Verification, Refinement, and Applicability of Long-Term Pavement Performance Vehicle Classification Rules

Chapter 3. Findings From Comparison of the State and LTPP Vehicle Classification Rules

Can Volumes Taken in a State Rule Set Be Adjusted to the LTPP Class Volumes?

The research team investigated whether it is feasible to develop a simple ratio multiplier that would allow the number of vehicles in a given class counted with one set of classification rules to be converted into the “correct” number of those vehicles if they were counted with the LTPP rule set. The bottom rows and right hand columns of table 5 and table 6 show these multipliers for these specific test cases.

What became quickly apparent in this analysis was that these ratios were not stable values, even when just one alternative classification rule set was examined. While the classification rule sets have specific biases (e.g., Washington’s WIM rules generally identify more Class 10 vehicles than the LTPP rules), the relative effects of these biases change from site to site. As a result, when the output from the LTPP rules was compared with the output from any other vehicle classification rule set, the ratio computed for any given vehicle type was highly variable. Examples of this are shown in table 7 and table 8, which present these ratios for all TPF sites for the Washington WIM and Florida WIM rule sets. In addition, table 7 and table 8 provide the mean and standard deviation for each of these ratios. (Note that attempting to treat the value of volume by vehicle classification as a percentage of either total volume or total truck volume and then to adjust those percentages on the basis of changing from one classification rule set to another resulted in a relationship that was no more consistent.)

Whether the differences in classification results matter in the load estimation process is a function of the relative amount of traffic in each vehicle class. On many interstate highways with high volumes of Class 9 trucks, the errors in all other classes are likely to be of minimal importance. On rural roads with lower through truck volumes and with a high percentage of trucks that carry bulk commodities, these differences may be very significant. However, because the Class 9 truck is by far the most common heavy truck in use throughout the country, this later case is likely to be a fairly uncommon loading condition.

Another significant finding of this study is that the biases that occurred when the LTPP classification rule set was compared with State classification rule sets were not consistent from one set of rules to another. Some State rule sets place more vehicles than LTPP does into specific truck classes (such as Class 8), while other State rule sets under-count these vehicles in comparison with LTPP. The mean ratios (State rule set volume/LTPP rule set volume) by class of vehicles for all seven tested rule sets are shown in table 9. Whether State rules under- or over-counted specific truck classes was not a function of whether those rules used vehicle weight in their classification algorithm, so simply understanding whether a classification count came from a WIM scale or an AVC device does not provide insight into the relationship between that vehicle count and the LTPP classification rule set.

Table 7. Ratio of Washington rule set volume divided by LTPP rule set volume by vehicle class.

