Gross Vehicle Weight Research Articles

The influence of gross vehicle weight (GVW) and transport distance on timber trucking performance indicators – Discrete event simulation case study in Central Finland

ABSTRACT Today, timber trucks of gross vehicle weight (GVW) up to 76 tonnes are allowed to operate on Finnish roads from roadside landings to mills. Reducing trucking costs and exhaust gas emissions have been the dominant reasons for the increased GVWs of timber trucks. A discrete-event simulation (DES) method was used to compare the impact of the truck and payload size, trucking distance, and timber assortment lengths on trucking performance indicators (e.g., productivity, energy efficiency, and costs of trucking) in the procurement area of a case logistic company operating in Central Finland. The studied truck sizes were 68, 76 and 84 t, of which the 76-t trucks dominate timber trucking in Finland. Over a transport distance of approx. 105 km with an average assortment length of 4.2 m, 76-t trucks had 9% higher and 12% lower productivity (m3/100 km), 1% lower and 4% higher fuel consumption (l/m3) and 4% lower and 6% higher trucking cost (€/m3) compared to 68- and 84-tonner options, respectively. The improvement in regards to previous indicators was clearly bigger for the 76-tonner than the 68-tonner if the trucked wood assortments were lengthened to 5.0 m. The differences in cost and fuel efficiency as well as annual trucking volumes were increased as a function of the trucking distance, when comparing the truck configurations with different GVWs and payloads. To conclude, the tendency of the size increase in GVWs in timber trucking in Finland can be justified in light of the study results.

Non-Linear Analysis of a Two Post Roll Over Protective Structure for Motor Grader

Roll over protective structure (ROPS) is a critical passive safety system of any off-highway equipment. The ROPS is one of the mandatory DGMS requirements and structure is expected to withstand the impact force and maintains the safe space for operator survival during rollover accident. In the present research work, attempts are made to study the non-linear behavior of a two-post roll over protective structure of motor grader having 25T Gross Vehicle Weight (GVW) by using Finite Element Analysis (FEA). In order to enhance the energy absorbing capacity and to have better performance of ROP structure, an interweave energy absorber was introduced inside the ROPS column. CAD model of ROPS was made by using Pro-E modeling software and non-liner analysis was carried by using LS-Dyna software. Non-linear analysis used to compute the maximum deformation and von-misses stress and energy absorption with respect to the lateral, vertical and longitudinal load. Non-linear analysis was carried out for each load case and studied the behavior of ROPS structure. Among all the load conditions, the lateral impact load is a vital role with respect to the energy absorption criteria. The result of non-linear analysis is appreciably par with the standard ISO: 3471(2008) E ROPS performance.

Non-Linear Analysis of a Two Post Roll-Over Protective Structure for Motor Grader

Roll over protective structure (ROPS) is a critical passive safety system of any off-highway equipment. The ROPS is one of the mandatory DGMS requirements and structure is expected to withstand the impact force and maintains the safe space for operator survival during rollover accident. In the present research work, attempts are made to study the non-linear behavior of a two-post roll over protective structure of motor grader having 25T Gross Vehicle Weight (GVW) by using Finite Element Analysis (FEA). In order to enhance the energy absorbing capacity and to have better performance of ROP structure, an interweave energy absorber was introduced inside the ROPS column. CAD model of ROPS was made by using Pro-E modeling software and non-liner analysis was carried by using LS-Dyna software. Non-linear analysis used to compute the maximum deformation and von-misses stress and energy absorption with respect to the lateral, vertical and longitudinal load. Non-linear analysis was carried out for each load case and studied the behavior of ROPS structure. Among all the load conditions, the lateral impact load is a vital role with respect to the energy absorption criteria. The result of non-linear analysis is appreciably par with the standard ISO: 3471(2008) E ROPS performance.

Field Characterization of Pavement Materials using Falling Weight Deflectometer and Sensor Data from an Instrumented Pavement Section

This study deals with the backcalculation of the mechanical properties of pavement layers using not only the falling weight deflectometer (FWD) sensor data but also pavement response under that FWD load from the embedded sensors in an instrumentation section. To perform the backcalculation, a layered viscoelastic pavement model incorporating asphalt concrete (AC) cross-anisotropy is developed as the forward model. Field degree of cross-anisotropy in AC is determined at the maximum magnitude frequency obtained through continuous wavelet transform of the material response signal. The material response signal is obtained from the deconvolution between the loading signal and the signal registered at the embedded sensors. An inverse analysis methodology is also developed to calculate the gross vehicle weight (GVW) of any vehicle passing through the instrumentation section using only the backcalculated material properties and pavement responses. From the results, it is observed that inclusion of the AC cross-anisotropy reduces the error norm, and a good agreement is observed with the laboratory dynamic modulus in both horizontal and vertical directions. It is also observed that the maximum magnitude frequency of material response and degree of cross-anisotropy in AC both decrease with an increase in average AC temperature. Furthermore, using the backcalculated material properties and pavement responses, it is possible to determine the GVW with 95% accuracy.

