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APPENDIX A LITERATURE REVIEW State truck weight enforcement agencies generally measure their accomplishments in teens of actual enforcement activity, i.e., the number of trucks weighed, legalizations, etc. However, these measures can not address actual weight violation activity, i.e. number and severity of actual on-road overweight truck traffic. As a result, truck weight enforcement agencies currently have no way of gauging the real problem of overweight truck activity. The objective of this literature search is to examine documented studies addressing relevant issues related to truck weighing effectiveness, i.e., potential in situ truck weight data sources and appropriate data-gathering technologies, required to establish a program for monitoring truck weight enforcement impacts. BACKGROUND Genera/ Truck Weigh! Enforcement Effectiveness Ding He late seventies, the U.S. Government Accounting Office sent a questionnaire (~) to all states asking for information on truck weight laws, enforcement programs and methods, and background data on their State Highway System. The final report, summarizing the states' responses, referred to enforcement program effectiveness only in terms of numbers of trucks weighed and citations issued. A 1981 NCHRP Synthesis (2) addressed criteria for evaluating truck weight enforcement programs. Various findings are cited as follows: i. One purpose of truck weighing programs is to enforce legal load limits and to prevent trucks from damaging highways and bridges. Although all states have truck weight enforcement 1 Appendix A
programs, none has established criteria for evaluating these programs. However, each state periodically reviews operations, evaluates and purchases equipment, requests revisions to laws, and adjusts its organization in an effort to improve enforcement. 2. Comparing truck population with the number of vehicles being weighed is part of determining the effectiveness of a truck weighing program. Also needed are data on the overloaded truck routes arid volumes, types of movements (interstate or intrastate), vehicle classifications, types of cargo, and distances traveled. Essential to truck weight enforcement is the effective combination and deployment of the various types of scales (permanent, portable, and semiportable). Through the use of data collected in truck traffic studies, permanent scales cart be located where there are many overloaded trucks, and these scales can be supported by roving portable-scale crews. Greater use of the sem~portable scales should be carefully considered arid may eliminate the need for a new permanent weigh station. Improved instrumentation for weigh stations and semiportable stations is needed. 4. In most states, overweight violations are misdemeanors arid are processed through the courts. In several states, an overweight violation is a civil offense, and penalties are collected at the weigh site or within 1 5 days after the citation is issued unless a hearing is requested. Most states have unloading requirements for an overload violation. Many enforcement officers believe that the off-loading requirement is the most effective deterrent in a truck weight enforcement program. Some of the problems In truck weight enforcement can be attributed to insufficient personnel, usually the result of an insufficient number of budgeted positions for proper operation of permanent and portable scales. The hours of operation of scales are related to the available personnel. Most permanent stations are operated continuously only on routes with large volumes of Duck traffic. 6. Each state needs to evaluate its truck weight enforcement program, beginning with cooperation within and among the agencies involved. The state needs to determine the most effective enforcement procedures possible under the law in light of the existing facilities and Appendix A 2
available personnel and with minimal expenditures for additional facilities and equipment. Long-range goals for changing state laws and improving site operations also are necessary, as are methods for measuring the effectiveness of state truck weight enforcement programs. Some of the possible methods are simple and can be implemented with little more than an evaluation of existing data. Other methods require a different use of existing equipment, additional equipment, or a change in operations. A deterrent to truck weight enforcement effectiveness is that overweighing can prove to be economically. beneficial for truckers. Paxson (3) demonstrated benefits to truckers of overweighing by means of an incremental approach (decrease in transport cost per unit with increase in cargo weight) and by using specific cargo movements to calculate the incentives to overweight. The fine and penalty structures of various states were examined and were combined with the probability of being weighed to calculate the expected value of being weighed to the trucker. The net benefit of overweighing to the trucker was then shown by comparing the costs with the incentives. Finally, actual permit costs were examined in relation to the cost of additional pavement damage caused by overweight trucks. Paxson concluded that (a) economic incentives often exceed the expected costs of overweighing to the trucker, (b) current enforcement programs in some states are not effective, (c) fine structures should take account of both the amount of truck overweight and the number of miles traveled, and (d) the cost of overweight permits does not reflect the additional pavement damage caused by overweighing. A Canadian study published by TRB (4) also addressed the economic disincentive of weight enforcement activity. The object of this research was to assess the effectiveness of a truck weight enforcement program. Truck weight regulations and trucking activity in the Province of New Brunswick, Canada, were used as a case study. The methodology compared incremental revenues that can be earned by overloading a particular truck configuration with the expected cost of getting caught, taking into account the fine regime and the level of enforcement. The results of the research demonstrated that fines are not structured in New Brunswick to be an effective deterrent for would- be violators. Alternative enforcement programs were postulated and the deterrent effect was evaluated. One strategy to improve the effectiveness of truck weight enforcement effectiveness was suggested in the Wisconsin study by Stein (5). This study recommended that weigh-in-motion data Appendix A 3
be utilized as a tool for prioritizing weight enforcement efforts. The suggested prioritization indicated patrolling Interstates first, followed by U.S. numbered highways, then state trunk and town roads. Current Weigh-/n-Mofion Programs Our survey of state enforcement agencies indicated that -- states conduct weigh-in-motion efforts. Most states collect truck classification and weight data in conformance with the Traffic Monitonng Guide (6). Two example programs documented in the literature are Florida and Wisconsin. Hazen (7) reported that Florida has 20 years of experience In running continuous weighing- in-motion stations. Florida currently has 1 3 continuous WIM stations in operation which provides a "wealth" of data. Research investigated optimum number of WIM sites required to address pavement management systems requirements. WIM data was examined for also seasonal patterns or other patterns for allocating a continuous WIM station to a pattern group. Florida found little or no seasonal patterns. There was some indication of patterns by geographic area of the State. Daily ESAL values are more variable than onginally thought. The Flonda study recommended one week of data collection at stable sites, two-one weeks at moderately stable sites at semiannual intervals, and four-one weeks at unstable sites spread over the quarters of a year. Beginning In 1983, We Wisconsin Department of Transportation collected truck weight data utilizing Bridge Weigh-In-Motion equipment at 21 sites distributed among 7 highway functional classifications. A study by Stein (5) focused on data gathered between 1983 and 1986 on the Rural Interstate and Rural Principal Arterial highway systems for the 5 Axle Combination Truck with Trailer, the common eighteen wheeler and test data collected at Rural Interstate and Rural Principal Artenal sites in 1987. 4 Appendix A
General findings and recommendations of the Wisconsin study were as follows. 1. Composite data from all highway systems indicate approximately 14% of the 5 Axle Combination Trucks with Trailer were operating with at least 1 possible weight violation and over 6% had gross weight violations. On the Rural Interstate, 15% had possible weight violations with individual stations ranging from 2% to 30%. On the Rural Principal Arterial system, 17.6% had possible violations with the individual stations ranging from 16% to 20%. 2. Forty percent of the ESALs observed on the Rural Interstate are attributable to excess axle loadings. The range of observations at individual stations was ~ 7% to 55% excess ESALs. On the Rural Principal Arterial, 29% were excess with a range of 17% to 38%. The test data indicated that ~ 0% of the trucks had a possible violation while the basic data indicated ~ 5% were possible violators on the Rural Interstate. These figures tend to confirm the validity of the basic data with respect to the extent of possible violators. 4. Confirmation of the magnitude of excess ESALs is less conclusive. However, the excess ESAL comparison In Illustration ~ 0 of 29% for We basic data and 14% In the test data tends to be supportive of the legitimacy of the basic data. 5. The basic data exaggerate the magnitude of We severity of violations (ESALs) while not significantly impacting on the data with respect to the number of probable violators. 6. Future analysis of buck weight data for highway systems within Wisconsin comparing data collected utilizing one weighing system and one calibration method will remove considerable ambiguity from the results and better establish the magnitude of the severity of the overloaded truck. In the interim, the basic data should be utilized for highway design and enforcement planning. s Appendix A
Specific finding of the Wisconsin study having implications for pavement design are as follows: An examination of data collected utilizing Bridge Weigh-In-Motion equipment illustrated Mat ESAL load factors based on data collected at enforcement scales were significantly underestimated. Load factors should be based on flexible pavement with a Structural Number of 5 and terminal serviceability of 2.5 and rigid pavement with a thickness of 9-inches and a terminal serviceability of 2.5. 3. Load factors should be maintained using current ESAL values attained utilizing weigh-in motion systems. Beneft/Need for Truck Weighing Programs Truck weight enforcement programs are both necessary and beneficial. Specific discussed aspects of this issue are the current truck overweight problem, economic impact of truck weight, pavement damage, and safety effects of increased weight. Current Truck Overweigh! Problem The most definitive study of the overweight problem was conducted in Wisconsin (5). Its findings are as follows: 1 . Scope of overweight truck population. Composite data Tom all highway systems indicate approximately 14% of the 5 Axle Combination Trucks win Trailer were operating with at least ~ possible weight violation and over 6% had gross weight violations. On the Rural Interstate, 15% had possible weight violations with individual stations ranging from 2% to 30%. On the Rural Principal Arterial system 17.6% had possible violations with the individual stations ranging Dom 16% to 20%. 2. Magnitude of excess ESALs. Forty percent of the ESALs observed on the Rural Interstate are attributable to excess axle loadings. The range of observations at 6 Appendix A
~ndividu~ stations was 1 7% to 55°/O excess ESALs. On the Rural Pnncipal Artenal, 29% were excess with a range of 17% to 38%. Economic impact of truck weight A New Jersey study (8) to estimate the total overweight truck population suggested that total pavement damage attributable to all overweight trucks may approach $20 million dollars per year. It was therefore concluded that a substantial increase in the revenue generated by overweight trucks may be appropriate. Pavement-related costs that might be affected by changes in truck weights include costs for (a) new and reconstructed pavements; (b) resurfacing and other forms of pavement rehabilitation; (c) routine maintenance, such as cleaning and filling cracks and patching potholes; and (d) effects of users caused by changes in pavement condition. For existing pavements, increases in traffic loadings would affect pavement rehabilitation costs in two ways. First, an increase in traffic loadings would shorten the time interval to the next resurfacing. Moving resurfacing expenditures nearer to the present would increase the real cost for resurfacing because of the time value of money (incurring a $1,000 cost today is worse than incurring a $1 ,000 cost one year from today, because in the latter case, the money could be invested productively for a year). If the funds required to resurface highways sooner were not available to highway agencies, the condition of the road when resurfacing is carried out (referred to as the "terminal serviceability") would be reduced and, as discussed below, highway users would be subjected to added cost and discomfort. Second, at the time resurfacing is required, higher traffic loadings would either increase overlay thicknesses or require more frequent resurfacing in the future. A cost-analysis methodology applied in TRB Special Report 225 (9) to estimate Me Impacts of altetnadve Duck weight regulatory scenarios has implications for the development of Muck weight enforcement M.O.E.s. This methodology consisted of three steps: I. The added costs to highway agencies for new and reconstructed pavements and for pavement rehabilitation were estimated assuming a 10 percent increase in traffic loadings (as measured in ESAL-miles) on the nation's highways. Separate estimates were developed for flexible and rigid pavements and for each of the seven regions 7 Appendix A
and four highway classes (Rural Interstate, Rural Non-Interstate, Urban Interstate, and Urban Non-Interstate) used in the productivity analysis. 2. For each truck weight regulatory scenario, the committee used the forecast of ~ 995 truck miles by region, highway system, truck type, and operating weight that was de veloped as part of the productivity analysis to calculate the percentage change (relative to the base case) in ESAL-miles by region, highway system, and pavement type. 3. The percentage changes calculated in Step 2 were used to scale the estimates of cost impacts developed in Step I; for example, a 5 percent increase in traffic loadings would produce half the impact estimated in Step 1 for a 10 percent increase. Pavement Damage Wheel loads of heavy Mucks contribute to various forms of pavement distress. Of the various types of damage, fatigue (which leads to cracking) and permanent deformation (rutting) are of great importance and are the primary focus of this study. A previously cited NCHRP Synthesis (2) noted that without dedicated, persistent truck weight enforcement officers, the highway system would have deteriorated long ago. However, an opposing perspective regarding the effect of buck weight on pavement damage was published by the New Jersey D.O.T. (8). This study was undertaken to quantify the magnitude of the pavement damage done by overweight trucks in New Jersey. This was accomplished using the AASHTO 18-Kip Equivalent Axle Load parameter, established engineering-economic procedures, and data obtained from the New Jersey State Police. Questions specifically addressed Include: I. How much pavement damage is attributable to overweight trucks? 2. What are the costs associated with this damage? 3. Are these costs adequately covered by the revenues collected from the overweight violators? 4. Is mandatory off-Ioading (requiring violators to immediately lighten their loads at the ticketed location) justifiable? 8 Appendix A
