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3.0 TRUCK-WEIGHT ENFORCEMENT MEASURES of EFFECTIVENESS (M.O.E.s) In response to the need for adequate truck-weight enforcement evaluation proce- dures, NCHRP Project 20-34 developed and validated applicable measures of effective- ness (M.O.E.s). The project effort also developed techniques to apply the M.O.E.s in a systematic sampling plan and to analyze the collected data. A discussion of the M.O.E. development process is contained in Appendix B. The field validation procedure is detailed in Appendix C. Results of these efforts are summarized in the following two report sections. 3.1 M.O.E. Development The first step in the M.O.E. development process was to consider an operational definition of truck weight enforcement M.O.E.s. Following this step, the project team developed a set of objective criteria against which to evaluate candidate M.O.E.s. The applied criteria were derived from M.O.E functional requirements. Candidate M.O.E.s were ranked according to their suitability to meet the designated performance criteria. It is necessary to understand the definition of truck-weight enforcement M.O.E. A Measure of Effectiveness (M.O.E.) of weight enforcement activity is defined as a Determinable quantity of what is achieved as the result of truck weight enforcement ac- tivity". Its application should also be used to quantify Me contribution that a particular activity makes toward achievement of one or more of the goals defined in Section 2.3. In order to quantify effectiveness there must be measures which show benefits in terms of: (~) compliance with operational weight and axIe-spacing regulations, (2) pave- ment/bridge preservation, or (3) minimizing accidents, deaths, injuries, and property damage. Initial truck-weight enforcement M.O.E. concepts were developed on the basis of art assessment of truck weight enforcement objectives (including results of a SO-state s

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agency survey) and the anticipated sensitivity of resulting candidate measures to those objectives. A set of candidate M.O.E.s for field validation was derived from a systematic application of the following functional criteria: I. Practicality of M.O.E. application, e.g., amenable to state agency data collection capa- bility, cost requirements, and ease of measurement. 2. Reliability of candidate MO.E, i.e., correctly represents a Sue distribution of weights, classification, percentage of overweight trucks, percent of bndge fonnula non-compli- ance, etc. 3. Support random sampling, i.e., designed to achieve representative sampling over desig- nated study region. 4. Absence of bias with regard to enforcement/monitoring procedure, i.e., generally sensi- tive to prevailing truck characteristics regardless of enforcement activity. 5. MO.E. compatibility with agency data collection methods, i.e., achieved in terms of measures that can be readily denved from existing or overwise readily obtainable data- collection apparatus. 6. Sensitivity to infrastructure damage, e.g., considers that excessive axle-weight as op- posed to excessive tandem-weight are more likely to result in pavement damage. 7. Applicability to future technology, i.e., data requirements are consistent with capabilities of emerging technologies. Candidate measures were evaluated and ranked by an expert panel. The final set of designated candidate M.O.E.s for field validation, along troth their definitions, is pre- sented in Table I. 3.2 M.O.E. Fielc! Validation A field validation study was conducted to confirm the sensitivity of candidate M.O.E.s to actual truck weight enforcement activity. Candidate M.O.E.s were tested in a four-state evaluation effort that applied matched sets of weigh-in-motion (WIM) data, collected under controlled baseline and enforcement conditions. Overall findings of the field validation effort confirmed the suitability of M.O.E.s listed in Table I. State-specific findings are summarized as follows.

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Table I. Designated Measures of Effectiveness (M.O.E.s) and their Definitions Hi - Eiifo~eiii,ent~"O~|.~., ~ ~ ~ ,, ~I) - i~.'=~...:~.~.~,.,:~,:~^,~.:..,: The fraction (or percentage) of the total Gross Weight Violation, Proportion observed truck sample which exceeds the legal gross weight limit. The extent to which average measured Gross Weight Violation, Severity gross weights for the observed sub-sample of gross weight violators exceeds the legal gross weight limit. The fraction (or percentage) of the total Single-axIe Weight Violation, Proportion observed truck sample with one or more axles which exceeds the legal single-axle weight limit. The extent to which average measured sin Single-axle Weight Violation, Severity ale-axle weights for the observed sub sample of single-axle weight violators ex ceeds the applicable legal limit. The fraction (or percentage) of the total Tandem-axle Weight Violation, Proportion observed truck sample with one or more tandems which exceeds the legal tandem axle weight limit. The extent to which average measured tan Tandem-axleWeightViolation, Severity dem-axle weights for the observed sub sample of tandem-axle weight violators exceeds the applicable legal limit. The Faction (or percentage) of the total Bndge Formula Violation, Proportion observed truck sample which exceeds the legal Bridge Formula weight. The extent to which average measured Bridge Formula Violation, Severity Bridge Formula weights for the observed sub-sample of Bridge Formula violators exceeds Be legal weight. The fraction (or percentage) of the total Excess ESALis, Proportion | observed truck sample exhibiting Excess ESALs; i.e., ESALs attributable to the ille gal portion the individual single or tandem axle group. The average value of Excess ESALs ob Excess ESALs, Severity served for the truck sub-sample exhibiting Excess ESALs. ' Equivalent Single Axle Load is defined in the Glossary (Appendix H) of this report. 7