A Monte-Carlo Simulation for the Estimation of Side-by-Side Loading Events on Oregon Bridges

Obtaining the side-by-side probabilities accurately is a very important procedure during two lane loaded live load factor analysis. To calculate the load factors properly, side-by-side loading events should be investigated very carefully. This study presents a statistical method to investigate the side-by-side events on the Oregon bridges. Numerical simulations were performed for this investigation. These simulations were developed in MATLAB. Gross vehicle weights (GVW) of the trucks were used during the analysis. Monte Carlo simulations were performed to analyze side-by-side loading events. Degree of correlation coefficient of GVW for side-by-side trucks were also obtained from Monte Carlo simulations. 290 bridges located at the prescribed mile markers on Interstate-5 (I-5) southbound on Oregon highways and 1-year of Oregon state-specific weigh-in-motion (WIM) data were used. 75,000 trucks were randomly selected from 1,787,612 trucks that correspond to 1-year WIM data from Woodburn NB traffic site that is located in Oregon. Inverse standard normal distribution functions and cumulative distribution functions of the truck data were generated. With respect to the statistical analysis, side-by-side loading probabilities were found to be smaller than the ones presented in American Association of State Highway and Transportation Officials LRFD calibration.

Impact on rutting from introduction of increased axle loads in Finland

ABSTRACT In 2013, Finland introduced legislation increasing gross vehicle weights (GVW) on a number of trucks. Since the actual impact on road damage is nearly impossible to quantify in advance, the present analysis of road surface measurements is intended to provide knowledge regarding the impact on road damage. Rutting is influenced by many conflated phenomena. To indicate and capture the effect on road damage due to the new maximum GVW for certain truck- and trailer combinations, the analysis follows two different but mutually supporting lines of reasoning, empirical and theoretical, respectively. Analysis of measured rut depth is supported by theoretical calculations. Theoretical findings clearly indicate that the relative increase in road damage induced by higher GVW is larger than the increase in relative payload capacity. There was a rapid fleet shift towards heavier trucks after 2013, and statistical (empirical) analysis of road surface measurements shows an increase in rutting after this introduction.

Using Statistical Analysis of an Acceleration-Based Bridge Weigh-In-Motion System for Damage Detection

This paper develops a novel method of bridge damage detection using statistical analysis of data from an acceleration-based bridge weigh-in-motion (BWIM) system. Bridge dynamic analysis using a vehicle-bridge interaction model is carried out to obtain bridge accelerations, and the BWIM concept is applied to infer the vehicle axle weights. A large volume of traffic data tends to remain consistent (e.g., most frequent gross vehicle weight (GVW) of 3-axle trucks); therefore, the statistical properties of inferred vehicle weights are used to develop a bridge damage detection technique. Global change of bridge stiffness due to a change in the elastic modulus of concrete is used as a proxy of bridge damage. This approach has the advantage of overcoming the variability in acceleration signals due to the wide variety of source excitations/vehicles—data from a large number of different vehicles can be easily combined in the form of inferred vehicle weight. One year of experimental data from a short-span reinforced concrete bridge in Slovenia is used to assess the effectiveness of the new approach. Although the acceleration-based BWIM system is inaccurate for finding vehicle axle-weights, it is found to be effective in detecting damage using statistical analysis. It is shown through simulation as well as by experimental analysis that a significant change in the statistical properties of the inferred BWIM data results from changes in the bridge condition.