It was found that detected overweight trucks cause a relatively small shortening of pavement life and, had overweight trucks been successfully off-loaded, a negligible savings would have result- ed. However, there is serious concern expressed in the New Jersey study that the number of overweight trucks actually detected represents a small fraction of the total number of violators. A Pennsylvania study (10) produced analytical guidelines for the posting of load limits. The analysis evaluated a variety of loading conditions (i.e. various load magnitudes and configurations) for different pavement thicknesses and material properties. It was found that axle configuration (i.e., single-, tandem-, and triple-axle assemblies) did not significantly affect pavement response, provided that the load per tire remained the same. A performance model based on present serviceability index was developed that related pavement performance to calculated subgrade strain. The program generates information concerning predicted years to failure for different load limits. Results indicate more damage responsibility for heavy loads on thin pavements than on thick pavements, as would be expected. However, the study concludes that cost allocation based on marginal pavement damage can be misleading if the initial cost of construction is not considered. The load-limit analysis procedure presented in this study can be a valuable tool in the evaluation of axle load limits and axle damage. The most recent and comprehensive study of pavement effects of heavy-truck effects on pavements was conducted at UMTRI by Dr. Tom Gillespie (11). Under NCHRP Project 1-25(1), the mechanics of truck-pavement interaction were studied to identify relationships between truck properties and damage (fatigue and rutting). Computer models of trucks were used to generate representative wheel load histories characteristic of the different trucks and operating conditions. Rigid and flexible pavement structural models were used to obtain pavement "influence functions," which characterize the pavement response to tire loads at any location on the roadway. Fatigue damage to rigid and flexible pavements is most directly detennined by maximum axle loads and pavement thickness. Fatigue damage varies over a range of 20: 1 with typical varia- tions in axle loads and over the same range with typical variations in pavement thickness. Other 9 Appendix A
vehicle properties have a smaller, but still significant, influence on fatigue. The relationships between damage and certain truck properties of interest are as follows: i. Axle loads - Fatigue damage is dominated by the most heavily loaded axles. The first-order determinant of overall fatigue damage for a vehicle combination is the sum of the Equivalent Single-Axle Loads (ESALs) for each axle. Assuming a fourth-power damage relationship, a 22-km axle is 23 times as damaging as a 10-km axle. 2. Tandem suspensions - Theoretically, tandem axles have the potential to be no more damaging to roads than single axles with equivalent load per axle (i.e., a 36-km tandem can be no more damaging than two 18-km singles). In practice, certain deficiencies in the performance of tandem suspensions preclude these benefits: a. Inequalities in static load sharing cause disproportionate fatigue from the heavily loaded axle. b. Most tandem suspensions produce dynamic loads comparable to their single axle equivalents. 3. Axle spacing - Aside from the suspension effects discussed above, locating axles at a close spacing does not contribute to pavement damage. Damage on flexible pavements is largely insensitive to axle spacing down to the limits dictated by current tire diameters. Pavement Cost /mp/ications of Enforcement Effectiveness The literature review addressed the documented sensitivity of various pavement impacts (e.g., damage, cost) to seek implications for effects of truck weight enforcement effectiveness. The methodology applied in TRB Special Report 225 (9) examined the impact of alternative truck weight regulation scenarios various pavement issues. Projections of heavy-truck miles by type of truck, region of the country, highway functional class, and operating weight were developed for Appendix A 10
a base case and alternative truck weight regulatory scenanos, i.e., referred to herein as "truck-weight cases". These projections were used to estimate impacts on truck costs, pavements, bridges, and safety. The study procedure is described as follows: "In-depth interviews with a cross section of firms selected to represent major segments of the trucking industry were a key input to the development of forecasts for the alternative scenarios. The analytical procedure used for the forecasting process is based on the assumption that all carriers would shift toward use of the most economical type of equipment, taking into account purchase price, operating costs, and He productivity improve- ments that might be realized by each type of equipment. The procedure takes into account all important constraints on the operation of each type of equipment, such as regional truck size and weight limits, the mix of commodities carried and types of operations involved, the proportion of time the equipment is weight-limited or volume-limited, and limitations of docks or storage capacity. Quantitative estimates of truck traffic for alternative scenarios were developed using a base case derived from FHWA forecasts, of 1995 vehicle miles by state, vehicle configura- tion, and highway functional class. Although the estimates are derived using forecast 1 995 traffic volumes, they actually are designed to represent the steady-state response of the industry to any change in weight limits; that is, they represent the situation that would exist in 1995 if the new limits had been In effect long enough for the industry to have acquired a fleet that had been optimized for operation under the new limits. Much of the estimated savings resulting from higher weight limits are likely to be obtained within 2 or 3 years of any change. However, carriers operating particularly expensive equipment arid those with operations that can benefit only marginally from the new limits could be expected to take appreciably longer to modify their fleet to take hill advantage of the new limits." Pavement impacts were estimated on the basis of costs for new pavements, reconstructed pavements, and pavement rehabilitation. Pavement rehabilitation costs, accounting for the greatest impact, were estimated using (a) projections of truck miles by vehicle type and operating weight, (b) AASHTO load-equivalence factors (used to calculate equivalent axle loads for different vehicles on flexible and rigid pavemerlts), (c) data on highway miles arid paved area from the FHWA 11 Appendix A
Highway Performance Monitoring System (HEMS), and (d) the Pavement Rehabilitation Cost Model, which was developed for TRY by Deacon (12). Deacon (12) developed sensitivity analyses using the pavement rehabilitation costs for pavements with widely varying levels of soil condition, traff c, and other variables. These sensitivity analyses indicated that, for pavements of a given width, there is surprisingly little variation in the added pavement rehabilitation cost associated with a 10 percent increase in traffic loadings. Depending primarily on soil condition, the added cost for 10 percent more ESALs on flexible pavements ranged from $12 per foot-mile on a very good soil (roadbed soil resilient modulus of 1,250 psi). On rigid pavements, the range was somewhat greater - from $7 per foot-mile on very good soil to $26 per foot-mile on very poor soil. For simplicity, a single-unit cost, $16 per foot-mile, has been chosen for use with both flexible and rigid pavements in estimating the pavement rehabilitation cost impacts of a 1 0 percent increase in traffic loadings. Pavement area by highway class and region was tabulated from FHWA's Highway Performance Monitoring System (HPMS) data base for flexible and rigid pavements. Local roads and other highways carrying less than 1 0,000 ESALs per year were excluded from these tabulations, because pavement costs for these roads are not likely to be significantly affected by the scenarios under consideration in this study. For each region and highway class, the added pavement rehabilitation cost per year associated with a 1 0 percent increase in traffic loadings was calculated by applying the unit cost of $ 1 6 per foot-mile to pavement area for the region and highway class. For the nation as a whole, the added pavement rehabilitation cost for a 10 percent increase in traffic loadings would be $344 million per year - $293 million for flexible pavements and $5 1 million for rigid pavements. The added cost (Z) for each truck-weight case was then estimated for each region and highway system: Z = X (Y/10 percent) 12 Appendix A
where X is the added cost for a 10 percent increase in traffic loadings and Y is the increase (or decrease) In traffic loadings, for each truck weight case expressed as a percentage of base case traffic loadings. Safer Implications of Enforcement Effectiveness The literature review addressed the documented sensitivity of accident occurrence (in terms of both frequency and severity) with truck weight to seek implications for safety effects of truck weight enforcement effectiveness. Campbell et al. (13) analyzed data based on fatal accident involvement ratios by gross weight for loaded single-unit trucks and combination vehicles on limited-access highways. Their findings suggest a moderate accident rate increase for higher gross weights. A caveat to this finding does exist, however, due to the relatively small number of data points and high degree of scatter. Fancher et al. (14) used the same data base to investigate relationships between fatal involvement rates and GVW for five-axle van tractor-semitrailers by crash type. That study found ~at: Fatal involvement rates in rollover and ramp-related crashes increased with increased GVWs. 2. For curve-related crashes and crashes in which trucks rear-ended other vehicles, increased GVWs may increase fatal involvement rates, although the trends were not as conclusive as those for the rollover or ramp-related crashes. 3. For jackknifes and sideswipes, increased truck gross weights do not affect the fatal involvement rates. Base accident rates used to estimate the impacts of alternative truck weight regulatory scenarios on safety as derived Campbell et al. (13) and other research were presented in TRB Special Report 225 (9). These base accident rates have implications for determining the effectiveness of truck weight enforcement activity and are shown in Exhibit 1 on the next page. 13 Appendix A
BASE ACCIDENT RATES USED TO ESTIMATE SAFETY IMPACIS OF SCENARIOS lope of Accident (per 100 million vehicle-mi) . . . Property Velli`:le Fatal Injury D.lmag`: Only . . Single-unit trucks 7.7 185 499 Tractor-semitrailers 10.2 245 595 Doubles 11.2 269 653 Exhibit A - 1 Source: TRB Special Report 225 The effect of truck weight on the severity of truck-car crashes has been extensively researched, with generally good agreement among past studies. In a truck-car crash, the primary determinant of the severity sustained by occupants of the car is the magnitude of the change of velocity (V) of the car at impact (151. V, in turn, increases dramatically with increased mass ratios between the truck and the car (161. The weight ratios of most existing medium or heavy Ducks to passenger cars range mainly Dom 7.0 to 30.0, and further increases in truck weight are not likely to result in significantly different V-values for cars or severity sustained by occupants of passenger cars in truck-car crashes. The base accident rates as reported in TRB Special Report 225 (99 were adjusted for changes in GVW using the following equation: R'= R(! ~ kG'/G) where R and R' are base and adjusted accident rates, G arid G' are average GVWs for the base case and the alternative scenario, and k is a constant. The constant k reflects the extent to which changes in average GVW are expected to affect accident rates. For example, a k of 0.0 would imply that accident rates are urlaffected by gross 14 Appendix A
weight; a k of 0.5 would imply that a 1 0 percent increase in average gross weight would cause a 5 percent increase in accident rates. Because data for producing reliable estimates of k are not available, the TRB Truck Weight Study Committee (9) judged that 0.5 and 0.0 are reasonable upper and lower bounds for k. Key findings from TRB Special Report 225 69J on the effects of truck operating weight and configuration on accident rates are as follows: 1. Without making changes to truck dimensions, number of axles, and vehicle and component designs, increased truck weights would increase accident involvement rates of trucks, particularly for rollover and ramp-related crashes for multiple-trailer combinations. In addition, the rates of fatal involvements in crashes on curves or crashes in which trucks rear-end other vehicles may also be adversely affected. 2. Seventy of truck accidents is not sensitive to truck configuration, and given that a truck accident occurs, the probabilities of fatalities or injures are not sensitive to changes in truck weight. TRUCK WEIGHT ENFORCEMENT OPERATIONS The weight and size of commercial vehicles is regulated and enforced for the following two reasons: (1) to avoid excess damage to roadway structures caused by overweight and overheight loads, and (2) to assure that operating safety of the roadway is not compromised by loads or vehicles that occupy an unsafe proportion of the roadway. A designated agency is generally responsible for enforcing the size and weight of commercial vehicles on state highways and in other jurisdictions. If a citation is issued to a commercial vehicle driver for carrying a load that is either overweight or oversized, the driver must pay the fines to the local court system. Commercial vehicles are required to stop at weigh stations or ports-of-entry, when they are open. For the most part, safety regulations nationwide are prescribed by the Federal Motor Carrier Safety Regulations (FMCSR) and administered through the Motor Carrier Safety Assistance Program (MCSAP) and state safety programs (l 7). 15 Appendix A
