3.1  Introduction

For freight transportation planning and highway deficiency analysis, it is important to know the number of truck trips passing through a particular highway section between freight origins and destinations. While States collect and maintain data on the number of trucks passing sections of the highway network, there is currently no direct source of information on the number of truck trips between origins and destinations. The Commodity Flow Survey (CFS), which is a comprehensive nationwide freight movement data source, provides information in terms of the tonnage and value of commodities between destination pairs. Consequently, it is necessary to convert commodity volume into truck trips for the purposes of assignment onto the highway network as part of freight planning process. This chapter describes procedures to convert the commodity flows measured in tons into the equivalent number of trucks for the development of FAF² truck O-D matrix.

3.2  Tonnage to Truck Payload Conversion Process

The primary source of information for developing the procedures for converting commodity flow in tons to truck trips was the 2002 Vehicle Inventory and Use Survey (VIUS) database. VIUS provides data on the physical and operating characteristics of the nation's truck population.
It provides national and state-level estimates of the total number by type of trucks. This data are gathered through surveys of a sample of the motor carrier industry and is conducted every 5 years as part of the economic census. The conversion of commodity flows from tons to truck trips involved four main steps:  (1) identifying the primary truck configurations and major truck body types, (2) allocating commodities to truck body types that are used to transport these commodities, (3) estimating average payloads by vehicle group and body type, and (4) converting the commodity tons into the equivalent number of trucks. Figure 3.1 is a schematic presentation of these steps. An additional step (5) involves estimating the percent of empty truck trips. This information is required for purposes of highway capacity and system usage analyses.

3.2.1  Truck Configuration

The first step in the process involved identifying the major truck types in terms of axle configuration and number of trailers. Using the AXLE_CONFIG variable in VIUS, the following five broad categories of truck configurations were identified:

• Group 1 – single unit trucks (straight trucks, SU)
• Group 2 – truck plus trailer combinations (truck plus trailer combinations)
• Group 3 – tractor plus semitrailer combinations (3S2, 2S2 etc.)
• Group 4 – tractor plus double trailer combinations (3S2-2)
• Group 5 – tractor plus triple trailer combinations (2S2-2-2).

For each vehicle group, there are several body types. Since truck size and weight limits are determined by the configuration, these groups reflect the range of truck weight limits and therefore the average payloads expected on the highway network. The body type also determines the type of commodities transported. As such, the various body types used in VIUS were analyzed to determine the major types.

 

Figure 3.1:  Steps in Conversion Process

 

Frequency distributions of the various body types by vehicle group were studied. Based on this analysis, the major types were identified. Figure 3.2 shows the body type distribution before and after grouping when all vehicle groups are combined. In grouping the body types, consideration was given to the average payloads and weights by vehicle group. This was necessary to ensure that body types in any one major group have similar average payloads. For example, even though the shape and appearance of a tractor plus trailer vehicle with open top van body type is similar to that of a basic enclosed van, the average payload for the former is more than 1.5 that of the latter. The average payload for the open top van is about the same as for the dump truck. Open top vans are typically used to transport high-density, heavy commodities. Consequently, these two body types are grouped together. Logging, livestock, and automobile carrying trailers are specialized body types that are considered separately from the other body types considered in this analysis. The following nine major truck body types were selected in order of decreasing percentage in the truck fleet.

1. Dry van (basic enclosed, drop frame, insulated non-refrigerated, curtainside, beverage) – 37.72%
2. Flat bed (flatbed, lowboy, stake, platform) – 24.37%
3. Bulk (dump, open top van, hoppers) – 14.73%
4. Reefer (insulated refrigerated) – 8.15%
5. Tank (dry bulk, liquid, gases) – 7.97%
6. Logging (pole, logging, pulpwood, pipe) – 2.12%
7. Livestock – 1.70%
8. Automobile – 0.91%
9. Other – (concrete mixers, service trucks, trash, mobile home toter, etc.) – 2.33%.

Figure 3.2 shows the vehicle groups and Figure 3.3 shows examples of these major body types. The next step was to determine the distributions of commodities by truck body type.