TPF Site	Class 1	Class 2	Class 3	Class 4	Class 5	Class 6	Class 7	Class 8	Class 9	Class 10	Class 11	Class 12	Class 13	Class 15
AZ 1	1.31	0.76	1.74	0.89	1.27	1.51	1.90	2.70	0.75	1.31	69.43	3.41	1.57	0.08
AZ 2	1.19	0.68	1.77	1.74	0.58	1.12	5.99	1.71	1.00	1.37	1.07	1.02	1.64	0.12
AR	1.40	0.72	1.47	1.58	0.85	0.97	1.50	1.92	1.00	1.60	1.05	1.06	1.46	0.10
CO	1.09	0.72	1.73	1.64	0.90	0.97	2.00	2.94	1.00	1.45	1.05	1.04	1.19	0.04
DE	1.02	0.80	1.69	5.69	0.99	0.91	1.02	2.05	1.01	1.27	1.67	1.53	1.52	0.15
IL	1.18	0.71	2.01	1.51	0.80	1.15	1.99	1.84	1.00	1.69	1.06	1.03	1.47	0.10
IN	1.01	0.77	1.70	4.85	1.27	0.75	1.01	1.55	1.00	1.18	1.02	1.07	0.52	0.09
KS	1.10	0.70	1.76	1.41	0.90	1.16	1.63	1.84	1.01	1.18	1.02	1.02	0.47	0.06
LA	1.01	0.69	1.31	5.11	2.06	0.89	1.09	3.95	1.01	1.29	1.32	1.21	0.71	0.41
ME	1.01	0.81	1.56	2.16	0.89	0.90	1.10	1.92	1.01	1.02	1.25	1.42	0.66	0.04
MD	0.99	0.82	2.21	4.29	0.64	0.81	1.19	1.59	1.00	1.69	5.47	1.87	0.09	0.08
MN	1.00	0.77	1.55	2.53	1.26	0.98	1.33	2.90	1.01	1.20	2.60	70.00	0.20	0.11
NM 1	1.03	0.77	1.40	0.87	1.22	1.50	2.99	2.70	1.01	1.13	1.06	1.05	0.75	0.04
NM 5	1.04	0.75	1.63	0.82	0.72	1.58	1.43	2.06	1.00	1.22	1.03	1.01	1.01	0.09
PA	0.96	0.76	1.71	1.58	0.95	0.95	1.01	1.80	1.00	1.21	1.03	1.01	0.65	0.15
TN	1.10	0.72	1.83	1.28	0.88	1.10	1.00	1.84	1.01	1.27	1.02	1.01	0.34	0.11
VA	0.98	0.82	1.97	3.43	0.69	0.89	1.39	1.47	1.00	1.33	1.02	1.04	0.61	0.20
WI	0.96	0.73	1.85	2.31	0.95	0.99	1.04	2.19	1.00	1.27	7.57	3.76	0.32	0.04
Mean	1.08	0.75	1.72	2.43	0.99	1.06	1.70	2.16	0.99	1.31	5.60	5.25	0.84	0.11
Standard Deviation	0.122	0.043	0.219	1.560	0.340	0.242	1.188	0.636	0.061	0.186	16.032	16.179	0.510	0.086

Note: Where the ratio shown is very large, the reason is always that a very small vehicle volume was present in the denominator of that class of vehicles. In such cases, a relatively modest change in the number of trucks resulted in a very large change in the ratio of one count versus the other.

TPF = Transportation Pooled Fund Study

Table 8. Ratio of Florida WIM rule set volume divided by LTPP rule set volume by vehicle class.

TPF Site	Class 1	Class 2	Class 3	Class 4	Class 5	Class 6	Class 7	Class 8	Class 9	Class 10	Class 11	Class 12	Class 13	Class 15
AZ 1	1.49	0.97	1.08	1.04	0.76	1.00	0.95	0.74	0.96	1.04	0.99	1.00	1.83	1.49
AZ 2	1.62	0.96	1.22	1.06	0.61	1.00	0.75	0.69	0.99	1.03	1.00	1.00	2.05	1.62
AR	1.58	0.97	1.08	1.02	0.68	1.00	0.76	0.76	1.00	1.04	1.00	1.01	2.31	1.58
CO	1.41	0.98	1.14	1.03	0.61	1.00	1.05	0.73	0.99	1.02	1.00	1.00	2.05	1.41
DE	1.04	0.99	1.08	1.23	0.72	1.00	0.99	0.66	0.99	1.06	1.00	1.00	2.81	1.04
IL	1.31	0.95	1.21	1.03	0.72	1.00	1.03	0.75	0.99	1.15	1.00	1.00	2.37	1.31
IN	0.99	0.99	0.98	1.05	0.76	1.00	0.57	0.84	1.00	1.02	1.00	1.00	1.32	0.99
KS	1.68	0.97	1.15	1.03	0.58	1.00	1.02	0.63	0.99	1.01	1.00	1.01	1.17	1.68
LA	1.03	0.97	0.96	1.26	1.16	1.00	0.99	0.84	0.99	1.03	1.00	1.02	1.25	1.03
ME	1.04	0.98	1.10	1.10	0.54	1.00	1.00	0.84	1.00	1.01	1.00	1.01	1.38	1.04
MD	1.12	0.99	1.26	1.05	0.44	1.00	0.94	0.64	0.99	1.20	1.00	1.00	1.14	1.12
MN	1.01	0.98	1.04	1.12	0.70	1.00	0.85	0.64	0.99	1.01	1.01	1.00	1.08	1.01
NM 1	1.04	0.98	1.01	1.02	0.84	1.00	0.98	0.71	1.00	1.00	1.00	1.00	1.22	1.04
NM 5	1.07	0.97	1.14	1.02	0.60	0.99	1.04	0.75	0.99	1.01	1.00	1.00	1.39	1.07
PA	1.19	0.97	1.09	1.03	0.77	1.00	1.00	0.87	0.99	1.02	1.00	1.00	1.49	1.19
TN	0.94	0.97	1.10	1.02	0.75	1.00	1.00	0.84	1.00	1.01	1.00	1.01	1.18	0.94
VA	1.29	0.99	1.23	1.04	0.51	1.00	0.71	0.76	1.00	1.19	1.00	1.01	1.42	1.29
WI	1.17	0.97	1.15	1.04	0.63	1.00	0.14	0.75	1.00	1.03	1.00	1.00	1.14	1.17
Mean	1.22	0.98	1.11	1.07	0.69	1.00	0.88	0.75	0.99	1.05	1.00	1.00	1.59	1.22
Standard Deviation	0.237	0.011	0.084	0.071	0.157	0.003	0.228	0.077	0.008	0.063	0.004	0.005	0.517	0.237