The literature review addressed aspects of truck weight enforcement activity which pertain to assessing weight enforcement effectiveness. Specifically searched literature topics were: general weight enforcement procedures, application of automated weight monitoring procedures, relevant evidence enforcement, effect of enforcement on compliance, weigh scale avoidance by trucks, and enforcement agency effectiveness evaluation. Genera/ weigh! enforcement procecfures Documented research studies have addressed truck size and weight enforcement operation in terms of specific Muck weighing practices which have implications for NCHRP Project 20-34. For example' NCHRP Synthesis of Highway Practice 68 (18) pointed out Hat significant differences exist between states in almost all aspects of enforcement. These differences include levels of enforcement activity, tolerance, actions taken toward violators, fine schedules for violations, and court actions. The study makes recommendations as follows: I. Assign all size and weight enforcement activity to a special operations unit that is adequately staffed. Establish program needs for use of various scales to ensure reasonable coverage of state systems and apprehension of violators. 2. Take effective action against violators with appropriate fine schedules with deterrent effect. Coordinate legislative and regulatory action. 3. Coordinate programs arid develop mode! systems with He assistance of the Federal Highway A~nin~stration, He American Association of State Highway arid Transportation Officials and the National Governors' Association. 4. Study problem of difference in permit issuance, which has greater impact than enforcement, arid those affected are possibly even more numerous. The problem stems partially from the fact that not all states have similar views on pennit issuance. Specific aspects of problem are permit limits, application arid issuance methods, routine issuance definitions, types of permits, permit restrictions, escort practices, arid motor vehicle accessory requirements. States should cooperate to issue pennits for interstate movements. One such compact needs to be examined because it has not 16 Appendix A
had anticipated results. Because of adverse effects of current practice, the permit situation badly needs correction. A Texas report (19) described Texas state regulations affecting motor vehicle sizes and weights, agencies involved directly or indirectly in the enforcement of these regulations, characteristics of oversize-overweight vehicle movements within the state (both legal and illegal movements), and the cost of these vehicle movements. The characterization of oversize-overweight movements was emphasized. To study the economic effects to the state, a 1 00 percent compliance case was developed to compare with the actual case. The study showed that, while current oversize- overweight movements may save the trucking industry up to 1 .4 billion dollars over the next twenty years at current conditions, these movements are estimated to cost the state an additional 261 million dollars over the same twenty-year period. Similarly, enforcement of state laws is estimated to result in only 84 million dollars if the current fine and permit fee structure is maintained. It is recommended that the current fine and fee structure be revised so that violators would pay for their share of the estimated damage to highways. App/icafion of Automated Weigh f Monitoring Procedures Three Oregon papers describe innovative procedures for automating truck weight enforcement activities. The first addresses screening of overweight trucks in the vicinity of Ports of Entry, Me second describes an automated management tool for deploying enforcement personnel, and the Gird relates application of automated vehicle identification technologies. Krukar and Evert (20) reported on the Oregon Department of Transportation's automation of the Woodburn port-of-entry (POE), located on Interstate Highway 1-5 southbound at milepost 274.40. Automation of the Woodburn southbound POE interfaced six components: (1) weigh-in- motion sorter scales, (2) automatic vehicle identification (AVI) system, (3) electronic static scales, (4) supervisory computer (SC), (5) various software interfaces, and (6) motor carrier data base. Reported advantages ofthe procedures were to minimize manpower tasks; improve weight, size, and safety enforcement; provide more data for planning and design purposes; maximize enforcement agency resources; improve tax collection and audit capabilities; and save time for the trucking industry. Findings indicated improvements and cost savings in (1) weighmaster functions, (2) 1 q Appendix A
performance measures, (3) POE operations and functions, (4) human resources deployment, (5) data collection, (6) tax audit trails, (7) tax collection, and (8) to the private motor carrier industry. An earlier paper by Krukar and Evert (21) described Oregon's Integrated Tactical Enforcement Network (ITEN). ITEN is an automated management tool for deploying enforcement personnel in a more effective and efficient manner. The foundations for this network are the automated ports-of-entry, the data collection weigh-in-motion systems coupled with automatic vehicle identification systems, automatic classification systems, computers, communication network, and custom software. A 1986 paper by Krakar and Evert demonstrated the use of WIM, AVC, AVI, and DBFCA equipment in the collection of traffic and truck weight data, applied in Oregon. Nine integrated, yet separate elements, involved the automatic identification, tracking, classification, and weighing of trucks traversing U.S. Interstate Highway 5 northbound from the Oregon-California border to the Oregon-Washington border, a distance of 3 1 0 miles, both on and off the Interstate System. Re/evanf Evidence Enforcement Relevant evidence truck weight enforcement is an application of civil rather than criminal law in enforcing truck weight. The procedure involves inspection of relevant documents (receipts, bills-of-laden) comprising records of origin, destination, weight and composition of shipments. When these records Indicate vehicles have violated weight laws, suits are Vitiated. Advantages are: (1) numerous violations can be cited in a single suit thereby rendering this procedure highly effec- tive against habitual violators, (2) the procedure is unobtrusive and not route-specific, and (3) no on- enforcement activity is required. Disadvantages are: (1) administration of the procedure can be costly, arid (2) the procedurets sensitivity is limited to gross weight violations. A number of states, i.e., Minnesota, Montana, and Texas, arid the Province of Alberta, Canada, apparently favor Relevant Evidence enforcement. While little literature was found regard- ing Relevant Evidence, it is well documented that Minnesota has demonstrated benefits of its 18 Appendix A
Relevant Evidence procedures, by virtue of their 1991 review of 428,000 bills of lading which resulted in 529 overweight loads being detected. Under Minnesota state statute, Relevant Evidence is defined as: "A document evidencing the receipt of goods issued by the person consigning the goods for shipment or a person engaged In the business oftranspordng or forwarding goods, which states a gross weight of the vehicle and load or the weight of the load when combined with the empty weight of the vehicle that is in excess of the prescribed maximum weight limitation permitted by this chapter is relevant evidence that the weight of the vehicle and load is unlawfill...a document required to be kept indicating a unit of measure that, when converted to weight and combined with the weight of the empty vehicle, indicates a gross weight in excess of the prescribed maximum weight limitation permitted by this chapter is relevant evidence that the weight of the vehicle and load is urdawful. The forgoing provisions cannot limit the introduction of other competent evidence bearing upon the question of whether or not there is a violation of the prescribed maximum weight limitations permitted by this chapter." Minnesota statute also requires that records be kept for certain overweight loads, and established penalties, by stating: "Record-keeping. A person who weighs goods before or after unloading or a person who loads or unloads goods on the basis of liquid volume measure shall keep a written record of the origin, weight and composition of each shipment, the date of loading or receipt, the name and address of the shipper, Me total number of axles on the vehicle or combination of vehicles, and the registration number of the power unit or some other means of identification by which the shipment was transported. The 1 Report to Congress from the Secretary of Transportation. Overweight Vehicles - Penalties end permits. An Inventory of State Practices for Fiscal Year 1991. Publication FHWA-MC-93-001. Federal Highway Administration. Washington, D.C., April 1993 19 Appendix A
record shall be retained for 30 days and shall be open to inspection and copying by a state law enforcement officer or motor transport representative, except state conservation officers, upon demand. No search warrant is required to inspect or copy the record. This subdivision does not apply to a person weighing goods who is not involved in the shipping, receiving and transporting of those goods, or to a person weighing raw and unfinished fann products transported in a single unit vehicle with not more than three axles or by a trailer towed by a farm tractor when Me transportation is the first haul of the product. Evidence. Except for records relating to the loading and unloading of We first haul of unprocessed or raw farm products and the transportation of raw and unfinished forest products, a record kept and mat ned as provided In subdivision ~ that shows that a vehicle has exceeded a gross weight I~rnit imposed by this chapter is relevant evidence of a violation of this chapter. The foregoing provisions do not limit the introduction of other competent evidence bearing upon Me question of whether or not there is a violation of the prescribed maximum weight limitation permitted by this chapter. Penalty. A person who falls to keep, maintain, or open for inspection and copying, those documents as required in subdivision ~ is guilty of a misdemeanor. A person who does not accurately record the information required to be contained in those documents required in subdivision ~ is guilty of a misdemeanor." An ongoing internal study by Me Wisconsin D.O.T. vail evaluate the effectiveness of Relevant Evidence laws in Minnesota, Montana, and Alberta. We have discussed this effort with the consultant performing the study. Results are scheduled to be available on August I, 1994. Our discussion with the consultar~t indicated that enforcement agencies in northern climates re-assign personnel to examine appropn ate records during inclement weather. No conclusion had been reached by the consultant regarding the effectiveness of Relevant Evidence laws. We shall follow- up on the current study as part of our Task 5 effort. 20 Appendix A
Effect of Enforcement Level on Compliance A Canadian study (22) reports that little is known about the effect of the level of enforcement on the degree of compliance with the weight limits. To fill this gap in the literature, the authors present the context, methodology and tentative results of three studies of the effect of enforcement on compliance carried out on provincial highways in Saskatchewan. Analysis of data from 12 permanent weigh scales situated on primary highways indicated that as the inspection rate (apprehension probability) increased to about five percent, the violation rate decreased rapidly. Increasing apprehension probability beyond five percent had little impact on violation rate. The data from 1 8 mobile patrol units confirmed this trend. Data from before and after type studies at two specific locations were used to study the effect of continuous andfor zero enforcement. One location was selected to be representative of a short-haul situation. The other location was selected to represent long-haul truck movements incorporating interprovincial and intercity truck haul with relatively little local haul. Enforcement levels were employed over a length of time necessary to ensure the trucking industry was aware of the change. The long-haul study showed that the rate of violation of gross weight limits decreased to a low of 2.8% at continuous enforcement from 5.6% at normal enforcement. The violation rate increased to 18.6% at zero enforcement. A statistical analysis utilizing the t-test indicated that there is a significant difference between the number of overweight trucks at the various enforcement levels. The short-haul study also indicated a significant difference between zero and normal enforcement. A sophisticated mathematical modeling approach to economic theories of compliance was documented by Hildenbrand et al., (23). The authors note a general acceptance of the notion that the costs associated with complete compliance are excessive. At the same time, the nature of public highways is such that enforcement is required. The theoretical model provides a strategic framework for analyzing the economic outcome of different levels of fines and enforcement efforts. The economic tools of "game theory" are used to model the conflict between truckers and the highway enforcement officials. Truckers have two choices: to comply with the law, or to overload their truck. The regulation enforcers also have two choices: they may have the scale open and weigh passing trucks, or they may close the scale. Assuming a randomized operation of scales and random overloading by truckers, the game theory model establishes the equilibrium level of weight regulation compliance, given a set of enforcement parameters. The game theory model is developed to estimate the equilibrium levels of enforcement and compliance. The paper concludes with a discussion of Me model results and its implications for highway transport policy. 21 Appendix A
Weigh Scale Avoidance by Trucks This behavior is a major concern to operational truck weighing operations. Two reported studies were undertaken in Virginia and Wisconsin. The most comprehensive work on truck avoidance has been documented by the Wisconsin Department of Transportation (241. Three levels of enforcement were conducted as follows: Level 1 - Mainline scale only Level 2 - Mainline scale and patrol on a major bypass Level 3 - Mainline scale and patrol on major and secondary bypasses. Avoidance of overweight is indicated by truck volume (see Exhibit A - 2 and by highway wear, expressed in ESALs (see Exhibit A - 31. The study revealed that the rate of overweight trucks on the mainline decreased 6% during Enforcement Level 1, while the rate of overweight trucks on the major bypass increased 140 percent. In Enforcement Level 2, the rate of overweight trucks on the mainline was 27 percent below baseline, while the rate of overweight trucks was still up 70 percent over baseline on the major bypass. During Enforcement Level 3, the rate of overweight trucks on the mainline declined still more below baseline to 34 percent, but the associated rate of overweight trucks on the major bypass had also declined to 13 percent below baseline. ESAL's were computed Mom individual axle weights arid as well as axle weight groupings. Although ESAL's were down 14 percent on the mainline during Enforcement Level 1 (about the same percentages truck volume), the Enforcement Levels-2 and 3, ESAL's were down 6 percent and 9 percent more than truck volume. Increased enforcement also meant scattered ESAL's: 40 percent of diverting ESAL's used the major bypass route during Enforcement Level 1, but only 8 percent used it during Enforcement Level 2 with a patrol there, and no ESAL's diverted to the major escape route in Enforcement Level 3. It is significant that trucks, overweight trucks and ESAL's all diverted in We same pattern. 22 Appendix A