 

Figure 3.2:  Selected Major Body Types

 

 

Figure 3.3:  Configurations of Vehicle Groups and Samples of Body Types

 

3.2.2  Commodity to Truck Body Type Allocation

The purpose of this sub-task was to identify the truck body types transporting the various commodities. To do so, frequency distributions were developed to identify the commodity types moved by the different truck body types. These distributions provide the basis for allocating the various commodities or groups of commodities to truck body types. Since a given truck body type may be used for transporting more than one type of commodity and since average payloads are dependent on the commodity type, this step established the percent of a given commodity carried by each vehicle group. This was a critical step in estimating the number of trucks expected to move a given volume (in tons) of freight between a given O-D pair. The distributions are expressed in percentages of the total number of trucks of a given vehicle group transporting each commodity type. These percentages were then broken down by truck body type and normalized to correspond to the total percentage for each vehicle group.

Given the geographical differences in truck size and weight regulations and types of commodity movements, States were grouped in the five regions used in the 1997 U.S. Comprehensive Truck Size and Weight (TS&W) Study. Therefore distributions were developed for each of the five regions and also at national level.

3.2.3  Payload Estimation and Validation

The mean and standard deviations of the gross vehicle weights, empty weights, and payloads were calculated for each vehicle group, major body type, and commodity. These mean payloads and the percent distributions discussed above were required to calculate the truck equivalent factors as described in the next section.

Since VIUS data were obtained through surveys, vehicle weight and payload data were not obtained by actually weighing the trucks. As such, actual truck weight data and expert knowledge of vehicle weight distributions of the various trucks were required to validate the average payloads derived from VIUS. Truck weight data from the 2002 Vehicle Travel Information System (VTRIS) were analyzed to serve as benchmark to validate the mean vehicle weights derived from VIUS. VTRIS is a database management system designed for vehicle classification and truck weight data.

Differences exist between the two sources of data. For example, vehicle classification in VTRIS is different from that used in VIUS. Straight trucks pulling trailers are not distinguished in VTRIS, and multiple trailer combinations in VTRIS do not differentiate between double and triple trailers. However, single unit trucks and single trailer combinations are clearly defined in VTRIS. These two truck types (vehicle groups) are common to both data sources. Furthermore, VTRIS data records the gross vehicle weights for loaded trucks. Consequently, the validation exercise focused on the gross weights of the loaded vehicles and for the two vehicle groups only. The mean weights for these two vehicle groups from VTRIS were compared with mean weights derived from VIUS (Table 3.1).

The results indicate that the mean vehicle weights for the tractor single trailer combinations from the VTRIS database compare well with those derived from VIUS. The differences vary from 5 to 12 percent across the five regions. This truck type represents 80 to 94 percent (average of 88 percent) of the sample of trucks weighed. Therefore it can be concluded that the mean weights and hence the payloads derived from VIUS are valid representations of mean weights for this truck type. The mean weights for single unit trucks from the VIUS data, however, are 16 to
54 percent (average 45 percent) less than weights derived from VTRIS for the same truck type. Obviously, the differences in the mean weights for the single unit trucks are quite significant across all five regions. It was therefore necessary to explore the variability of the VIUS data.

Table 3.1:  Results of Vehicle Weight Validation

Vehicle Group	Region	% of Trucks	VTRIS Mean GVW	% Difference†	VIUS weight			Adjusted VIUS Weight	% Difference†
					Mean	σ	CV
Straight Truck	North Central	6.1	46,462	41.5	27,165	16,712	0.62	43,876	5.6
	North East	19.4	55,212	53.1	25,895	18,929	0.73	44,824	18.8
	South Atlantic	11.9	36,748	25.8	27,249	18,163	0.67	45,412	-23.6
	South Gulf	14.3	47,913	46.2	25,794	17,265	0.67	43,059	10.1
	West	7.7	53,833	56.4	23,494	15,714	0.67	39,208	27.2
	AVERAGE	11.9	48,034	44.6	25,919	17,357	0.67	43,276	7.6
Tractor + Single Trailer	North Central	93.7	75,978	5.1	72,072	14,390	0.20
	North East	80.2	81,578	11.7	72,008	17,274	0.24
	South Atlantic	87.8	67,281	-5.5	71,001	12,878	0.18
	South Gulf	84.3	78,584	13.3	68,132	15,117	0.22
	West	91.3	75,439	8.2	69,244	16,991	0.25
	AVERAGE	87.5	75,772	6.6	70,491	15,330	0.22