NOx Emissions from Euro 5 and Euro 6 Heavy-Duty Diesel Vehicles under Real Driving Conditions

Despite the strengthening of vehicle emissions standards and test methods, nitrogen oxide (NOx) emissions from on-road mobile sources are not being notably reduced. The introduction of real driving emission (RDE) regulations is expected to reduce the discrepancy between emission regulations and actual air pollution. To analyze the effects of RDE regulations on heavy-duty diesel vehicles, pollutants emitted while driving were measured using a portable emission measurement system (PEMS) for Euro 5 and Euro 6 vehicles, which were produced before and after RDE regulations, respectively. NOx emissions were compared as a function of emissions allowance standards, gross vehicle weight (GVW), average vehicle speed, and ambient temperature. NOx emissions from Euro 6 vehicles were found to be low, regardless of GVW; emissions from both vehicular categories increased with a decline in the average speed. To reflect real road driving characteristics more broadly in the RDE test method for heavy-duty vehicles, it is necessary to consider engine power, which is a criterion for classifying effective sections, in the moving average window (MAW) analysis method, as well as including cold start conditions.

WIM-based vehicle load models for urban highway bridge

With the rapid development of China's economy, many long-span bridges have been built and put into service. Vehicle load has been changing year by year in terms of the gross vehicle weight (GVW), the wheelbase and the traffic volume, especially the overload of heavy vehicles, which is a major challenge to the safety and durability of bridges. It is necessary to establish the vehicle load model through the measured traffic data for actual traffic conditions of the given bridge. In this study, the weigh-in-motion (WIM) data collected from an operational long-span urban highway bridge located in Wuhan, China, were used to analyze the statistical characteristics of vehicle loads. On the basis of the types of vehicles, (1) Considering the double or multimodal Gauss distribution characteristics of the GVW, the expectation maximization (EM) algorithm was used to estimate the statistical parameters of the Gauss distribution; (2) The generalized extreme value distribution (GEV) was used to develop the statistical model of the vehicle load extreme value; (3) The vehicle load extreme values in the design reference period of the urban highway bridge were estimated by the extreme value type I distribution; (4) According to the axle weight and the axle spacing, a statistical fatigue vehicle load model for the small and medium span urban highway bridges located in Wuhan, China was presented based on the Miner linear accumulated damage hypothesis and the effective fatigue damage principle.

Analysis and optimization of mono parabolic leaf spring material using ANSYS

This research paper describes the work carried out on a mono parabolic leaf spring of a mini loader truck (Tata Ace) with a GVW (gross vehicle weight) of 1550 kg. A leaf spring is simple form of spring, pervasively used for the suspension in automotives. In this paper analysis is done for leaf spring whose thickness varies from the centre to outer end in parabolic nature followed by mathematical equation of a parabola, hence it is named as parabolic leaf spring (PLS). The modeling and analysis of the leaf spring has done in CATIA V5 R20 and ANSYS 15. The finite element analysis of the leaf spring has been carried out by initially discretising the model and then applying the relevant boundary conditions under the static loading conditions. The results from FEA indicated that the red area close to shackle was undergoing maximum value of stress which may lead to failure of mono parabolic leaf spring. A comparison between the different materials of leaf spring has also been performed to study the influence of mechanical properties of different material of PLS, in order to find out the amount of maximum stress for different material. During the analysis of all the materials boundary condition and applied load are same.

Impact on pavement deterioration due to overload vehicle regulation in Brazil

The investments required to maintain pavement conditions during its life-cycle are directly connected to the fleet weigh spectrum. Recently, Brazilian authorities have agreed on increasing trucks overloading enforcement tolerance – from a 7.5% maximum overweight per axle to 10%, despite maintaining the gross vehicle weight (GVW) to a maximum of 5%; this allowed heavier axles and, therefore, increased road owner cost to maintain functional parameters within expected limits. To evaluate the impact of the observed overload on pavement deterioration and, specifically, due to the new regulation, an assessment on the pavement’s life cycle alteration was carried out using the traffic load spectrum obtained during the year of 2017 in a weighting station located on the BR-116 (Rio Grande do Sul State). The HDM-4 models were applied in order to obtain the pavement deterioration and to conduct an economic evaluation for a 30-year life-cycle cost analysis considering four scenarios: (i) no overload tolerance; (ii) new overload regulation – 10% tolerance enforced on the axle-load weight limits; (iii) actual axle-loads spectrum – including overloaded axles. The scenario with the actual axle-loads resulted in a considerable impact in the LCCA in terms of Net Present Value (NPV), what reinforces the need of a better inspection of vehicle loads in order to preserve the pavement investments.