1 1 SCALE AVOIDANCE PATTERNS: BY TRUCK YOLUVE 48-HOUR COWS ENFORCEUENT AT SCALE. END ORCEUENT LEVEL 1 loon &La4S~ TR=`S - IOOS NoRu4L a4$12 T~S 3002 NORMAL B" T~KS ENFORCEMENT LEVEL 2 ENFORCEUENT LEVEL ~ 56X- 07~ 3.4X- T" AYO"D 36X- SECONDARY BYP"S AS: ~ BYPASS \ ~" / T~ 852 ~ 3.6: - OVER // )S.OS-~" AVO"D it/ )~- SEC~"Y BYPASS ,l/ / ~FLEX-u~ B - 4SS \ ~" / T - ~82X 6.3X - OTHER NOff-T" AVID -SECONDARY BrP"s 7 NONE- U4JOR BIBS / T~83Z Exhibit A - 2 Observed Wisconsin Scale Avoidance Patterns by Truck Volume 23 Appendix A
SCALE AVOIDANCE PETERS: BY OVERWEIGHT TRUCKS ENFORCEMENT LEVEL 1 ~ '~ - n' - n ADOS LaUO OVERLIE - T TR=KS BOOK NORMAL S640 OVERNIGHT ~5 BOOS NOR~AL-IS] OVERWEIGHT AIMS - 6~ M~ BYPASS \ ACME / T~79: ENFORCEMENT LEVEL 2 > 37.2: - OT - R 2.BY - UA=R B - ASS \ HA - " / T - Usso: / / ENfORCEUENT LEVEL ~ . _ ~ _ >453- OVER - UA~ BYPASS \ ~" ~ T - U-SSX Exhibit A - 3 Observed Wisconsin Scale Avoidance Patterns by ESAL 24 Appendix A
The overall Wisconsin D.O.T. study was conducted from various tasks, producing ~ ~ key findings as follows. " I. Truck avoidance of enforcement scales was found to range: o o o o 15-~% by truck volume; 21-45% by overweight trucks; 6-34% by the rate of overweight trucks; and 14-26% by ESAL's (the engineering standard unit for pavement fatigue). Of these measures, ESAL diversion is equatable to added pavement deterioration or wear. 2. At 1 5-1 8%, avoidance by truck volume was considerably under the 30% diversion that was expected. Avoidance broke down as follows: o 5-1 I% was geographical-based (took an alternate route); o 3-5% was time based (waiting at rest stops for scale to close); and 0 4-6% was unknown (beyond the monitored routes). 3. Concentrated enforcement meant scattered truckers. As enforcement was incrementally increased each phase, truckers diverted by routes progressively farther away from the scale. 4. Although ESAL's must be calculated and are therefore intangible, they are the most important basis by which to evaluate and modify weight enforcement activity since ESAL's are a direct measure of the wear trucks inflict on pavements. Accordingly, the state patrol should develop an ability to gauge their truck weight enforcement electiveness based on ESAL's. A logical first step would be more portable weighing activity on the bypass routes coordinated with scale operation. This Hearts optimizing operations with existing weighing equipment' buying more WIM or other portable weighing equipment, and employing more inspector personnel. 25 Appendix A
5. Scale avoidance effects, assuming the scale in operation 34% of the time, include reduction of 2 years in the pavement life of the major bypass route and an increase of ~ year in the pavement life of the mainline. Elects on other routes are uncertain, but should be quantified through first, a fills inventory of bypass routes surrounding each scale and second, more WIM or other weighing equipment monitoring. 6. Of the trucks diverting around the Rusk Scale: o o o 0 51% had safety violations (MCSAP); 24% had driver violations (predominantly hours of operation); 8% had weight violations; 4% had registration violations; arid o ~ 3% had no violations whatsoever. 7. During Rusk Scale operations, the likelihood of weight violations was ~ times greater on the major bypass route than at the scale. Driver violations were 65% higher on the major bypass route than at the scale. Safety violations were 14% higher on the major bypass than at the scale. The likelihood of legal trucks on the major bypass was I/3 that of the scale. 8. After enforcement cessation, truckers waiting in rest stops and restaurants quickly returned to the mainline, within I-S hours. This traffic normalization pattern may have implications for enforcement strategy: e.g., conduct weighing at rest stations simultaneous with scale operation. 9. Although most truckers returned to the mainline 9-16 hours after scale closure, some continued to bypass even 24 hours after scale closure. This traffic normalization pattern suggests that enforcement should continue to monitor bypass routes Me first ~ hours after scale closure. It also suggests that some truckers decide many hours in advance and far away to avoid the scale, although their disappearance off the mainline is not recorded until later. 26 Appendix A
1 O. ESAL factors (average ESAL's by truck class) used by Wisconsin pavement design engineers as a standard since 1987, are adequate to accommodate diversion on scale bypass routes, since these standards slightly exceed ESAL factors found in our field study. ESAL factors found differed significantly by highway type. 1 1. Portable or pad weigh-in-motion (WIM) equipment accuracy was found to be +13.3% on gross truck weight at the 95°/O confidence level. Accuracies by axle weight were found to range +19-26% at the 95°/O confidence level. The portable WIM was 3 times more reliable than bridge WIM (BWIM) equipment: it lost 5% of total truck traffic due to malfunctions compared to a 14% loss for BWIM." A significant issue raised in the Wisconsin study was the relative effect of pavement wear between the mainline and diversion routes resulting from truck avoidance of weight enforcement. Based on the computed ESALs, it was determined that pavement service life ofthe routes used for diversion was shortened by two years. A Virginia study (25) also studied weigh scale avoidance by overweight trucks. In addition, secondary study objectives were: (1) to determine the magnitude of overweight truck activity on selected routes, and (2) to compare traffic loading data collected using static scales with enforcement with data collected using weigh-in-motion without enforcement. Two weigh stations on one Interstate route were studied for weigh station avoidance. It was found that 1 1 and 14 percent of the trucks on routes used by trucks to bypass the two stations were overweight. However, at one station, 50 percent of the runbys were trucks which passed the weigh station because the entrance lane to the station was filled. The study also found that between 12 and 27 percent of trucks on two primary routes and one other Virginia Interstate route were overweight. Regarding the second study objective, traffic loadings collected with WIM without enforcement are 30 to 60 percent higher tears loadings collected using static scales and enforcement. 27 Appendix A
Enforcement Agency Effectiveness Evaluation NCHRP Synthesis of Highway Practice 82 presented criteria for an enforcement agency to evaluate the effectiveness of its pro gram. The synthesis points out that comparing truck population with the number of vehicles being weighed is part of determining the effectiveness of a program, e.g., these steps are generally followed by enforcement agencies as part of their periodical FHWA certification programs. Data on overloaded trucks, truck routes and volumes, types of movements, vehicle classifications, types of cargo and distances traveled are also applied in this evaluation. The effective combination and deployment of various types of scales is essential for effective operations. In most states, overweight violations are misdemeanors and are processed through the courts. Some of the problems in truck weight enforcement are attributed to inefficient personnel. Each state needs to evaluate its truck weight enforcement program beginning with cooperation within and among the states. This synthesis report describes data collection and its application to the truck population, site selection and equipment, weight laws, enforcement. The report recommends various short- and long-term self-evaluation program steps. Another study (4) also developed a method for assessing the electiveness of a truck weight enforcement program. The procedure compared incremental revenues earned by overloading a particular truck with the expected cost of geuing caught, taking into account the fine structure and the level of enforcement. Results demonstrated that fines are not structured to be an effective deterrent for would-be violators. An ongoing study undertaken by We Wisconsin D.O.T. is thoroughly evaluating the Wisconsin's truck safety and weight enforcement program. Objectives of the study are: (1) to compare Wisconsin's program with programs in other states, (2) to develop specific objectives and measures of success for the program, and (3) to prepare and evaluate strategies to meet the objectives. Results of this study will not be available until August; although we have been advised by the consultant, Cambridge Systematics, Inc., that they concluded from their review of Federal and state reports that "no one is measuring the right thing to determine the effectiveness of truck weight enforcement, nor have appropriate proxy measures been developed". An applied truck weight enforcement M.O.E. in the Wisconsin study is the estimated enforcement "coverage", taken as a proportion of scale capacity to truck traffic on the road. 28 Appendix A
STATE DATA SOURCES FOR MONTIORING TRUCK WEIGHT EFFECTS A review of the literature has demonstrated a number of potentially available data sources which state highway agencies can apply to monitor the effectiveness of truck weight enforcement activities. These are SHRP's Long-Term Pavement Performance (LTPP) Program WIM sites, Pavement/Bridge/Safety Management Systems, the Highway Performance Monitoring System, and Traffic Monitoring Guide data collection sites. A brief explanation of each is as follows. SHRP i;ong-Term Pavement Performance (I TPPJ sites The Strategic Highway Research Program (SHRP) was a 5-year, $150 million dollar research program funded through a set-aside of state-apportioned Federal highway aid funds. The Long-Term Pavement Performance (LTPP) Program was designed ~ a 20-year program. With the completion of the first 5 years of the research under SHRP, the LTPP Program was transitioned to the FHWA. Objectives of the LTPP Program are to: I. Evaluate existing design methods. 2. Develop improved design methods and strategies for the rehabilitation of existing pavements. Develop improved design equations for new and reconstructed pavements. Determine the effects on pavement distress and performance of loading, environments material properties and variability, construction quality, and maintenance levels. 5. Determine the effects of specific design features on pavement performance. 6. Establish a national long-tenn pavement data base to support SHRP objectives and future needs. Information Mom the LTPP studies is available from the LTPP Information Management System (IMS), a data base developed under SHRP. The LTPP Program will collect data on in- service pavement sections throughout the country for a 20-year period. 29 Appendix A
Data collected under the LTPP Program are classified into the following seven modules: 1. Inventory 2. Materials Testing 3. Climatic 4. Maintenance 5. Rehabilitation 6. Traffic 7. Monitoring The most relevant data modules for application to truck weight enforcement monitoring are the maintenance and traffic modules. The maintenance module consists of 9 tables that store data recorded on 1 7 data sheets; one of the data sheets is used to record historical maintenance activities. This module is primarily used to record maintenance activities performed on the test section after inclusion in the LTPP Program. This module also records maintenance-related information such as placement of seal coats, patches, joint resealing, milling' and grooving. The traffic module will store annual traffic summary statistics for a study lane for each year since the road was opened to traffic. The specific items for the study lane will include automobile and truck volumes, axle weight distributions by axle configurations (single, tandem, tridems, etc.) and weight range(s) that are usually in 1000- to 2000-lb (454- to 908-kg) increments, estimated Equivalent Single Axle Loads (ESALs) using American Association of State Highway and Transportation Officials (AASHTO) procedures, and an indication of the statistical variability of the data. Highway Performance Monitoring System (HPMSJ The HEMS is a nationwide inventory system that includes all of the nation's public road mileage as certified by the States' Governors on an annual basis. In concert with recent highway legislative mandates and regulations, this mileage includes all facilities both on and off the state highway systems. Each state furnishes on an annual basis all data requirements specified in the HEMS Field Manual. The provision of data is a cooperative effort with the state highway agencies 30 Appendix A
(SHAs), local governments and the metropolitan planning organizations (MPOs) working to assemble and report the necessary information. The FHWA identifies the data to be collected, establishes efficient collection methods, develops improve<! analytical techr~ques, and analyzes the data. Collectively, these activities facilitate informed highway plaIming, policy making, and decision making. Data provided by state agencies falls into two primary sample classifications. These are "standard" and "donut area" samples: o A standard sample section record contains the universe data plus additional data items related to the physical characteristics, condition, performance, use, and operation of the sampled sections of highway. These sample data provide detailed information which is used as the basis for evaluating change over time, and provides the basic input to the HEMS Analytical Process (models). O Donut area samples are unique in that their sole purpose is to enhance the precision of travel estimates outside of the adjusted urbanized areaks) boundary but within the NAAQS nonattainment areas designated by the Environmental Protection Agency (EPA). Consequently, donut sample data item additions are limited to identification, AADT and an expansion factor. Annual area-w~de HEMS data reporting requirements are summarized immediately below: 1. System Length and Daily Vehicle Travel Summary Data. 2. Minor Collector and Local Functional System Length Data. 3. Fatal and Injury Motor Vehicle Accident Data. 4. Travel Activity by Vehicle Type Data. 31 Appendix A
Vehicle classification data requirements which are relevant to NCHRP Project 20-34 are as follows: I. Two-Axle Six-Tire Single-Unit Trucks -- All vehicles on a single frame including trucks, camping and recreational vehicles, motor homes, etc., having two axles and dual rear wheels. 2. Three-Axle Sinale-Unit Trucks -- All vehicles on a single frame including mucks, camping and recreational vehicles, motor homes, etc., having three axles. 3. Four~r-More Axle Sin~le-Unit Trucks -- All vehicles on a single frame with four or-more axles. 4. Four-or-Less Axle Sincle-Trailer Trucks -- All vehicles with four-or-less axles consisting of two units, one of which Is a tractor or straight truck power-un~t. Five-Axle. S~ngle-Trailer Trucks -- All five-axle vehicles consisting of two units, one of which is a tractor or straight truck power-unit. 6. Six-or-More Axle. Single-Trailer Trucks -- All vehicles with six-or-more axles consisting of two units, one of which is a tractor or straight truck power-unit. Five-or-Less AxIe. Multi-Trailer Trucks -- AH vehicles with five-or-less axles consisting of three-or-more units, one of which is a tractor or straight truck power unit. 8. Six-Axle Multi-Trailer Trucks -- All six-axle vehicles consisting of three-or-more units, one of which is a tractor or straight truck power-unit. 9. Seven-or-More Axle. Multi-Trailer Trucks -- All vehicles with seven-or-more axles consisting of three-or-more units, one of which is a tractor or straight truck power unit. 32 Appendix A .