TPF = Transportation Pooled Fund Study

Table 9. Mean across all test sites of alternative rule set volume by class divided by LTPP rule set volume by class.

New Class Rule Set	Class 1	Class 2	Class 3	Class 4	Class 5	Class 6	Class 7	Class 8	Class 9	Class 10	Class 11	Class 12	Class 13	Class 15
CA WIM	1.05	0.93	1.20	1.16	0.99	1.00	0.76	1.00	0.97	1.01	1.00	1.00	1.22	2.27
WA WIM	1.08	0.75	1.72	2.43	0.99	1.06	1.70	2.16	0.99	1.31	5.60	5.25	0.84	0.11
FL WIM	1.22	0.98	1.11	1.07	0.69	1.00	0.88	0.75	0.99	1.05	1.00	1.00	1.59	6.42
MO AVC	1.24	1.03	1.05	2.05	0.58	1.03	0.71	0.69	1.02	1.26	0.88	2.03	1.36	0.07
CA AVC	1.28	0.98	1.27	1.08	0.30	1.00	0.87	0.67	0.97	1.01	1.00	1.00	0.99	2.06
WI AVC	1.24	1.02	0.92	4.70	0.69	0.84	2.80	2.16	0.99	1.07	0.88	2.03	0.51	3.21
FL AVC	1.24	0.98	1.06	1.20	0.58	1.03	0.66	3.81	1.00	1.05	1.00	1.00	1.39	1.06

WIM = Weigh in Motion

AVC = Automatic Vehicle Classification

In combination with the variability of these ratios from site to site (as illustrated in table 7 and table 8), this means that it is not possible to develop a set of national adjustments that will accurately convert traffic volumes collected using any given State classification rule set to the volumes needed to correctly apply the LTPP load spectra. Creating such an adjustment requires understanding the effects of using different classification rule sets, and that requires performing a detailed analysis of both the State classification rule set being used and the characteristics of the vehicles at each specific site.

One approach for solving this problem in the future would be to develop files containing per-vehicle records for the vehicle classification data, similar to the ones currently used in W-cards for the weight data. This way vehicle classification data collected using one algorithm or rule set could be reprocessed if a different algorithm or rule set is desired (for example, to align data collected using different classification rule sets).