Reliability Assessment of Steel Bridges for Specialized Hauling Vehicles

Specialized hauling vehicles (SHVs) are short heavy trucks within the legal weight limits but induce higher load effects than routine commercial loads. The Manual for Bridge Evaluation (MBE) adopted a series of single-unit trucks (SUs) to represent this type of vehicle. However, the SUs were introduced without rigorous reliability-based analysis due to the lack of data on SHVs. With the availability of vast amounts of data on weigh-in-motion (WIM) truck weights and configurations, the reliability of steel bridges under the SHVs should be evaluated in a more robust and quantitative manner. Through the utilization of WIM data, the authors quantified the SHVs in terms of percentages of SHVs among all truck traffic, daily average counts of SHVs, and number of axles. The gross vehicle weights (GVWs) and typical configurations of SHVs were investigated. In addition, their load effects were determined and normalized by the corresponding SUs. The maximum live loads corresponding to a return period of 5 years were also extrapolated using normal probability paper (NPP). To evaluate the effectiveness of current load-rating procedures for SHVs, the authors investigated the relationship between the load-rating factors and the corresponding reliability indices for existing bridges using the developed live load parameters based on the WIM data. Results indicated that the current live load factors were not able to provide a uniform and appropriate reliability index at different average daily truck traffic (ADTT) scenarios. This paper thus proposes new live load factors and weight adjustments of SU trucks to provide an adequate and uniform safety margin for the evaluation of steel bridges.

Multi-parameter Dynamic Traffic Flow Simulation and Vehicle Load Effect Analysis based on Probability and Random Theory

In order to evaluate the vehicle load adaptability of existing highway bridge at the operational stage, and provide a reference for the strategy of reinforcement and maintenance, a new model of multi-parameter traffic load flow simulation and vehicle load effect (VLE) analysis is proposed. In this paper, static traffic flow data was collected by weight in motion (WIM) system, and the characteristics of static traffic flow, such as gross vehicle weight (GVW), vehicle gap distance (VGD), wheelbase and the proportion of axle weight distribution (PAWD), was analyzed in different lanes. The program run by MATLAB was used to conduct the Monte-Carlo method on all kinds of traffic data collected and to generate the multi-parameter dynamic random traffic flow (DRTF) data. By loading DRTF data onto the influence line of the sample bridges (simply supported integral bridges of 20 m to 40 m), the maximum VLE under DRTF could be calculated and compared with the static VLE of Chinese current design code. The results showed that the fitting of GVW distribution should be used a skewed distribution or a kurtosis distribution. And under current daily traffic volume (DTV), the service condition of highway bridges can meet the requirement of traffic load. However, in the driveway of some heavy trucks, the VLE is greater than the value suggested in the current design code, which may cause partial damage to the bridge.

The effect of vehicle weight on the sound produced by transverse rumble strips

Transverse rumble strips (TRS) are commonly used as traffic calming measure in the vicinity of premises. So far research have been extensively concentrated on the effect of vehicle type and speed on the noise produced by TRS, and very little research focused on the effect of vehicle weight. Do these vehicles produce extremely higher sound level parallel to their heavier weight? This is important as in reality, traffic flow consist of light, medium and heavy vehicles, which are also important sources of noise. This study investigated the effect of vehicle weight, such as gross vehicle weight (GVW) when transited on TRS, particularly with emphasis on impulsivity content. The objectives of this research were to: (1) determine the effect of GVW on noise generation when a vehicle transits on TRS and (2) assess the effect of GVW on the impulsivity of noise. Data from vehicles with weight between 800 kg - 8000 kg were collected based on previous research where these vehicles were tested on speed values of 30km/h and 50km/h. It was found that when the vehicles transited on TRS, the generated noise was strongly related with the vehicle weights (R2=0.71) higher than those normal road surface (R2=0.49). However, the changes of noise were not well represented by direct relation. It was found that TRS can increase and decrease the sound pressure level, depending on GVW, but on average, TRS can increase the sound pressure level by 1 dBA. Despite that, TRS was found to have an impulsive characteristic within the tested speed range. This finding can facilitate the authority to evaluate the environmental noise produced by TRS.

Situational characteristics of fatal pedestrian accidents involving vehicles traveling at low speeds in Japan