An important data item provided by the HPMS sample with regard to our assessment of candidate measures in "road roughness". One intent of the HPMS is to provide a measure of pave- ment condition that has nationwide consistency and comparability and is as realistic and practical as possible, a uniform, calibrated roughness measurement for paved roadways. The details and reporting requirements were established by an HPMS Pavement/ Roughness Working Group. Roughness is defined (in accordance with ASTM E 867-82A) as "The deviations of a surface from a true planar surface with characteristic dimensions that affect vehicle dynamics, ride quality, dynamic loads and drainage." After a detailed study of various methodologies and road profiling statistics by the FHWA/State Pavement/Roughness Working Group, the International Roughness Index (IRI) was chosen as the HPMS standard reference roughness index. The IR] was chosen because it facilitates correlation to a variety of roadmeter vehicles over a range of surface types. The summary numeric (HPMS data reporting unit) is the IR] in in/ml or m/km. IR} is computed from elevation data ("known profile") in a wheel-path for use as a profile numeric for profile measuring methods. The primary advantages of the IR} include: I. It is a time-stable, reproducible mathematical processing ofthe known profile. 2. It is broadly representative of the ejects of roughness on vehicle response and user's perception over the range of wavelengths of interest, arid is thus, relevant to the definition of roughness. 3. It is identical to the Reference Quarter Car Simulation (RQCS) inches per mile statistic derived in the National Cooperative Highway Research Program (NCHRP) 228 Report (26). 4. It is compatible with all profile measuring equipment currently available, and projected, in the U.S. market. 5. It is independent of section length and amenable to simple averaging. 33 Appendix A
6. It is directly consistent with recently established international standards, arid able to be related, through published correlations to other U.S. arid foreign roughness measures. Truck Weight Data The proposed HPMS truck weight sample is a subset of the vehicle classification sample. This process eliminates duplication and directly ties the estimates on weight, classification, and volume. Since automatic vehicle weighing equipment classifies and counts, and the recommended period of measurement is the same (48 hours), sample sections in the weight sample do not require a separate classification or volume count. This combination further reduces the level of effort required by the recommended program. The stratification categories remain the same as those in the vehicle classification scheme. As in the classification element, the distribution of the sample within the combined strata will remain proportional to traffic volume measures. The minimum recommended reporting strata are: 1. Interstate 2. All other roads The estimation of sample size for the truck weight sample is based on the characteristic Equivalent Single Axle Loadings or Loads (ESAL). Exhibit A - 4 illustrates the sample size and precision relationships at the 95 percent confidence level for the total Interstate system. The analysis conducted shows that about 30 measurements (over a 3-year cycle) are needed to estimate equivalent single axle loadings (ESAL) on the Interstate system for 3S2 trucks (18- wheelers) with a precision of +/- 10 percent with 95 percent confidence. The 3-year cycle acts to further reduce the sample needed annually. If the reporting strata were Interstate Rural and Interstate Urban, and the same precision levels were desired in each, then a sample of 60 locations, 30 rural arid 30 urban, would be needed. 34 Appendix A
Interstate Sample Size vs. Precision (Equivalent Single Axle Loads at the 95% Confidence Level) 50 40 Precision as a 30 Percentage of the Estimate 20 10 To 6 or More Axle Trucks (ESAL) _~ ~/ 3-Axle Combinations (ESAL) , , 3S2 Trucks (ESAL) \~ lo go so do 50 100 Exhibit A - 4 Pavement/Bridge/Safety Management Systems 200 300 Sample Size Source: Traffic Monitoring Guide The Intermodal Surface Transportation Efficiency Act (ISTEA) of 1991 required states to develop and implement systems for managing: Highway pavement of Federal-aid highways; bridges on and off Federal-aid highways; highway safety; traffic congestion; public transportation facilities and equipment; and intermodal transportation facilities and systems. In addition, this legislation requires states to develop and implement a traffic monitoring system for highways and public transportation facilities and equipment. These requirements went into effect on a designed National Highway System (NHS) on October I, ~ 995, and on non-NHS Federal-aid highways on October I, ~ 997. 35 Appendix A
Pavement management system (PMSJ means a systematic process that provides, analyzes, and summarizes pavement information for use in selecting and implementing cost-effective pavement construction, rehabilitation, and maintenance programs. Mandated data elements to be included in the PMS include: i. An inventory of physical pavement features including the number of lanes, length, width, surface type, functional classification, and shoulder information. 2. A history of project dates and types of construction, reconstruction, rehabilitation, arid preventive maintenance. ,. Condition surveys that include ride, distress, rutting, and surface friction. 4. Traffic information including volumes, classification, and load data. 5. A data base that links all data files related to the PMS. The data base shall be the source of pavement related information reported to the FHWA for the HEMS in accordance with the HPMS Field Manual. Applicat~ons of Pavement Management Systems The state-of-~e-art is Pavement Manage- ment Systems (PMS) application is aptly described by Novak and Kuo (27) as "an application software system that analyzes and processes data from the designated data base for use by policy makers who are then able to do such things as control long-term network condition and funding re- quirements [via maintenance, rehabilitation, and reconstruction (MR&R) program development constraints] to reduce the total cost of pavement preservation, and to have decisions flow from the top down.' Various highway agencies and researchers have recently developed efficient methods for maintenance planning. PMSs have been implemented in numerous states. Three illustrative examples studied describing their application are cited in Michigan, Maryland, and Virginia. 36 Appendix A
UMTRI's Novak and Kuo (27) noted that pavement management systems are typically designed to select projects and treatments on the basis of which alternatives have the lowest project life-cycle cost. Network life-cycle cost analysis is based on the remaining service life and strategy analysis concepts, which are not in wide use. Therefore, these methods are explained briefly. Conceptually, network and project life-cycle cost analysis are similar in that for network analysis, the lane-mile length of each alternative program is used in place of each alternative project' and each alternative program's average design service life is substituted for alternative project treatments. Novak and Kuo also illustrated procedures to use project life-cycle cost analysis to increase the total cost of network preservation. They also proposed that the policy level use network life- cycle cost analysis to minimize the total cost of network preservation. Economic analysis would then be a three-step process: network life-cycle cost analysis, to establish program development constraints that minimize the total cost of preservation; program analysis, to select the combination of projects and treatments that meet policy constraints and maximize program benefits; and engineering analysis, to minimize project cost. A Maryland study noted that PMS and Maintenance Management Systems frequently neglect effects on user costs, which can greatly exceed the maintenance costs. Wei and Schonfeld (28) conducted a comprehensive literature review and questionnaire survey, to argue that the concept of combined cost for highway maintenance and traffic operation is relatively unfamiliar. Recognizing ex~shng deficiencies, the authors proposed a maintenance planning methodology to evaluate venous economic and safety factors and to analyze technical trade-offs between different maintenance strategies. A quantitative optimization model will then be developed for determining the best maintenance plan. The ultimate objective ofthe plan is to help decision makers to reduce user costs and Improve maintenance operations efficiency. Virginia has published a series of reports on the progression of their pavement management system (29). Among the issues discussed are the development of an adequate data base and the implementation of a condition rating system. 37 Appendix A
Among the major findings are the following: I. The applied condition inventory method differentiates among candidate projects for the establishment of maintenance replacement priorities. 2. A 5% random sample of pavements is adequate for condition monitoring purposes. 3. A significant portion of the interstate system is below par in structural capability as a result of truck traffic and axle loads and age. 4. 5. Continued increases in traffic and axle loads will significantly reduce the service life of traditional overlays. The condition rating system will provide management with an objective approach to pavement management including documentation of the funding required for maintenance replacement. Bridge management system (BMSJ means a decision support tool that supplies analyses and summaries of data, uses mathematical models to make predictions and recommenda- tions, and provides the means by which alternative policies and programs may be efficiently considered. A BMS includes formal procedures for collecting, processing, and updating data, predicting deterioration, identifying alternative actions, predicting costs, determining optimal policies, performing short- and long-term budget forecasting, and recommending programs and schedules for implementation within policy and budget constraints. Bridge management systems are to include a data base and an ongoing program for the collection and maintenance of the inventory, inspection, cost, arid supplemental data needed to support the BMS. States were to complete the BMS design process by October I, ~ 995, and the BMS is to be finely operational by October I, 1998. 38 Appendix A
Application of Bridge Marlagement Systems A Bridge Management System (BMS) can help transportation agencies evaluate current and future conditions and needs and determine the best mix of maintenance and improvement work on a road network over time with and without budget limitations. AASHTO guidelines (30) established minimum requirements of a BMS capable of providing this type of evaluation. At the minimum, a BMS should consist of both procedures for coordinating various organization units and technical inputs and a computerized database and decision support tool. The BMS must serve to facilitate allocating funds to bridges on a network in order to protect safety, preserve the national investment in bridges, and serve commerce and the motoring public. A BMS decision report (31) cited the BMS function of assisting the bridge manager in the cost-effective assessment of bridge infrastructure needs. Typical decision support that a comprehen- sive BMS should provide include: easy data storage, access and retrieval of bridge related informa- tion, assessment of bridge needs, evaluation and cost estimating of relevant, alternate strategies for possible timely inclusion in optimized capital and maintenance programs as well as network and project level forecasting and trend analysis. An example BMS application was documented by the Pennsylvania D.O.T. (32~. PennDOT has developed and implemented a comprehensive BMS. This system has been operational since December 1 986. Pennsylvania's BMS has the ability to store a wide range of bridge inspection data. The BMS also has the ability to analyze the data using individual subsystems in order to provide decision support for Department managers. A Bridge Rehabilitation and Replacement Subsystem provides cost estimating and prioritization of bridge improvement projects to support long range planning and programming decisions. This BMS provides cost estimating and prioritization of bridge maintenance activities for assistance in developing annual maintenance programs. A Modeling Subsystem that utilizes deterioration curves for bridge condition and bridge load capacity enables Department managers to predict future bridge improvement needs using different funding scenarios. An Automated Permit Rating and Routing Subsystem is being developed to provide decision support in the load rating, routing and issuance of permits for overweight and oversize 39 Appendix A
vehicles. Finally, a Reports Subsystem is available to provide both standardized and customized report generation capabilities for any subset of data in the BMS. Highway Safety Management System (SMSJ means a systematic process that has the goal of reducing the number and severity of traffic crashes by ensuring that all opportunities to improve highway safety are identified, considered, implemented as appropriate, and evaluated in all phases of highway planning, design, construction, maintenance, and operation and by providing information for selecting and implementing effective highway safety strategies and projects. SMS data requirements include: (1) Data necessary for identifying problems and determining Improvement needs. Data bases and data sharing shall be integrated as necessary to achieve maximum utilization of existing arid new data within and among the agencies responsible for the roadway, human, and vehicle safety elements. These records consist of information pertaining to: crashes, traffic, pedestrians, enforcement activities, vehicles, bicyclists, drivers, highways, and medical services; (2) Analysis of available data, multi-disciplinary and operational investigations, and comparisons of existing conditions arid current standards to assess highway safety needs, select countermeasures, and set priorities; and (3) Evaluation of the effectiveness of activities that relate to highway safety performance to guide fixture decisions. The SMS was scheduled to be fully operational by October 1, ~ 996. Traffic Monitoring Systems The Intermodal Surface Transportation Efficiency Act (ISTEA) of 1991 specifies "requirements for development, establishment, implementation, and continued operation of a traffic monitoring system for highways (TMS/H) in each State in accordance with the provisions of 23 U.S.C. 303 ". 40 Appendix A
TMS/H means a systematic process for the collection, analysis, summary, and storage of highway traffic data, including public transportation on public highways and streets. Highway traffic data must be sufficiently comprehensive when used to develop estimates of the amount of vehicular travel and associated vehicle characteristics for a system of highways. These data must support an estimation of traffic volume, vehicle classification, and vehicle weight. Specific weight requirements noted in the legislation include "the weights of such vehicles including the weight of each axle and associated distances between axles on a vehicle". TMS/H data elements include the following: a. Annual average daily traffic (AADT). The estimate of typical daily traffic on a road segment for all days of the week, Sunday through Saturday, over the period of one year. b. Annual seasonal factors. The set of 12 factors, one for each month of the year, that is used to adjust coverage counts to estimates of AADT. Annual seasonal factors make use of the All year's data collected by continuous counters. c. Automatic traffic recorder. A device that records the continuous passage of vehicles across all lanes of a given section of roadway by hours of the day, days of the week or months of the year. d. Continuous counter. An automatic traffic recorder that operates continuously for all hours of a year. e. Coverage count. A traffic count taken as part of the requirement for system-level estimates of traffic. The count is typically short-tenn and may be volume, classification, or weigh-in-motion. f. Functional classification. The grouping of streets and highways into classes or systems, according to the character of service they are intended to provide. The recognition that individual roads do not serve travel independently and most travel involves movement through a network of roads is basic to functional classification. 41 Appendix A