Changes in Total Truck Volume

The fact that the estimated volume of trucks in any given FHWA vehicle class changes when different classification rule sets are applied is important, but these volume by class changes also affect the total number of vehicles that are called “trucks” (and thus how many vehicles are included or excluded in the pavement design process), as well as the number of axles by type of axle associated with each class of truck.

The total volume of trucks counted is significant for two reasons. First, pavement design is often based on simple traffic estimates. Traffic loads have traditionally been computed by using the simple formula “traffic volume multiplied by percentage of trucks multiplied by load (damage) per truck,” where “trucks” are all vehicles in FHWA Classes 4 and higher. This basic concept is still important when the MEPDG is used because only FHWA vehicle Classes 4 through 13 are included in the MEPDG pavement analysis process. Therefore, any vehicle classification system that changes the estimated number of trucks using a given roadway has the potential to change the performance predicted by a design/analysis effort.

Consequently, as vehicles are shifted into or out of vehicle Classes 1, 2, 3, and 15,^[5] the total number of vehicles that affects the pavement design changes. If an average percentage of trucks within a given vehicle class is multiplied by total trucks, as can occur in a Level 3 MEPDG design, the estimate of total trucks will also affect the number of trucks found within each of the FHWA truck categories.

Table 3 through table 5 demonstrate that the number of vehicles in Classes 1, 2, and 3 is generally far greater than the number of vehicles in the other vehicle classes. Therefore, a relatively small change-in percentage terms-within these passenger vehicle categories can result in very large changes in both the number of trucks in a specific truck class and in the total number of trucks.

Because cars pulling trailers have axle spacing characteristics that are frequently similar to those found on multi-unit trucks, many classification rule sets have difficulty separating these two types of vehicles. Consequently, changing from one rule set to another can shift many of these vehicles into or out of the various truck classes. Where large numbers of cars and pickups pulling trailers exist, these changes can result in large percentage differences in truck volumes while creating only minor percentile differences in passenger vehicle volumes.

Table 6 demonstrates this issue clearly. As a result of their different parameter settings, the Florida WIM classification rules and the LTPP classification rules traded a number of vehicles among vehicle Classes 2, 3, 5, 8, and 15. However, because Classes 2 and 3 were very large in comparison with Classes 5, 8, and 15, a 25-percent decline in Class 5 trucks combined with a 16-percent reduction in Class 8 trucks resulted in only a 9-percent increase in Class 3 passenger vehicles, even though roughly half of the Class 3 increase came from Class 2 (cars pulling trailers), and Class 2 lost only 3 percent of its LTPP estimated volume.

Table 10 shows that four of the seven classification rule sets used for this portion of the analysis counted, on average, fewer trucks than the LTPP rule set. The other three rule sets counted more trucks than the LTPP rule set. However, once again, there was considerable variation in these statistics from site to site for any given set of rules.

Table 10. Ratio of total trucks (Classes 4-13) counted by TPF site alternative rule set/LTPP rule set.

TPF Site	WA WIM	WI AVC	MO AVC	FL AVC	FL WIM	CA WIM	CA AVC	OH AVC
AZ 1	1.354	1.068	0.728	1.069	0.816	0.945	0.464	1.165
AZ 2	0.978	0.935	0.923	0.972	0.933	0.992	0.872	0.983
AR	1.025	0.984	0.970	1.015	0.967	0.996	0.927	1.023
CO	1.045	0.967	0.884	0.985	0.898	0.997	0.791	1.005
DE	1.067	0.998	0.865	0.988	0.884	1.002	0.768	1.020
IL	1.015	0.993	0.952	1.008	0.958	0.994	0.907	1.016
IN	1.098	1.042	0.970	1.044	0.941	0.990	0.891	1.065
KS	1.030	0.943	0.889	0.972	0.894	0.996	0.818	0.986
LA	1.623	1.412	0.937	1.326	1.062	1.007	0.685	1.444
ME	1.033	0.987	0.886	1.050	0.887	1.002	0.823	1.006
MD	0.845	0.747	0.630	0.713	0.632	1.006	0.493	0.752
MN	1.233	1.106	0.844	1.140	0.857	0.996	0.700	1.147
NM 1	1.157	1.062	0.921	1.096	0.949	0.999	0.817	1.107
NM 5	1.009	0.955	0.961	1.004	0.959	0.996	0.928	1.006
PA	1.019	0.995	0.979	1.006	0.976	0.993	0.949	1.011
TN	1.022	0.994	0.981	1.017	0.980	0.999	0.953	1.022
VA	0.966	0.912	0.864	0.923	0.862	0.999	0.800	0.934
WI	1.059	1.015	0.913	1.012	0.888	0.972	0.822	1.037
Mean	1.088	1.006	0.894	1.019	0.908	0.993	0.800	1.041
Standard Deviation	0.172	0.127	0.091	0.116	0.090	0.014	0.141	0.133
Number of TPF Sites with Ratio > 1	15	6	0	12	1	4	0	14