Objective: This study aimed to investigate the situational characteristics of fatal pedestrian accidents involving vehicles traveling at low speeds in Japan. We focused on vehicles with 4 or more wheels. Such characteristics included daytime or nighttime conditions, road type, vehicle behaviors preceding the accident, and vehicle impact locations.Methods: Pedestrian fatality data on vehicle–pedestrian accidents were obtained from the Institute for Traffic Accident Research and Data Analysis of Japan (ITARDA) from 2005 to 2014. Nine vehicle classifications were considered: Trucks with gross vehicle weight (GVW) ≥7.5 tons and <7.5 tons, buses, box vans, minivans, sport utility vehicles (SUVs), sedans, light passenger cars (LPCs), and light cargo vans (LCVs). We compared the situational daytime or nighttime conditions, road type, vehicle behaviors preceding the accident, and vehicle impact locations for accident-involved vehicles traveling at low and higher speeds across all vehicle types.Results: The results indicate that pedestrian fatalities involving vehicles traveling at low speeds occurred more often under daytime conditions across all vehicle types. At signalized intersections, the relative proportions of pedestrian fatalities were significantly higher when vehicles were traveling at low speed, except when the accidents involved box vans or SUVs. Similarly, when vehicles turned right, the relative proportions of pedestrian fatalities were significantly higher when vehicles traveling at low speed were involved across all vehicle types. In terms of the frontal right vehicle impact location, the relative proportions of pedestrian fatalities were significantly higher when trucks with GVW ≥7.5 tons or <7.5 tons, sedans, or LCVs traveling at low speed were involved.Conclusions: The situational characteristics of fatal pedestrian accidents involving vehicles traveling at low speeds identified in this study can guide targeted development of new traffic safety regulations or technologies specific to vehicle–pedestrian interactions at low vehicle travel speeds (i.e., driver alert devices or automated emergency braking systems). Ultimately, these developments can improve pedestrian safety by reducing the frequency or severity of vehicle–pedestrian accidents for vehicles turning right at intersections and/or reducing the number of resultant pedestrian fatalities.

Numerical analyses of rigid and flexible pavements responses under heavy vehicles’ loading

In an attempt to better understand the interaction between heavily loaded trucks and the pavement structure; rigid and flexible pavements’ responses (stresses, strains and deflections) were evaluated under simulated loading of 11-axle trucks (MI-20, MI-18, MI-14, MI-13) at gross vehicle weights (GVW) of 164,000 lb with different axle configurations, which are allowed in the state of Michigan. These responses were compared against results of a standard 5-axle semi-trailer at GVW nearing the common 80,000 lb standard in most states. Using these heavy truck types, the combined effects of truck loading, pavement thickness, joint spacing, material properties and thermal conditions on the pavement damages were evaluated. The major fatigue and faulting damages for rigid pavements as well as fatigue damage and subgrade rutting for flexible (asphalt) pavements are analysed. The finite element method (FEM) based program ISLAB2000 and multilayer elastic theory (MLET) based program JULEA were used to compute rigid and flexible pavements responses, respectively. Results show that the standard 5-axle truck yields up to 50% more fatigue damage potential under positive temperature gradient across slab (during daytime) even at a much lower gross vehicle weight than that of Michigan (MI) trucks. However, the 11-axle MI trucks provide up to 45% higher fatigue damage potential under negative temperature gradient (during nighttime). In comparison with the standard truck, the 11-axle MI trucks yield up to 17% less faulting damage for the typical rigid pavement with a thickness of 8 mm and up to 18% more faulting for larger pavement thickness. In flexible pavements, the standard truck exhibits up to 39% higher asphalt concrete fatigue damage than MI trucks. However, up to 80% more subgrade rutting damage for typical flexible pavements is observed for MI trucks with the multi-axles group configuration and larger GVW than the standard truck.

Some observations on BWIM data collected in Manitoba

Three highway bridges in the Canadian province of Manitoba are being monitored continuously not only for their long-term performance but also for bridge weighing-in-motion (BWIM). Data collected for the BWIM study has led to some observations that have far-reaching consequences about the design and evaluation loads for highway bridges. This paper presents the well-known concept of equivalent base length, Bm, as a useful tool for comparing trucks with different axle weight and spacing configurations as they influence load effects in all bridges. It is discussed that the statistics of gross vehicle weights (GVWs), W, collected over a one-month period is not significantly different from that for the GVW data collected over a longer period. A rational method concludes that the value of W for the CL-W Truck, the design live load specified by the Canadian Highway Bridge Design Code, is 555 kN for Manitoba. The observed truck data in Manitoba presented on the W–Bm space is found to be similar to that collected in the Canadian province of Ontario more than four decades ago. It was also found that the multi-presence factors, accounting for the presence of side-by-side trucks in two-lane bridges, specified in North American bridge design and evaluation codes are somewhat conservative.