g. Functional system. Highways of a similar type as determined by functional classification. h. Highway traffic data Estimates ofthe amount of person or vehicular travel, vehicle usage or vehicle characteristics associated with a system of highways or with a particular location on a highway. These types of data include estimates of the number of vehicles traversing a section of highway or system of highways during a prescribed time period (traffic volume), the portion of such vehicles that may be of a particular type (vehicle classification), the weights of such vehicles including weight of each axle and associated distances between axles on a vehicle (vehicle weight), or the average number of persons being transported in a vehicle (vehicle occupancy). i. Traffic data collection session. The collection of highway traffic data for a defined period of time at a specific highway location. Applications of State Highway Agency Truck Weigh! Sampling A number of state have documented their truck weight monitoring procedures. Two examples are Wisconsin and Minnesota. Truck weight sampling procedures used by the Wisconsin Department of Transportation were described by Gardner (33). The TRB paper addressed determining the number and locations of truck study sampling stations. The purpose of the described Wisconsin program is to collect representative trucking characteristic data for use in pavement design, highway cost allocation, motor carrier enforcement, and other planning and research activities. The use of weigh-in-motion technologies and the emphasis on the collection of basic weight data permit random selection of weigh stations and a comprehensive sample of truck traffic. The sampling plan developed relies heavily on user needs and statistical criteria to help ensure a valid and meaningful sample. By using data from the 1980-1981 highway performance monitoring system Wisconsin truck weight case study, the number of required stations is calculated on the basis of the average variability of buck weights in the state. Stations are distributed across recommended road types in proportion to the size of the total population (truck vehicle miles of travel) on each road type. Stations by road type are 42 Appendix A
assigned to counties by using a weighted random procedure. Corridor and specific station locations are designated via application of established criteria. The Minnesota Department of Transportation (34) has operated permanent continuous weigh-in-motion stations since 1 98 1. At present, 1 6 sites are collecting volume and weight data by vehicle type for use in transportation planning and design. Questions that can be answered from an analysis of this data can provide useful information. For example, gross weight trends of big trucks in Minnesota have been speculated on with great interest. Are trucks on the highways getting heavier? With a number of years of accumulated data from the first WIM sites and several years from succeeding locations available, we have the means to answer this question. Typically, 5-axle tractor semi-trailers contribute 60 to 90 percent of the Equivalent Single Axle Load (ESAL) damage on many highways. For example, 5-axle semis in the right eastbound lane of Interstate 494 in Bloomington contributed over 70 percent of the rigid ESALs and about 65 percent of the flexible ESALs in 1 989, yet they totaled just over nine percent of the traffic flow. Similarly, on the U.S. Highway 2 Bemidji Bypass, 5-axle semis, 1 1 percent of the traffic in the right eastbound lane, contributed about 80 percent of all ESALs in ~ 989. Although both weight and volume of trucks are crucial to issues such as pavement damage, safety, etc., a particularly sensitive relationship exists between truck weights and ESALs. For example, a four percent increase in axle weights produces about a 16 percent increase in ESALs. This study analyzed gross weight data of 5-axle semis at five WIM locations. The amount of data available for analysis ("good data") varied from year to year at each site. Three measures, average gross vehicle weight, average gross vehicle weight of all-but-empty trucks, and percentage of trucks operating over legal weight limits, were used to determine weight trends. The data have been developed from tables of gross weight distribution by vehicle type, aggregated by week for each site for a year. All five of the sites were on designated 1 O-ton routes where 80~000 pounds is the maximum allowable gross weight. Two sets of average gross weights of all 5-axle semis were given at each location. Average gross weight of all-but-empty 5-axle semis was also used in this study. 43 Appendix A
The Traffic Monitoring Guide The Federal Highway Adm~nishation's Tragic Monitoring Guide 66) provides a method for states to apply a statistically-based procedure to monitor traffic characteristics such as traffic loadings. The TMG provides demle<] directions for the mon~tonng of traffic charactenstics. Traffic characteristics are those obtained through a coordinated program of Marc counting, vehicle classification, arid truck weighing. Truck Accident Data Programs While not a source of truck weight data, a number of federal agencies, along web states, Me motor carrier ~ndus~y, and highway safely groups madman truck accident data. These data sources may provide useful information in evaluation of truck weight enforcement activities. Therefore, Exhibit II - 5, assembled by TRB's Committee for the Truck Safety Data Needs Study (26) summarizes existing truck accident data programs. SUMMARY OF EXISTING TRUCK ACCIDENT DATA PROGRAMS alms Data Base Agency Frame Features and Strengths Limitations FARS TIFA CARDfile Computerized Motor Carrier Accident Reports (50-T) SAFETYNET NHTSA UMTRI NHTSA NHTSA Office of Motor Camers, PHWA Office of Motor Carriers, FHWA State accident data Individual states NTSB reports NTSB Since 197S Census of fatal crashes; has good Does not include nonfatal crashes; lim- quality control Sincc 1980 Census of fatal truck crashes; rich detail on truck, carrier, and daver; good quality control Sincc 1988@ Based on a probability sample of fatal and nonfatal crashes Sincc 1982 Large sample of fatal and non&- tal crashes Since 1973 Rich details on trucks Since 1990 Census of reported truck crashes (interstate carriers) Census of reported fatal and nonfatal crashes Rich details on contributing factors Exhibit A - 5 44 ited detail on truck and operation Does not include nonfatal crashes Limited detail on truck and operation; based solely on police reports Not based on a probability sample; lim- ited detail on truck and operation; no road class; based solely on police re- ports Lacks data on intrastate carriers; based solely on self-reporting No truck configuration, driver, or crash type; based solely on police reports Data elements and reporting thresholds not uniform among states; h,ls`:lJ s`,l`:l on police rcpl)rts Number of crashes investigated is ex- tremely small and not randomly se- lected Source: TRB Special Report 228 Appendix A
In order to maximize the utility of provided information, data from these sources is structured into components as follows: Monitoring Systems: These systems assemble data on truck accidents and travel on an ongoing basis nationwide. Sufficient details on the vehicle, roadway, region, driver, and accident circumstances are included to allow users to discern significant differences in truck safety trends troth respect to factors relevant to truck safety perfonnance and to spot potential safety problems. Data Systems for Accident-Causation Research and Other Special Studies: These data are needed to answer specific, well-defined research questions. The data may be collected on a one-time basis, or be tailored to meet the needs of individual studies. Management Information Systems: This kind of system provides day-to-day support for agency or company programs that affect safety. Management information systems allow users to identify components that may be inefficient or to redirect resources. The level of detail and kind of information to be collected depend on the particular operations that the data are intended to support. Management information systems should be an integral part of the programs that they are supporting. APPLICABLE DATA-COLLECTION TECHNOLOGIES FOR TRUCK WEIGHT ENFORCEMENT M.O.E. DEVELOPMENT The development of truck weight enforcement M.O.E.s is largely dependent on available technologies for detecting truck weights, classification, axle configuration, and vehicle identification. Three primary technologies for such application are: (1) Weigh-in-Motion (WIM), (2) Automatic Vehicle Identification (AVI), (3) and Automatic Vehicle Classification (AVC). While WIM applications have been frequently documented, all three have been experimentally applied, e.g., Krukar arid Evert (35)~ H.E.L.P.~ Inc. (1994). 45 Appendix A
Primary Technologies Primary technologies designated for truck weight enforcement M.O.E. development are described as follows. Weigh-i~z-Motion ~M) Utilizing WIM systems, truck axle and gross weights of vehicles can be obtained while they are traveling along the highway using in-pavement sensors. Vanous systems are available ranging from slow-speed WIM through a range of full highway speed systems, each with a different level of capability and cost. WIM is now an established technology throughout the world. Various types of WIM systems are as follows. Bending plate systems Bridge systems Capacitive mat systems Deep Pit scales Piezo-electric systems Shallow weigh scales Automuf~c Vehicle Adenoid cation' (A V79 refers to techniques that uniquely identify vehicles, as they pass specific points on the highway. On board transmitters emit a uniquely identifiable signal requiring no action on the part of the driver or an observer. Recent advances in vehicle detection and the processing of data have made AVI application techni cally arid economically feasible. AV! systems consist of three subsystems: a vehicle-mour~ted transponder, a roadside detector, with associated antennas; and a system for the transmission, analysis and storage of data. Applicable technologies comprising these systems are the following. Inductive loops Optical and infrared systems Radio frequency and microwave systems 46 Appendix A
Automatic Vehicle Classifeation (AVC) AVC systems have application in providing vehicle classification information which is widely used in the design, maintenance and management of highway networks. AVC systems consist of the following. Sensors - indicating vehicle presence. Detectors - which receive and condition signals from sensors and then transmit the signals to the processor. Processors - which perform calculations to determine wheel base, number of axles, etc., to determine vehicle classification. Recorders - to store and present data. Limited application of these technologies was noted in the literature. Krukar (35) documented Oregon D.O.T.'s experience with WIM, AVC, and AVI and described: (1) the historical perspective on truck weighing in Oregon, (2) the Oregon experiment with WIM and AVI equipment, (3) present selection criteria, installation and testing, (4) costs and limitations of the present system, (S) WIM/AVI results, and (6) conclusions, recommendations, and future directions. The Heavy Vehicle License Plate (HELP) program comprised the first formal multi-state demonstration of the technologies noted above. This extensive evaluation effort, known as the Crescent Evaluation Team (36), identified various applications of these technologies. The Crescent evaluation concluded that application of the technologies produces the following services which have direct application in the evaluation of truck weight enforcement effectiveness. Roadsidle Dimension and Weight Compliance Clearance - Allows state authorities to check the size and weight of commercial vehicles without stopping them. Benefits include reduced trip time for compliant trucks and more effective enforcement (capture) of non-compliant trucks by the states. 47 Appendix A
Pre-Clearance of Vehicles with Proper Documents - Electronic checking of vehicle documents, by storing the data in a transponder in the vehicle or in state databases that can be quickly checked when the vehicle's identity is automatically determined, could reduce unnecessary vehicle stops, improve enforcement, and reduce trip time for compliant trucks. Government Audit of Carrier Records - Electronic monitoring of vehicles could improve the accuracy and reduce the costs of state audits of: carrier mileage records, number and location of vehicles, Mel tax payments, and certification of fleet maintenance inspections. Government Processing of Commercial Vehicle Operator Documents Electronic administration of documents is both required for other services to be effective (for example, pre-clearance of vehicles with proper documents may require that the documents be electronically filed) and could reduce the time and paperwork currently involved in issu- ing/acquir~ng/certifying permits, credentials, and inspections. The Crescent evaluation included measures of the equipment and system performance (for example, WIM accuracy and availability), operations adequacy (for example, site layout), and adequacy of the applied technologies. A number of states participated in the evaluation. These are: Arizona, California, Colorado, Idaho, Iowa, Minnesota, Nevada, New Mexico, Oregon, Pennsylvania, Utah, Virginia, and Washington. The "Western States Transparent Borders" project, part of a national effort to achieve a more efficient transportation system, is aimed at developing technologies and systems that provide a less expensive and more efficient operating environment for co~runercial vehicle operations (CVO), and ultimately, one which watt allow unimpeded passage of trucks across state boundaries. Goals and objectives of the Transparent Borders project are as follows: "Provide documents for each participating state that describe the current regulatory and administrative organizational frameworks within that state as they relate to the creation of transparent state borders for interstate commercial vehicle operations. 48 Appendix A
Develop, within each participating state, an interagency working group that will guide the implementation of systems and technologies related to the transparent borders concept. These technologies will be designed to improve the efficiency of both governmental agencies and trucking firms operating in the state. Identify the areas where use of IVHS technologies will provide the most significant benefits for each state. Develop working relationships between these groups on an interstate level. Determine a potential course of action for each state to implement IVHS technologies to improve commercial vehicle operations." The Transparent Borders Project final report (37) summarizes the first part of the Transparent Borders Project, a seven-state study to identify the institutional barriers to implementation of various Intelligent Vehicle Highway Systems (IVHS) technologies for CVO. The report describes He current practices within state and federal agencies and organizations that affect CVO in Washington. Documer'!ed Weigh-in-Mofion Application Numerous literature items were cited which describe and evaluate truck weigh-in-motion (WIM). An early NCHRP synthesis (38) described how WIM scales can be used to collect data on truck weights, what uses those data have, and the advantages and disadvantages of using WIM systems to collect the data. The history of WIM development was briefly described, and WIM data needs and uses were reviewed. A subsequent evaluation of low-cost WIM alternatives (39) cited data requirements for pavement and bridge design, truck size and weight enforcement, and the development of adminis- trative policy and legislation. This study was the first to cite current technologies for low-cost WIM systems. One of these, piezoelectric cable, was investigated in a joint research effort with Iowa, Minnesota, Washington, the FHWA and several European countries. A second technology, an inexpensive capacitive weigh~nat WIM sensor and associated electronics, was developed for the 49 Appendix A