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California The California Department of Transportation provided output from a WIM scale located on I-5. An analysis of 3,678 truck combinations exhibited lower gross weights path a smaller proportion of overweight axles during the tune when the weigh station was open. Data on a sub-sample of 2,370 tractor-semi-trailer combinations was further analyzed to examine M.O.E. sensitivity to the enforcement activity. The results confirmed the validity of the following M.O.E.s: Tandem-axIe Weight Violation Severity, Bridge For~nula Violation Proportion, and Excess ESAL Seventy. Georgia Mobile truck-weight enforcement operations, utilizing an obtrusive portable roadside weigh scale, were conducted at a rum interstate location. An analysis of WIM data gathered on 483 combination trucks revealed a number of M.O.E. validation effects associated with observed axle and tandem weights. Under conditions of visible (and unexpected) mobile enforcement operations, Me observed truck sample exhibited tower steering-axIe weights, lower rear-axIe weights, and lower rear-tandem weights. Dunng the surprise enforcement operation, a number of overweight trucks were observed to either park alongside the roadway or divert to alternate routes. The results validated the following M.O.E.s: Single-axIe Weight Violation Proportion, Tandem-axie Weight Violation, and Excess ESAI~ Seventy. Idaho A large volume of WIM data, i.e., gathered on approximately 29,000 commercial vehicles, was provided by Me Idaho Trarsportation Department. A comparison of baseline versus enforcement conditions during Tree different weekdays produced a number of sig- nificar~t findings. While no day-of-week effects were readily evident to indicate on which days enforcement effort would more likely be effective, all of Me tested operational meas- ures were shown to be sensitive to enforcement activity. M.O.E.s most consistently demon- strating sensitivity to enforcement activity were: (1) Gross Weight Violation Proportion, (2) Single-axIe Weight Proportion, (3) Tandem-axIe Weight Proportion, and (4) Excess ESAL Proportion. While less frequently associated with enforcement activity, the electiveness of following measures were also validated in the Idaho data: (1) Gross Weight Violation Severity, (2) Single-axle Weight Violation Severity, (3) Tandem-axle Weight Violation Seventy, and (4) Excess ESAL Severity. 8

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Minnesota Data sets representing two weeks of continuous traffic monitoring were provided by the Minnesota Department of Transportation. Bending-plate WIM data were gathered approximately five miles from a permanent truck-weight enforcement scale during times when the scale was both open and closed. While generally weak M.O.E. validation findings were seen in Minnesota results, one data set did exhibit a smaller proportion of gross weight and tandem axle violations along with a tendency for less severe excess ESALs. The other set produced a tendency to lower Bndge Formula violations. The results validated the following M.O.E.s: (~) Gross Weight Violation Proportion, and (2) Tandem- axIe Violation Proportion. Summary All of the tested M.O.E.s. were shown to be sensitive to actual truck weight enforcement activities. A number of factors were seen to affect M.O.E. sensitivity to enforcement procedures, including actual truck weight/configuration charactenstics, shipping commodity demands, observed truck sample size, and WIM equipment vanables. Those measures most strongly supported by the field data (in descending order) are as follows: (~) Excess ESALs, Severity, (2) Tie - Gross Weight Violation, Severity, and Excess ESALs, Proportion; and (3) Tie - Gross Weight Violation, Proportion, Single-axIe Weight Violation, Proportion; and Tandem-axle Weight, Severity. 9