† - percent difference relative to VTRIS data

The extent of variation of the data from VIUS was examined by calculating the coefficients of variation (CV) of the mean vehicle weights derived from VIUS. CV is a statistical measure of dispersion around the mean and it is a useful statistic for comparing the degree of variation from one data series to another. Table 3.2 shows the CVs by vehicle group and body type. For the tractor plus trailer combinations, the CVs are less than 20 percent. This is considered acceptable given that the data were gathered through surveys of motor carriers with a wide range of operations. However, for the single unit straight trucks and truck plus trailer combination vehicle groups, the CVs are significantly high (i.e., 50 percent on average for single unit straight trucks and 46 percent for truck plus trailer combinations), indicating greater dispersion about the mean for these vehicle groups. The significantly low mean weights compared to actual weights from VTRIS and the wide dispersion of the VIUS data for these vehicle groups require adjustments in order to reflect reality as closely as possible. To this end, the mean weights from VIUS data were augmented by one standard deviation and the resulting weights were compared to the mean weights from VTRIS data. As noted in Table 3.2, the adjusted weights compare favorably with the VTRIS weights, i.e., an average difference of less than 8 percent compared to 45 percent before adjustment. Figure 3.4 also shows the comparisons.

Based on the results of this analysis, the average payloads derived from VIUS for the straight truck and straight plus trailer combination vehicle groups were adjusted by augmenting the mean by one standard deviation. No adjustment was necessary for the other three vehicle groups.

Table 3.2:  Results of Variation Analysis

Body Type	Mean (lbs)	σ (lbs)	CV	Mean (lbs)	σ (lbs)	CV	Mean (lbs)	σ (lbs)	CV
	Straight Trucks			Straight Trucks + Trailers
Automobile
Livestock
Bulk	33,864	16,956	50.1	34,213	24,690	72.2
Flatbed	31,678	19,614	61.9	39,367	22,732	57.7
Tank	34,156	13,188	38.6	59,744	25,343	42.4
Van	17,140	8,416	49.1	21,236	13,730	64.7
Reefer	24,823	9,332	37.6	23,056	2,994	13.0
Logging	45,492	21,362	47.0	82,208	20,479	24.9
other	30,232	20,213	66.9	28,193	13,930	49.4
average			50.2			46.3
	Tractor +single trailer			Tractor +double trailer			Tractor + triple trailer
Automobile	73,804	10,673	14.5
Livestock	71,852	16,559	23.0	101,569	953	0.9
Bulk	78,517	11,263	14.3	97,910	22,869	23.4	110,167	21,744	19.7
Flatbed	72382	17,203	23.8	95,855	14,986	15.6	178,793	29,520	16.5
Tank	78,507	9,617	12.3	100,813	27,354	27.1
Van	64,313	13,634	21.2	79,491	9,051	11.4	99,891	8,329	8.3
Reefer	72,218	12,306	17.0	79,242	21,667	27.3
Logging	79,442	11,257	14.2	95,888	30,500	31.8
other	53,725	16,997	31.6
average			19.1			19.7			14.9

 

 

Figure 3.4:  VIUS and VTRIS Mean Weight Comparison

 

3.2.4  Tons-to-Truck Trips Conversion

This is a two-step process. First, the mean payloads by truck type, body type, and commodity type were established. Second, the mean payloads were applied to the percent allocations by body type to convert the commodity volume in tons to an equivalent number of trucks. The formulation of the conversion from commodity tons to equivalent number of trucks is outlined below:

Let X_i represent the tonnage of commodity i, where i = 1, 2, ….. 50.

Let Y_j represent the number of trucks in vehicle group j, where j = 1, 2, …. 5.

Let β_k represent fraction of commodity moved by truck body type k, where k = 1, 2,..9.

Let ω_ijk represent mean payload of truck type j with body type k transporting commodity i.

 

Tonnage of commodity X_i carried by truck type j and body type k = X_i β_ijk

Number of truck type j and body type k required to move X_i β_jk tons = X_i β_ijk / ω_ijk

Where β_ijk = fraction of commodity i moved by truck type j with body type k

Number of truck type Y_j=1 to move X_i β_ijk tons commodity X_i by all body types is given by

 

          (3.1)

 

Similarly, the number of truck type Y_j=2 to move X_i β_ijk tons commodity X_i by all body types

 

          (3.2)

 

Thus, the number of truck type Y_j to move X_i β_ijk tons commodity X_i by all body types can be expressed as

 

          (3.3)

 

Therefore, the total number of trucks to move commodity X_i and the total number of trucks to move commodity all commodities are given by the following expressions.