FHWA. A third alternative is a reduced cost configuration of the bending plate WIM transducer manufactured and distributed by the PAT Equipment Corporation. Each of these was evaluated in this study to determine its usefulness in providing effective truck weighing devices at a cost that would allow widespread implementation of in-motion truck weighing programs in Texas. A subsequent Texas study (39) was conducted to evaluate piezo film WIM sensor technologies, produce an electronic data collection unit, and integrate the different assemblies with appropriate software to produce a low cost piezoelectr~c film WIM system. Numerous applications of WIM have been applied to instrument highway bridges. One study (40) described the background and history of the bridge weighin-motion system, the personnel training provided, and the operation of the system including bridge selection, traffic control, installation and take-down, calibration, and problems. Results are given regarding the accuracy of the bridge weigh system in three areas: classification, axle spacing and speed, and vehicle axle and gross weights. Enforcement effectiveness is also evaluated. The cost effectiveness of the system was discussed, and conclusions were presented. A number of studies were cited to compare WIM accuracy with permanent truck weighing scales in an attempt to establish the reliability of WIM systems. Two such studies are noted as follows. The first study by Dahlin and Novak (41) analyzed WIM data collected by continuously operating systems at three sites on the same route. The analysis examined the gross weight distribution of 5 axle semis. Truck loading pattern differences were studied for both travel directions on the same route. One observed result of consistent patterns was that, on selected routes where long-hau] loading characteristics (origin-destination, commodities hauled, etc.) are known, data users can confidently apply weight data collected at one location and to predict patterns for another location on that route. A second result is that these repeating patterns make it possible to monitor the calibration of WIM systems. A shift in the weight distribution at one site, while remaining constant at the other two, indicates a possible change in calibration. These changes in calibration are readily observable. The authors conclude that the demonstrated techniques can also be used in analyzing data collected at WIM sites which may be distant from other WIM sites. 50 Appendix A
The majority of current WIM data collection throughout the United States is conducted at SHRP Long-Term Pavement Performance (LPTT) sites. Emerging Technologies Significant emphasis during the conduct of NCHRP Project 20-34 will address future applicable technologies for mon~tonng and communicating collected truck weight/classification data. Therefore, a review of literature was conducted which pertained to IVHS application and telecommunications technology. Intelligent Vehicle Highway Systems (IVHSJ The previous discussion of Crescent-evaluated (H.E.L.P., 1994) AVI and AVC technologies comprised IHVS application. In addition, He Crescent project evaluated an integrated communications system and database. The Crescent computer system enabled data from WIM, AVI, and AVC technologies to be integrated and analyzed. This data link provided various state and motor carrier users with the following services: To enable "one-stop-shopping", the database includes motor carrier credential and permit information, allowing all agencies and states to share the information rather than require motor carriers to acquire documents in each state and agencies to re-enter data. 2. Weigh stations can check credential and permit data from the database for each truck identified by the AVI equipment for pre-clearance of vehicles u ith proper documents. 3. AVI and WIM/AVC data are captured by the database and can be accessed by states and motor carriers, by terminal or hard copy: A. State taxation agencies can use the data to audit carrier records. B. State planning agencies can use traffic volume and weight data for road planning. 51 Appendix A
c Motor carriers can use AVI data for vehicle and dr~ver administration (location, estimated time-of-arrival, time on duty, average speed)." The Transparent Borders project (42) applied AV} and WIM in the design of a continuous data collection program for vehicle classification and weight. Hallenbeck and O'Brien note that Intelligent vehicle-highway system EVES) initiatives offer substantial improvements in the operational efficiency of public agencies that regulate, administer, and interact with commercial vehicle carriers. The IVHS technologies combine with changes in data collection methods, information sharing, and organization to form a new concept, referred to as "transparent borders." The transparent borders concept was developed to: 1. reduce motor carrier costs, 2. reduce regulatory costs for public agencies, improve competitiveness among motor carriers, improve motor carrier safety and compliance, and eliminate unnecessary delays for both public agencies and the motor carrier industry. Hallenbeck and O'Brien also note that although many IVHS technologies are already commercially available, substantial barriers prevent their immediate implementation. These barriers may include the following: I. physical limitations at existing facilities, 2. resource constraints, 3. political concerns (e.g., job security, authority), 4. antiquated computer systems and manual record keeping, and 5. administrative and legislative restrictions on the collection and dissemination of information and money (including privacy issues). Telecommunications Devices The Oregon State Highway Division has developed ax Integrated Tactical Enforcement Network or ITEN. Management has on-line real-time access to field personnel for immediate deployment when and where the need arises based on histograms of truck traffic and violation trends. 52 Appendix A
The district weighmaster supervisor has a master computer which will, upon comrnar~d, dial the various permanent weigh stations and highway monitoring systems in that district. This gives the supervisor real-time access to site data. Using split screens, with the capability of using graphics, the supervisor can obtain information in real-time view mode and past-time histograms on what is occurring at that site with respect to daily and hourly truck volumes, their gross and axle weights, and possible violations. Crews can then be deployed to maximize their enforcement efforts for efficiency and effectiveness. At other remote sites where there are no permanent weigh stations, the supervisor can deploy his portable scale crews to maximize their enforcement efforts. This could be done on an hourly basis and crews could be deployed to meet the changing truck traffic. With the weighmaster being asked to take on additional responsibilities and do more with less, there is a real need to deploy their available human resources efficiently and effectively. Management needs a tool which will help them achieve these goals. Moreover, a wide variety of new maintenance management technologies designed for acquisition, recording, transmission, receipt, and field verification of field data was evaluated under NCHRP contract (43). The evaluated electronic devices applied telecommunications technologies to offer new and better ways to provide accurate and timely information, allow quick transfer of data from field to office and vice versa, and improve the productivity of the maintenance organization. The applied technologies included portable hand-held computers, electronic clipboards with handwriting recognition, bar-code scanners, voice recognition systems, satellite Global Positioning System (GPS), digitized maps, radio frequency transponders, facsimile machines, and telecommunications including regular and cellular telephones. Maryland, Connecticut, and Arizona DOTs all agreed to participate in the development, testing, and evaluation of the technology applications and options. 53 Appendix A
CANDIDATE TRUCK WEIGHT ENFORCEMENT M.O.E. DEVELOPMENT Reviewed literature contained a number of implications for development of candidate truck weight enforcement M.O.E.s. Prior to citing documents which contain implications for specific measures, the related issue of data acquisition requirements is addressed. Reviewed literature is then cited which pertains to overweight truck presence and resulting pavement-wear effects. Following this, candidate M.O.E.s suggested in the state survey are noted. Finally, we note two promising courses for M.O.E. application: the Federal Highway Administration Truck Weight Study, and the Traffic Monitoring Guide (6). Dafa-monitoring method Implicit in the development of M.O.E.s is consideration of the applied methodology required to determine the measures. TRY Special Report 228 (26), Data Requirements for Monitoring Truck Safety, cited methodological needs recommended to monitor truck safety. However, an adaption of this methodology can be specifically geared to truck weight enforcement requirements. Thus, data requirements derived to monitor truck weight enforcement M.O.E.s are as follows. Monitoring Systems: These systems would assemble data on truck volume, classification, and weight on an ongoing statewide basis. Sufficient detail on the vehicle classification, axle loading, ESALs, and Bridge Formula compliance, would be included to allow the state agency to discern significant differences in truck compliance trends with sufficient sensitivity (or statistical confidence) to spot potential pavement damage, bridge structural, or safety problems. 2. Data Systems for Pavement/Bridge Damage and Safety Research: These data are needed to answer specific, well-defined research questions related to deleterious effects of overweight trucks. The data may be collected on a one-time basis, or be tailored to meet the needs of individual studies. Management Information Systems: This kind of system provides day-to-day support for agency programs related to truck weight monitoring/enforcement. The level of detail and 54 Appendix A
kind of information to be collected will depend on the developed M.O.E.s. Management information systems are an integral part of the programs that they are supporting. WIM has obvious and essential application for monitoring truck weight enforcement effectiveness. The primary issue regarding WIM applicability is weight accuracy. Recent research (11,44) has demonstrated improve accuracy with multiple sensors. Recent WIM system cost estimates (44) indicate that dual piezoelectr~c sensor systems cart be installed for $9,500 per lane. Four-year life cycles were estimated with a 25% sensor failure rate at the end of three years. Sensor replacement cost is $2,000. Canc~idate M.O.E. Development A number of documents were cited in the literature review which give rise to consideration of specific candidate M.O.E. concepts. Excessive Truck Weight Due to the fact that pavements are designed to withstand specific loading during their lifetime, overweight trucks are a critical factor in pavement deteriora- tion. Literature previously cited in this review have elaborated on this point. For example, Gillespie (11) studied the mechanics of truck-pavement interaction to identify relationships between truck properties and damage (fatigue and rutting). Stein (5) documented excessive truck weights in the traffic stream as follows. I. Forty percent of the ESALs observed on the Wisconsin Rural Interstate System were attributable to excess axle loadings. Data indicated that ~ O to ~ 5 percent of trucks were potential violators. (It was not possible in effort this to discern overweight violators from overweight permitted trucks.) 3. Due to this presence of observed overweight trucks, Stein recommended that Weigh-In- Motion data be utilized as a tool for prioritizing weight enforcement efforts. While Pavement Management Systems do contain information which may be useful for M.O.E. application, their applicability to the development of truck weight M.O.E.s is limited. Research by Hallenbeck and Kim (45) has demonstrated that states' current application of Pavement 55 Appendix A
Management Systems are not sensitive to truck weight. The Transparent Borders project team examined nine states' pavement management systems. These states included: Arizona, Arkansas, California, Florida, Idaho, Minnesota, Nevada, Ohio, and Washington. In all of these states, some measure of traffic was used in the pavement management system. However, in none of these systems did truck volumes or an estimate of actual equivalent single axle loads (ESAL) play a leading role in the determination of expected pavement deterioration rates or pavement rehabilitation prioritization. The Transparent Borders project indicated that expected pavement life was predicted in years, not ESALs, and was usually a predetermined function based on standard deterioration curves adjusted (in some cases) to reflect actual pavement performance. In none of the examined PMS were the deterioration rates based directly on ESAL estimates measured on individual road segments. The Transparent Borders Project literature review demonstrated that traffic and/or truck volume estimates were used only peripherally in pavement management systems. Application of traffic measures served to categorize the expected deterioration rate (e.g., high, medium, or low rates of deterioration). However, in no reviewed case was the pavement management system sensitive to expected ESAL loading changes based on monitoring of actually applied loads or traffic volumes. The use of pavement condition to determine expected pavement life within the structure of PMSs, rather Han the use of cumulative ESALs, was in part due to the lack of valid Buck data available when time these PMSs were implemented. Deterioration rates were used partly because the PMSs lacked accurate loading data and partly because the use of actual deterioration rates allowed the PMS to account for a variety of causes of pavement deterioration (e.g., poor quality construction). However, the study demonstrated the critical impact of truck weight in terms of ESALs as it affects pavement deterioration. A frequent cause of "premature" pavement failure was found to be significant underesti- mation of actual level of traffic loading. The underestimated load results in a pavement that actually meets its design life in ESALs but fails prematurely in terms of the number of years it lasts. For example, if a pavement is designed to withstand 1 million ESALs per year for 7 years, but actually receives 2 million ESALs per year in loads, the pavement will fail in 3.5 years. The perception is 56 Appendix A
that the pavement failed prematurely, when in actuality, the pavement met its design criterion (7 million ESALs). Thus, Transparent Borders project underscored the need for truck weights, preferably in ESALs, to be applied as an estimate of pavement wear due to excessive truck weight. Pavement Distress index Grivas et. al. (46) presented a methodology for determining a pavement distress index (PDI) needed for pavement management purposes. The authors concluded that the developed index is a viable single measure of pavement surface condition useful for pavement management purposes. Pavement Distress Index formulation is based on two types of information, namely, (a) individual distress ratings along nominal lengths of pavement, and (b) a set of weighing values associated with the various distress types and severity-extent combinations. The PDI is used as a condition measure in various other analytical methodologies within the pavement management system. Application of the PD] has been practiced by the New York State Thruway Authority. A usefi~1 application of pavement distress in developing a potential truck weight enforcement M.O.E. was documented in Virginia by McGhee (29). This study incorporated the AASHTO pavement distress function, g, related to Equivalent Single Axle Loadings in the Exhibit A - 6 plot shown on the next page. This straight line function intercepts the horizontal axis at C, the point at pavement distress is said to occur. A possible confounding factor in application of a pavement distress function as a truck weight enforcement M.O.E. is unreliability of pavement deformation due to variations in properties of materials. This factor will be investigated in the Task 5 M.O.E. evaluation study. Pavement Roughness While pavement roughness Carl be considered as a candidate M.O.E., McGhee (29) that, due to the generally good ride quality and low pavement roughness associated with Virginia highways, that pavement roughness is not useful in prioritizing pavement rehabilitation projects. Therefore, the sensitivity of this measure to overweight truck traffic must be carefully evaluated. 57 Appendix A
To : 04 o ~ log A _ ~ log ESAL Di stare s s f unct ion vs . Exhibit A - 6 tr2~f ic . Source: McGhee, 1984 Ride Qualify AASHTO (47) reports that one ofthe major accomplishments of Weir 1956 1 960 Road Test to develop a concept for evaluating the performance of a pavement. Ride quality was used as a measure of how well pavements could serve the public. Studies made, after completion of the Road Test, have consistently indicated that ride quality can be correlated to pavement roughness. It has also been shown that roughness is not only a measure of user satisfaction (or dissatisfaction), but can also be related to user costs; i.e., vehicle operating costs and speed profiles. The report notes that road roughness should be considered as a fundamental requirement for a pavement management system. There are a wide range of methods of measurement to evaluate road roughness, either subjectively (ride quality) or objectively (roughness). For state highway administrations the use of automated measuring devices to measure and record roughness is considered preferable to subjective ratings. Local government agencies, which do not have access 58 Appendix A