On-board measurement of emissions from freight trucks in urban arterials: Effect of operating conditions, emission standards, and truck size

Diesel trucks contribute significantly to emissions leading to deterioration in urban air quality. Many recent studies have attempted to quantify real-world emissions from trucks in cities. However, studies on real-world emission from trucks in India are scarce. In this study, we measured real-world emissions of gaseous pollutants (CO, HC, and NO) from twenty trucks of different sizes and emission standards. The trucks were classified into three categories (light-duty diesel trucks (LDDTs), medium-duty diesel trucks (MDDTs), and heavy-duty diesel trucks (HDDTs)) based on their gross vehicle weight (GVW). The tested trucks conformed to Bharat Stage (BS) II, BS III, and BS IV emission standards. A vehicle specific power (VSP) based approach was adopted to model the relationship between vehicle activity and emissions. In addition, real-world emission factors of CO, HC, and NO for all the truck types were determined and compared based on their emission standard. Considerable reductions in emission factors were observed from lower to higher emission control standards for all the pollutants. The CO, HC and NO emission factors from the BS II standard LDDTs were 8.05 g/km, 0.86 g/km, and 8.04 g/km, respectively. The CO emission factor decreased by 29% and 65% respectively, for LDDTs and MDDTs with improved emission standards. The HC emissions (g/km) reduction from BS II to BS III for LDDTs and HDDTs were 49% and 8%, respectively. In the case of MDDTs, HC emission factor reduced by 16% from BS II to BS IV. On comparing with ARAI emission standards, we found that the emission factors of the trucks with GVW less than 3500 kg were higher for all the pollutants. In the case of trucks with GVW greater than 3500 kg, the CO emission factor for BS II and BS III complying trucks were higher than standard values while HC emission factors were lower than the standard values. Further, the emission factors of CO and NO from BS IV standard trucks were higher than the standard values. Moreover, emission factor values from our study were higher than that reported in the literature. Although India aims to adopt BS VI emission standards by 2020, phasing out older vehicles will be the key to mitigate emissions from diesel vehicles.

A Simplified Shear-Strain Based Bridge Weigh-In-Motion Method For In-Service Highway Bridges

Bridge Weigh-In-Motion (BWIM) has been demonstrated to be reliable for obtaining critical information about the characteristics of trucks that travel over the highways. Continued improvements provides greater opportunity for increased use of BWIM. Traditional BWIM systems based on measuring the bending strain of the bridge have various challenges which has led to a class of BWIM methodologies that employ the use of shear strain in determining the gross vehicle weight (GVW) of crossing trucks. However, the known techniques of these shear-strain BWIM methods assume or measure the shear influence line for the calculation of the GVW. In this paper, an alternative shear-strain based BWIM technique is proposed. The method presented here is independent of the influence line, does not require a measurement of the speed of the truck, and is based on the difference in magnitude observed at the discontinuity of the shear strain record as a truck crosses over the sensor location on the bridge. A series of field tests is presented that demonstrate this shear-strain based BWIM method has error levels consistent with other more complex BWIM methods and as such has great potential to be used for determining the GVWs of trucks that travel on simple or multispan bridges in a consistent and reliable manner.

Statistical Distributions of Pavement Damage Associated with Overweight Vehicles: Methodology and Case Study

The trucking industry is the primary mode of transporting for goods and commodities in the United States. Currently, there is an increasing trend in the use of overweight (OW) vehicles on the highway network. State highway agencies (SHAs) are challenged to address this increase, particularly relative to associated pavement damage. In this study, a probabilistic method was developed to evaluate rutting and fatigue cracking damage caused by OW vehicles under different road and environmental conditions. The influential input parameters in this analysis included gross vehicle weight (GVW), axle configuration, axle weight, pavement temperature, and vehicle-miles traveled (VMT). Necessary information was obtained by analyzing more than 170,000 entries of a Nevada Department of Transportation (NDOT) OW permit database. The developed model was based on mechanistic-empirical (ME) approach and considered asphalt concrete (AC) viscoelastic characterization. The results of this study were distributions of AC critical responses, load equivalency factors (LEFs), and relative damage factors (RDFs). The analysis showed that load equivalent factor (LEF) distributions could be incorporated in pavement design methods to account for OW vehicles. Furthermore, the damage induced by specific OW vehicles could be assessed using the relative damage factor (RDF) concept and may be efficiently used by SHAs during the permit application process. A case study was presented illustrating the impact of an OW axle configuration on pavement damage. Finally, a method was suggested for developing RDF tables with damage ranges corresponding to different axle configurations and the GVW that could be a tool for SHAs to evaluate and understand pavement damage induced by OW vehicles.