TPF = Transportation Pooled Fund Study

WIM = Weight in Motion

AVC = Automatic Vehicle Classification

For example, in comparing the Wisconsin rule set with the LTPP rule set, on average, there was very little difference in truck volumes counted. (The mean volume of trucks changed by a factor of 1.008.) However, at only 6 of the 18 TPF sites did the Wisconsin rule set actually count more trucks than the LTPP rule set. At one of those six sites, the Louisiana SPS-1 site, the Wisconsin rules estimated many more Class 4, Class 5, and Class 8 vehicles. This resulted in a 40-percent overall increase in total truck volume in comparison with the LTPP rules. In calculating the average for Wisconsin, this outlier result overshadowed the fact that 10 of the TPF sites showed lower volumes. The result also highlights that specific vehicle configurations that shift from one vehicle class to another, given a specific set of rules, are often over-represented at individual sites yet almost nonexistent at other sites.

From a pavement design perspective, it is not just the percentage change in volume for each class that matters but also the absolute change in volume for those specific classes of trucks that apply a large fraction of the load to the pavement. In the case shown in table 4,^[6] Class 8 trucks increased by 33,700 vehicles in the year measured, while Class 9 trucks increased by 6,900 vehicles, Class 10 increased by almost 2,900, and Class 11 increased by more than 2,000. These changes were offset by a decrease of more than 13,400 Class 5 trucks and 1,500 Class 13 trucks. However, Class 5 trucks would likely subject the pavement to very light traffic loads, and the number of Class 13 vehicles was relatively small given the increase in Class 9 trucks. Therefore, if vehicle counts based on the Washington WIM system were used, the increase in estimated load at this site would be larger than the simple increase in truck volume would suggest because the vehicles added to the truck counts were generally considered to be heavier than the vehicles removed from the truck counts.

The importance of such an increase on predicted pavement performance and the resulting appropriate pavement design is the subject of later analyses within this project.

Given the above findings, the research team concludes that there is no simple set of adjustments that can be computed and applied to State-supplied vehicle volumes by classification that will account for differences between a State classification rule set and the LTPP rule set. Neither is it possible, without detailed site and rule set specific data, to predict the size and scope of total volume changes when alternative classification rule sets are used.

Changes in the Number of Axles Per Vehicle by Class of Vehicle

Traffic volume by class is not the only change that occurs when the application of a different classification rule set causes vehicles to shift FHWA classes. The estimated number of axles, by type of axle, associated with each class of vehicles also changes. These values (e.g., the number of single-axle loads to which the average Class 8 truck subjects the pavement) are computed as part of the load spectrum development process. The MEPDG then uses these values to determine how many axles of a given axle type should be applied to design a pavement section on the basis of the number of trucks of that vehicle class.

If the truck volume counts were taken with a different classification rule set than the load spectra that are applied along with those counts, the expected number of axles per vehicle for each class of vehicles would likely be incorrect. Exactly how those values change is a function of which vehicles shift from one class to another, along with the percentage of vehicles within each of those two classes that shift from one class to another.