to automated devices, have found subjective estimates of ride quality to be a useful measure of functional performance. Methods for measuring roughness and interpreting roughness vary and are constantly changing as both equipment and analytical capabilities improve. Both response type roughometers, designed to measure vertical movement between the axle and frame of a vehicle (or trailer) and profilometers, designed to measure the longitudinal profile, have been used to evaluate roughness. Within any particular agency, any of the response or profilometric equipment can be used. The pros and cons of each need to be carefully considered since the reliability of the measurement and utility of the data (correlation to ride quality) will vary. For comparison between agencies, the conversion to the International Roughness Index (IRI) could be considered as a useful means of summarizing roughness measurements (101. Physica/ Distress AASHTO (47) reported that physical distress is a measure of the road surface deterioration caused by traffic, environment and aging. There are no national standards for procedures to be followed or equipment to be used for identifying pavement distress. It is, however, acknowledged that the type and cost of maintenance, rehabilitation and reconstruction will be significantly influenced by the type, extent and severity of distress. The types of distress Carl generally be categorized into three classes: fracture (cracking), distortion (rutting, corrugations, faulting), or surface wear or deterioration (raveling, spelling). Specific descriptions of distress related to asphaltic or Portland cement concrete pavements may vary depending on the types of distress encountered in a particular area. Methods for evaluating distress can vary widely, ranging from "windshield" surveys from a moving vehicle to automated equipment designs to measure and record distress in a prescribed way. The choice of method should be made as an integral part of the PMS development. The primary factors to consider are: applicability, cost, productivity, quality and quantity of the information obtained. The most important of these considerations are applicability, quality and 59 Appendix A
quantity. For example, is there a sufficient amount of the right kind of information and does the information represent field conditions? Currenf/y Applied M.O.E.s The survey of states, conducted as part of the NC~P 20-34 effort, revealed little application of truck enforcement M.O.E.s. Twenty-three surveys were returned from state enforcement agencies, and 36 were returned from state highway planning agencies. Appendices B arid C, respectively, to this report provide response summaries for the enforcement and planning questionnaires. Bold face appendix entries on questionnaires display both the number of agency responses and the corresponding percentage of the nationwide sample. Responses are indicated in the appendices as follows. ..} Does your state conduct an on-going truck Weigh-In-Motion (WIM) program? Yes IS (36%) No ~ (10%~" The above example signifies that IS responding enforcement agencies (or 36.0 percent of all · ~ sampled agencies) conduct on-going WIM truck weighing activity. The state survey queried M.O.E. information both from state enforcement agencies and state highway planning agencies. M.O.E.s Suggested by Stale Enforcemenf Agencies Exhibit A -6 lists state truck weight enforcement agency responses to question numbers 6 and 7, stated as follows. ..~ a. What measures (e.g., reduction in the number, proportion, and severity of overweight trucks) are currently applied to evaluate truck weight enforcement effectiveness? Please explain if not included in documentation. 7. What measures (e.g., reduction in the number, proportion, and severity of overweight trucks) are DIanned for fixture application to evaluate Duck weight enforcement effectiveness ? Please explain." 60 Appendix A
Arkansas None. Colorado Vehicle Compliance Ratios. Georgia None. Idaho Illinois Iowa Kansas None. Michigan None. Montana None. Nebraska None. 1. Severity of overloads 2. Proportion of enforcement action v. number weighed Suggested Relevant Evidence helpful, but would likely not pass legislation. Monthly activity reports are compared to proposed goals Weight Enforcement plan submitted to FlIWA. New Jersey Total overweight compliance; monthly comparison with previous year. New York No current. Planned monthly statistics re: vehicles weighed, dangerously overloaded vehicles. North Carolina Oklahoma None. No current. Plans for: (1) severity of overweight trucks, (2) reduction in violations. Oregon 1. Truck Weighings, annual count 2. Statewide average weight violation trends, by roadway classification. 3. Legalizations, by type (cargo shift, off-load) Pennsylvania Truck volume, amount overweight, trip distance. Virginia Did not complete questionnaire, due to current transition in enforcement procedures. Washing- Compliance ratio, severity of violation, WIM monitoring. ton Wyoming Routine weight monitoring Exhibit A - 6. Candidate Truck Weight Enforcement M.O.E.s M.O.E.s reported by State Enforcement Agencies 61 Appendix A
Of the responding states, nine indicated some applied or planned measure(s) of truck weight enforcement effectiveness. These are listed below. I. Severity of violation. Four states. 2. Vehicle Compliance Ratios, i.e., the number of citations as a proportion of total number of weighed vehicles. Three states. 3. Routine weight or WIM monitoring. Three states. 4. Reduction in violations. 5. Truck Weighings, annual count 6. Statewide average weight violation trends, by roadway classification. 7. Legalizations, by type (cargo shift, off-load) 8. Comparison of monthly activity to FHWA enforcement plan goals 9. Relevant Evidence findings Despite the fact that an introductory letter explaining the nature of the project was sent to state enforcement agencies, it is nevertheless obvious from the above list that certain of the suggested candidate M.O.E.s miss the point of determining what is actually accomplished by the enforcement effort rather than merely indicating a level of enforcement effort. M.O.E.s Based on Paveme'2~/Bridge/Safe~ Management Systems In order to assist in the development of candidate M.O.E.s the state survey asked the following question of state highway planning agencies. Exhibit A - 7 lists responses from 36 states. 't7. What measures are gathered (or planned for fixture data collection) in your state's Pavement/Br~dge Management System? If convenient, enclose appro- priate documentation portions." Responses shown in the exhibit contain measures shown in the literature review to be considered as candidate M.O.E.s. 62 Appendix A
Alabama AADT, Percent Commercial Vehicles, Truck Weight Arkansas None at this time. Arizona None reported Colorado Pavement - Traffic, Rut depth, Cracking, Skid, GPR, Weight Bndge - Traffic, NBI, Weight, PONTIS (System aid to optimization of budgets and programs) Connect icutt Overload permit records anticipated in PMS Florida Final decision on variables not determined, as yet Georgia None yet Illinois Extensive list of geometric and locational data provided Kentucky Traffic volume, classification, ESALs at 64 counting stations Kansas . · . Loulslana Pavement - Portable WIM data Bridge- SHRP data None provided Iowa ESALs at 18 sites; volume, classification, speed at 24 sites; volume, speed at 43 sites. Maryland None reported. Michigan 90 TMG WIM and 30 SHRP sites. M in n eso ta Volumes, ve hicl e classified lions, ESALs, ro adw ay a nd st ructure inf orma lion, co n dit lo n ra ti ngs, etc. Nebraska None reported. Nevada None reported. New Hamosh~re IRI for pavements; 15 WIM sites Exhibit A- 8 Measures available from Pavement Management Systems Reported by State Highway Agencies 63 Appendix A
Application of FHWA's Truck Weight Study As has been noted in this review, many states collect massive WIM data from relatively unobtrusive WIM stations for the purpose of monitoring pavement performance. The Federal Highway Administration has developed software and distributed it to states to the purpose of reducing and analyzing the WIM data. Data from approximately one-half of the states is maintained in files stored at the FHWA. Summary data obtained from this source can potential be applied to monitor long-term truck weight enforcement effectiveness. App/icat~on of Traffic Monitoring Guide (TMG) Variables Cottrell (25) developed a sampling plan involving the systematic deployment of portable WIM devices at TMG sites. Courell concluded that use of the TMG and WIM systems together provide improved monitoring of truck weight sampling procedure using the TMG and WIM systems. Four alternatives from the TMG that were based on differentschemes for multiple measurements at permanent WIM sites were evaluated. A Suck weight sampling plan was developed for the preferred alternative. Truck weight sampling sites, data collection procedures, cost and resources estimates, data from permanent WIM sites, and data management information are included in the plan. REFERENCES I. General Accounting Office, "Excessive Truck Weight: An Expensive Burden We Can No Longer Support--Questionnaire Summary." Washington, D.C. (1979) 2. Downs, Hugh G., "Criteria for Evaluation of Truck Weight Enforcement Programs. " NCHRP Synthesis of Highway Practice 82. Transportation Research Board (1981) I. Paxson, D.S., "Value of Overweighing to Intercity Truckers." Transportation Research Record 889 Transportation Research Board (1982) Bisson, B.G. and Gould, D.~., "Methodology for Evaluation of Truck Weight Regulation Enforcement Programs." Transportation Research Record 1249 Transportation Research Board (1989) 5. Stein, Paul P., et al., "The Overweight Truck in Wisconsin: Its Impact on Highway Design, Maintenance and Enforcement Planning." Wisconsin Department of Transportation (1988) 64 Appendix A
6. Federal Highway A~ninistration, The Tragic Monitoring Guide, Office of Information Management, Department of Transportation, Washington, DC (1995) 7. Hazen, Philip I., "Getting Better Truck Flows and Loads: Truck Weight Case Study." Presentation at 73rd TRB annual meeting Transportation Research Board (! 994) 8. Bairns, Richard T., "Analysis of Pavement Damage Attributable to Overweight Trucks In New Jersey." New Jersey Department of Transportation (! 984) 9. Transportation Research Board, "Truck Weight Limits: Issues and Options." Special Report 225, Transportation Research Board ~990) 10. Luhr, David R. and Fernando, Emmanuel G., "A Microcomputer Procedure to Analyze Axle Load Limits and Pavement Damage Responsibility." Transportation Research Board (~ ~ 987) I. Gillespie, T.D., et al., "Effects of Heavy-Vehicle Characteristics on Pavement Response and Performance." National Cooperative Highway Research Program (1993) 12. Deacon, ].A. Pavement Wear Elects of Turner Trucks, TRB, National Research Council, Washington, DC (1988) 13. Campbell, K.~. et. al Analysis of Accident Rates of Heavy Duty Vehicles, Final Report, University of Michigan Transportation Research Institute. (1988) 14. Fancher, P.S. et. al Turner Truck Handling and Stability Properties Affecting Safety, University of Michigan Transportation Research Institute (1989) 0 15. O'Day, J. and Kostyniuk, L.P. Large Trucks in Urbar1 Areas: A Safety Problem. Jounal of Transportation Engineering, ASCE, Vol. III No. 3 (1985) 16. MacKay, M. and Walton, A. Heavy Commercial Vehicle Design and Other Road Users 28th Proceedings of the American Association of Automotive Medicine, Arlington, IL (1984) 17. Kohne, Jodi; Sheibe, Robert R.; and Hallenbeck, Mark, "Western States Transparent Borders Project: Description of Current Practices--Idaho." Washington State Transportation Center (1993) 1 8. Transportation Research Board, "Motor Vehicle Size and Weight Regulations, Enforcement, and Pennit Operations." Washington, D.C. (1980) 65 Appendix A
19. Walton, C.M. and Yu, C., "An Assessment of the Enforcement of Truck Size and Weight Limitations in Texas." Texas University (1983) 20. Krukar, Milan and Evert, Ken, "Finding from Five Years of Operating Oregon's Automated Woodburn Port-of-Entry." Paper presented at 73rd Annual Meeting, Transportation Research Board (1994) 21. Krukar, Milan and Evert, Ken, "Integrated Tactical Enforcement Network." State Highway Division, Oregon Dept. of Transportation ( 1990) 22. Wyatt, J. J. and Hassan, M.U., "Some Tentative findings About the Effect of Level of Enforcement on Compliance With Truck Weight Regulations." Roads and Transportation Association of Canada (! 985) 23. Hildenbrand, M.D.; Prentice, B.E., and I. Lipnowski, "Enforcement of Highway Weight Regulations: A Game Theoretic Model." Transportation Research Forum (1990) 24. Stein, Paul P., et al., "The Overweight Truck in Wisconsin: Its Impact on Highway Design, Maintenance and Enforcement Planning." Wisconsin Department of Transportation (1988) 24. Cottrell, B. H., Jr., "Using the 'Traffic Monitoring Guide' to Develop a Truck Weight Sampling Procedure for Use in Virginia. Final Report." Virginia Transportation Research Council (! 992) 26. Transportation Research Board, Committee for the Truck Safety Data Needs Study, "Data Requirements for Monitoring Truck Safety." Washington, D.C. (1990) 27. Novak, Edwin C., Jr. and Kuo, Wen-Hou, "Life-Cycle Cost Versus Network Analysis." Transportation Research Board (} 992) 28. Wei, C.H. and Schonfeld, P., "The Combined Costs of Highway Maintenance and Traffic Operations, Final Report." Marylandt Department of Transportation (1 992) 28. McGhee, K.H., "Development of a Pavement Management System for Virginia--Final Report on Phase I--Application arid Verification of a Pilot Pavement Condition Inventory for Virginia Interstate Flexible Pavements." VA Highway & Transportation Research Council (1984) 29. American Association of State Highway & Transportation Office, "Guidelines for Bridge Management Systems." Washington, D.C. (1993) 30. Shirole, A.M.; Winkler, WJ.; and Fitzpatrick, M.W., "Bridge Management Decision Support." Transportation Research Board (1993) 66 Appendix A
32. Oravec, J.D., "Case Study: PENNDOT's Bridge Management Decision Support Process." Transportation Research Board (1993) 33. Gardner, WD, "Truck Weight Study Sampling Plan in Wisconsin." Transportation Research Board (} 983) 34. Krukar, M., "The Oregon Weigh-in-Motion/Automatic Vehicle Identification Project (Coordination Weight Monitoring and Enforcement Program Demonstration Project Using WIM/AV! Equipment). Final Report." Oregon Department of Transportation (1986) 35. The Crescent Evaluation Team, "The Crescent Project: An Evaluation of an Element of the Help Program." Heavy Vehicle Electronic License Plate, Zinc., Phoenix, AZ (1994) 36. "Transparent Borders Project." TRAC Research Review (! 993) 38. Use of Weigh-in-motion Systems for Data Collection and Enforcement, Synthesis of Highway Practice 124, Transportation Research Board, Washington, DC, (1986) 39. Cunagin, W.D.; MajUi S.O., arid Yeom, H.Y., "Development of Low Cost Piezoelectric Film WIM System, Final Report." Texas Transportation Institute (! 991~ 40. Maryland Department of Transportation, "Evaluation ofthe Bridge Weigh-in-Motion System." Brooklan~ville, MD (no date) 41. Dahlin, Curtis and Novak, Mark, "Comparison of Weight Data Collected at Weigh-in-Motion (WIM) Systems Located on the Same Route." Transportation Research Board fI994) 42. Hallenbeck, Mark E. and O'Bnen, Amy I., "Truck Flows and Loads for Pavement Management." Washington State Transportation Center (1994) 43. Hymnal, W. A.; Alfelor R.M.; and Alexander, T.M., "Field Demonstrations of Advanced Acquisition Technology for Maintenance Management." National Cooperative Highway Research Program (1993) 44. Taylor, Brian and Bergan, Art The Use of Dual Weighing (Double ThreshoicI) to Improve the Accuracy of WIM Systems ant! the Effect on Weight Station Sorting, International Road Dynamics, Saskatoon, Saskatchwan (1993) 45. Hallenbeck, Mark E. and Kim, Soon-Gwam, "Final Technical Report for Task A: Truck Loads and Flows." Washington State Transportation Center (! 993 67 Appendix A
46. Grivas, D.A.; Schultz, B.C.; and Waite, C.A., "Determination of Pavement Distress Index for Pavement Management." Transportation Research Board (1992) 47. American Association of State and Highway Transportation Officials, Guidle1tines for Pavement Management Systems, July 1990 68 ~ . Appendix A
