceptance of the or of variations in these practices, is likely to improve the new data collection equipment should be contingent on the

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42 satisfactory performance of the equipment in that test, and structure reduce the cost of non-intrusive sensor place- the highway agency should use those results to understand ment to the point where they have a cost advantage over how data collected with the new device correlate with the intrusive sensors?) data collected using the agency's WIM scales. Are there site conditions that prevent accurate data col- lection from taking place? (Is the pavement in too bad of a condition for WIM or classification equipment to 4.1.2 Location Issues operate correctly? Does the poor pavement condition warrant the use of non-intrusive data collection tech- Often the classifications collected are not driven by the pref- nologies either because intrusive sensors will not sur- erences of the user, but by the constraints of the location at vive long or because the poor pavement will cause axles which data must be collected. A number of location-specific to jump the intrusive sensors?) constraints can affect the choice of data collection technology. Is the pavement depth deep enough to allow sensor instal- Key location-specific constraints and their effects include the lation? (If not, choose a different location, use a non- following: intrusive sensor, or build a special pavement slab deep enough to hold the sensor.) Is the data collection site urban or rural oriented? (That Are there environmental conditions that restrict the use of is, is congestion likely to be present? Are vehicles often specific technologies? (Do temperatures drop below lev- formed into closely space platoons?) Devices that work els at which some technologies work? Are temperature effectively in uncongested rural areas often do not work variations sufficient to cause calibration errors in some effectively in more congested urban conditions. (Tests sensor technologies? Are there visibility constraints that performed by Minnesota Guidestar in 2001/2002 should limit the accuracy of specific non-intrusive data collec- provide guidance on which non-intrusive devices can tion technologies?) accurately collect data in urban conditions. See Are there environmental conditions that are likely to http://www.dot.state.mn.us/guidestar/projects/nitd.html.) badly impact the duration of data collection? (For exam- Are there traffic signals or other control devices nearby ple, are freeze-thaw conditions likely to reduce the that may affect vehicle speeds and/or spacings? (Classi- expected sensor life?) fication and WIM equipment should not be located near signals because vehicles frequently accelerate and decel- In some cases, shortcomings of the site should warrant erate near intersections, causing problems in the perfor- selection of another data collection location. For example, mance of most classification and weight data collection poor pavement condition affects the performance of all WIM devices.) sensors. Rather than accepting poor WIM performance (and At what speeds are vehicles traveling? (Some devices do perhaps choosing an inexpensive, inaccurate sensor because not operate at very low traveling speeds, while others are "bad data will be collected no matter what sensor is chosen"), not effective at very high traveling speeds.) consideration should be given to either (1) moving the data On how many lanes do data need to be collected, and collection site upstream or downstream to a site more con- what is the layout of those lanes? (Some devices can only ducive to WIM data collection but with essentially the same collect data in one lane, and that lane must be on the out- traffic stream as at the original site or (2) improving the pave- side of the roadway, next to a shoulder or median.) ment condition prior to the installation of data collection sen- Can detectors be placed safely in (or above) the travel sors. The goal is to meet two criteria: (1) that the traffic data lanes? Is formal traffic control needed for this purpose? being collected correlate very closely with the traffic at the (Inability to place sensors in the lanes of travel would site for which the data are being collected and (2) that the indicate the use of non-intrusive detectors, and inability new site has conditions that allow the equipment to perform to work above the lanes of travel would further restrict the accurately. technology choice to one that can function from beside the roadway.) Are there specific site constraints that need to be 4.1.3 Count Duration Issues accounted for in the selection of equipment? (Will the road's channelization be changing in the near future, so The intended duration of a count has a considerable impact that permanent intrusive sensors are not cost-effective on the type of data collection technology selected. The longer and non-intrusive sensors should be selected?) the desired count duration, the more likely a permanently Are there other features to the site that constrain or mounted sensor is needed. enhance the use of certain data collection technologies? For long-duration data collection sites, it is also impor- (What is the availability of power or communications, tant to determine the expected life span of the site itself. For and does that availability indicate the need to select a low- example, because vehicle weight data are scarce on most power consumption data collection technology? Does the roads in most states, it seems prudent to collect no more than presence of an existing sign, bridge, or other overhead 2 years' worth of weight data at a specific site and then move