An excellent example of this issue is the Class 13 to Class 10 shift described earlier in this report. Almost all of the vehicles that must shift from LTPP’s Class 13 to Class 10 to be correctly classified are equipped with either tridem or quad axles. If this shift occurs, it decreases the number of tridem and quad axles included in the Class 13 load spectrum, which will probably decrease the number of tridem and quad axles per Class 13 vehicle.

In many States, the vehicles that remain in Class 13 after such a shift has occurred are more likely to be dominated by the most common long haul vehicle configurations, such as the seven-axle configuration single-tandem-tandem-single-single ^[7] and the eight-axle variant of that vehicle, which replaces the last single axle with a tandem axle. (Note that there are no tridem or quad axles in either of these configurations.) Thus, after removal of the Class 10 trucks, the Class 13 load spectrum would be expected to reflect fewer tridem or quad axles per truck and more single or tandem axles per truck because the total number of axles per truck must be greater than or equal to seven.

Of course, if the vehicles that remain in Class 13 are primarily Canadian B-train configurations (single-tandem-tridem-tandem), then the number of tridem axles per truck in Class 13 will remain high-or even increase-especially if the Class 10 vehicles that change vehicle classes have quad axles instead of tridem axles. If the Class 10 vehicles that shift classes all have single-quad-quad axle configurations and all the vehicles that are left are Canadian B-trains, the number of quad axles per truck will decline to zero in Class 13, while the number of tridems per truck will increase to 1.0.

Similarly, the nature of the trucks shifting into Class 10-relative to what is already included in Class 10-will determine whether the number of tridems or quad axles per vehicle changes. Table 11 shows how the estimated number of axles per vehicle in Classes 10 and 13 changes depending on whether the LTPP rules or the Washington rules are applied to the Tennessee SPS-6 site.

To understand this table, note that the LTPP rules counted 10,587 Class 10 trucks and 2,358 Class 13 trucks at this site. Application of the Washington rules to the set of vehicle records at this WIM site keeps all of the LTPP Class 10 vehicles in Class 10. It also moves an additional 2,018 vehicles from Class 13 and 25 vehicles from Class 12 into Class 10, and it identifies 838 vehicle records that were previously unclassified as Class 10. Thus the Washington rules increase the Class 10 count by 21 percent, which, while a substantial increase, is still a modest percentage change. The fact that almost 80 percent of the vehicles in Class 10 do not differ from those classified by the LTPP rules limits the degree to which additional axles of a specific type will change the axle/truck values computed for that class.

For Class 13, the Washington rules remove 2,018 of the 2,358 vehicles placed there by the LTPP rules while adding an additional 463 vehicles that are unclassified under the LTPP rules. A large proportion of those unclassified vehicles have more than the nine-axle maximum allowed by the LTPP rule set. (Washington allows up to 12 axles in Class 13.)

Table 11. Number of axles per truck, Tennessee SPS-6 site, Washington WIM versus LTPP classification rule set.

Class/Axles	Washington WIM Rules	LTPP Rules
Class 10 Singles	1.013	1.007
Class 10 Tandems	1.197	1.353
Class 10 Tridems	0.691	0.644
Class 10 Quads	0.068	0.001
Class 13 Singles	1.564	1.080
Class 13 Tandems	1.598	0.752
Class 13 Tridems	0.501	0.996
Class 13 Quads	0.875	0.357

WIM =Weight in Motion

LTPP = Long-Term Pavement Performance

As shown in table 11, there are significant differences in the number of axles in all four axle groups in Class 13, with smaller differences in Class 10. This is partly because 80 percent of the vehicles in Class 10 under the Washington rules are also there under the LTPP rules, whereas the makeup of Class 13 changes dramatically, with more than 85 percent of the LTPP Class 13 vehicles changing categories, and more than 57 percent of the Washington Class 13 vehicles coming from a different classification. The result is that under the Washington rule set, Class 10 gains a substantial number (in percentage terms but not in absolute terms) of quad axles per truck and a more modest number of tridem axles per truck, while the number of tandems and single axles per truck declines slightly. In Class 13, in part because of the smaller number of trucks used in the denominator of the axle/truck calculation, these vehicle shifts result in a dramatic increase in the number of quad axles per truck, a decline of nearly 50 percent in the number of tridems per truck, a doubling of the number of tandems, and a 50-percent increase in the number of singles.