 

          (3.4)

 

          (3.5)

 

The ton-to-truck conversion factor or truck equivalency factor is therefore is given by

 

          (3.6)

 

TEF_ijk = is the factor that converts tons of commodity to equivalent number of trucks. This is a 3-dimensional factor that is a function of (i) truck type (configuration), (ii) body type, and (iii) commodity. These factors at national level are presented in Table 3.3.

3.3  Empty Truck Percent Estimation

The conversion process described in the previous sections estimated the number of trips of loaded trucks based on commodity movements. Consequently, “empty trucks” are not included. Empty trucks equally impact the capacity of the highways and therefore must be accounted for in analyzing system performance. Approaches for identifying and accounting for empty trucks include adjusting the matrix during calibration or using complementary models to depict empty trips as a function of routing choices that a commercial vehicle operator can make. The former approach was adopted in this study. The number of empty trucks was estimated by analyzing the percent of miles that a truck is empty in VIUS to determine the percent of trucks operated in empty conditions. The analytical steps are described in this section.

First, frequency distributions of empty trucks for each vehicle group were analyzed. The results of the frequency distributions are depicted in Figure 3.5. The percent of miles that each vehicle group operates in an empty condition varies. However, more than 50 percent of trucks in each vehicle group operate less than half-empty. For example, about 55 percent of straight trucks and 58 percent of tractor semitrailer combination trucks are less than 50 percent empty. For the straight truck plus trailer and tractor plus double trailer combinations, however, more than
70 percent of the empty truck miles are operated less than 50 percent empty. In other words, according the VIUS data, the percentages of miles that trucks are completely empty are rather small.

 

Figure 3.5:  Cumulative Distribution of Percent of Miles Empty

 

Second, the means, standard deviations, and medians of the percent of empty miles were calculated at the national level for each vehicle group and major body type. The results are summarized in Table 3.3. Depending on the vehicle group, the mean values range from 19 to 29 percent with single unit straight truck vehicle group having the highest value.

 

Table 3.3:  Truck Equivalent Factors Used in FAF² Tonnage to Truck

NOTE:  The missing cell indicates that commodity is not carried by those particular vehicle group and associated body types

 

Third, the analysis of means and medians was repeated by major body type. Differences in percent of empty miles among body types of the same vehicle group exist. The analysis further accounts for the interchangeability and flexibility of the certain truck body types (e.g., dry van) and the specificity of other body types (e.g., automobile, livestock, tank) in the types of commodities that they transport. The results clearly indicate that the differences in percent empty miles by truck body type are significant. The van body type (dry van and reefer) has the least percent of empty miles. This can be explained by the flexibility or versatility of this body type in commodity movement as noted above. Also, the percent of empty truck miles for a given body type is not necessarily the same across all vehicle groups. For example the percent for tank body types for straight trucks is not necessarily the same as the percent of empty tractor-semitrailers with tank body type. This is depicted in Table 3.4 and illustrated in Figure 3.6. Based on these findings, different percent empties were established for each vehicle group and body type as summarized in Table 3.4.

Table 3.4:  Summary of Percent Empty Trucks

Body Type	Percent of Empty Trucks (%)
	Straight Truck	Truck + Trailer	Tractor Semitrailer	Tractor Double Trailer	Tractor Triple Trailer
Automobile			28
Livestock			42	34
Bulk	44	28	43	40	12
Flatbed	29	34	32	40	7
Tank	35	37	43	44
Van	25	16	21	10	14
Reefer	20	17	19	26
Logging	49	44	44	28
Other	22	12	51
National Average	29	24	27	24	19

The analyses yielded percentages of trucks in each vehicle group and body type that were operated in an empty conditions. These represent the relative percentage of empty movements versus loaded movements for each body type and truck configuration. The percentages shown in Table 3.4 were applied to each of the loaded movements to estimate the number of empty truck trips.

 

Note: Insufficient data available for tractor trip trailer combinations

Figure 3.6:  Percent of Miles Empty by Body Type

 

 

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