Another big change in Class 13 under the Washington rules is that because of the addition of the large number of vehicles with 10 or more axles, the total number of axles per truck for Class 13 changes from 7.0 axles per truck to 9.76 axles per truck. In Class 10, the addition of the vehicles with more axles per truck has less impact but still increases the total number of axles per truck from 5.65 to 5.75.

As with many of the other classification changes examined in this study, in some cases, changes from one classification rule set to another result in large changes in the number of axles per truck (by type of axle). In other cases, these changes are relatively modest. It is not possible to predict the significance of these changes for any given site and any given State rule set without detailed information about that site and rule set.The above example simply illustrates the complexity of the interactions that govern how the estimated number of axles per truck changes given a change in the vehicle classification rule set.

The different factors that affect potential changes in the estimated number of axles per truck when a specific classification rule set is applied can be summarized as follows:

• Does the new classification rule set have a bias (relative to the old rule set) in how vehicles are classified? (If not, no significant changes occur.)
• Whether such a bias affects the average number of axles per truck is a function of the following:
  • Whether specific axle configurations are associated with the vehicle types related to those biases.
  • Whether the number of trucks shifting into or out of a given classification is small or large relative to the number of vehicles remaining in that class from the original classification rule set.
  • Whether the vehicles moving into or out of a vehicle class have a total number of axles per truck that is substantially different than that found on the vehicles remaining in that classification.

All of these factors are affected by the nature of the vehicle fleet using a specific roadway, which in turn, is affected by the truck size and weight laws in each State. As a result, as noted repeatedly above, there is considerable variability from site to site and from one classification rule set to another, in how the number of axles (by type of axle) per vehicle for each class of vehicles changes, given a change in classification rules.

This variability is well illustrated by comparing the Washington and LTPP rule sets and looking at the resulting changes in the estimated number of quad axles per Class 10 vehicle. When compared across all 18 test sites, the mean value for the change in this number as a result of shifting from the LTPP rules is an increase of 0.104 quad axles per truck. However, this value ranges from 0.004 (at the Maine SPS-5 site) to 0.334 (at the Maryland SPS-5 site). In contrast, if either of the California rule sets is compared with the LTPP rule set, essentially no change occurs in the number of Class 10 quad axles per truck.

If Class 8 is examined instead of Class 10, the California AVC rules produce a mean decrease of 0.142 in the estimated number of single axles per truck, along with an increase of 0.212 tandems per truck. The Washington rule set has the opposite effect, increasing the number of single axles per truck by 0.115 and decreasing the number of tandems per truck (by -0.188). The standard deviation of these statistics ranges from 0.05 to almost 0.10. That is, the coefficient of variation ranges from 25 percent of the mean adjustment to more than 90 percent of that mean adjustment.

All of these changes will have an effect on the load that each of these vehicle types is estimated to apply when volume counts based on non-LTPP classification rule sets are used in conjunction with load spectra computed from WIM scales that incorporate the LTPP classification rule set. These changes become significant from the pavement design perspective when these classes make up a high percentage of the truck distribution for a given site.

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⁵ Class 15 is "unclassified" vehicles. Unclassified vehicles are not used in the MEPDG computations.

⁶ Table 4 shows the effects of the conversion from the LTPP rule set to the Washington WIM rule set at the Tennessee TPF site.

⁷ This axle configuration is consistent with a standard three-axle tractor pulling a semi-trailer with a tandem rear axle, which in turn, is pulling a full trailer with two single axles.