Safety Belt Usage by Commercial
Motor Vehicle Drivers
Purchase Order No. DTMC-01-P-00071
FEDERAL MOTOR CARRIER SAFETY ADMINISTRATION
CENTER FOR APPLIED RESEARCH, INC.
Richard L. Knoblauch
Rita Furst Seifert
TABLE OF CONTENTS
Executive Summary ------------------------------------ ii
A. BACKGROUND 1
B. PURPOSE AND SCOPE OF THE PROJECT 1
C. DATA COLLECTION PROCEDURES 1
Imaging Techniques 1
Pilot Testing of Observational Procedures 2
D. SAMPLING METHODOLOGY 3
Sample of States 3
Sample of County Groups 3
Selection of Observation Sites 6
E. OBSERVATION PROCEDURES 7
F. RESULTS 8
Usage Rates - Truck Class 9
Usage Rates - Fleet Type/Truck Type 10
Usage Rates - Location/Day of Week/State 12
APPENDIX A - MEMO FROM WESTAT DESCRIBING SELECTION
OF STATES AND COUNTY SAMPLES WITHIN STATES 15
APPENDIX B - SITE LOCATIONS 21
LIST OF FIGURES
Figure 1. Safety Belt Usage Rate of Drivers by Vehicle Type and Class of Truck 9
Figure 2. CMV Safety Belt Usage Rate by Fleet Type 10
Figure 3. Safety Belt Usage Rate by Trailer Type and HAZMAT/Not HAZMAT (Class 8 only) 11
Figure 4. Safety Belt Usage Rate by Type of Location 12
Figure 5. Safety Belt Usage Rate by Day of Week 13
Figure 6. Safety Belt Usage Rate by State for Passenger Vehicle Drivers and Commercial Vehicle Drivers 14
Approximately 5,000 people are killed annually in accidents involving large trucks. Although less than 20% of the fatalities in such crashes are occupants of the truck, the truck occupant is often killed in situations that may be preventable. In single-vehicle crashes where the driver runs off the road and rolls over or hits a large stationary object, many drivers die because they fail to wear a safety belt.
Prior to this study, there were no reliable statistics regarding the level of seat belt usage among commercial motor vehicle (CMV) drivers. Although, the National Highway Traffic Safety Administration (NHTSA) has conducted a number of seat belt studies, they have been limited to only automobile occupants.
The scope of this study was to design and implement a nationally representative sample survey of seat belt usage among commercial motor vehicle drivers and, based on the data collected, to produce estimates of seat belt usage rates for this segment of the driving population.
The Federal Motor Carrier Safety Administration (FMCSA) will use the data to determine how best to allocate its resources to achieve its goal of 1.65 fatalities per 100 million truck vehicle miles traveled by 2008, and to increase seatbelt use among commercial vehicle drivers.
A three-stage sampling procedure was used in this study, conducted in 2002. In the first stage, a sample of twelve states was selected, using a "probability proportional to size" systematic sampling procedure, with state truck vehicle miles traveled (VMT) as the size measure.
In the second sampling stage, counties in each selected state were combined to form groupings that had a minimum of 300 limited-access highway miles. Once these county groups were formed, one county group was randomly selected from each selected state.
In the third sampling stage, observers visited each sampled county group, and selected locations, using county and city maps, where the safety belt usage of commercial trucks could be observed. When a potential observation site was identified, its truck volume was measured. If the site had at least two commercial vehicles passing through it within a five-minute interval, it was used for data collection. There were a total of 117 observation sites used in the study. Most of the sampled states had at least 10 sites.
Shoulder belt usage in all Class 7 (six to nine tires) and Class 8 (10 or more tires) trucks was observed at each selected site. Observations were made over a two-day period in each of the 12 states. A minimum of 10 hours was spent collecting data in each state. Of the vehicles observed in the study, roughly 10% were Class 7, and the remaining 90% were Class 8. Vehicles in Classes 1 through 6, with gross-vehicle-weights of less than 26,000 lbs., were not observed.
A total of 3,909 trucks were observed. The overall safety belt usage rate for commercial vehicles observed in the study was 48%, with a standard error of 1.4% (standard errors were generated using the WesVar software program developed by Westat, Inc.). Class 7 trucks, those with at least six tires, but less than 10, had a safety belt usage rate of 54%. Class 8 trucks, those with more than 10 tires, had a usage rate of 47%. This compares to a usage rate of 79% percent for all passenger vehicles (U.S. DOT NOPUS Survey, June 2003).
The usage rate for those units where the vehicle's tractor was identified as a major regional or national fleet was estimated to be 55%. For trucks that were either independent or part of local fleets, the usage rate was estimated to be 44%.
Seat belt rates were also estimated by commercial vehicle type, and by the presence of hazardous materials (HAZMAT). The vehicle type with the highest usage rate was found to be the single tanker (61%), and the vehicle type with the lowest usage rate was found to be the single-trailer dump truck (26%). Drivers of trucks pulling trailers placarded for HAZMAT were found to have the highest safety belt usage rate of all of the various categories observed (67%).
In recent years, approximately 5,000 people are killed annually in accidents involving trucks. Less than 20% of these fatalities are occupants of the truck. Due to the sheer mass of a commercial vehicle (CMV), often the safest place in an accident is inside the truck. Unfortunately, most accidents that are fatal to truck drivers involve running off the road and rolling over, or hitting a large stationary object (e.g., tree, bridge abutment, culvert, etc.). Many of those killed in these types of crashes died because they failed to wear their seat belts and were thrown from the CMV.
At present there are no reliable statistics regarding the level of seat belt usage by CMV drivers. NHTSA has conducted a number of seat belt studies but they have been limited to automobile occupants.
B. PURPOSE AND SCOPE OF THIS PROJECT
With the FMCSA's goal to reduce the large truck fatality rate to 1.65 fatalities per 100 million truck vehicle miles traveled by 2008, knowledge of the current seat belt usage rate by CMV drivers would help the agency determine how best to allocate resources and evaluate outreach and education strategies to increase seat belt usage.
The scope of the study was to develop a nationally representative sample survey of seat belt usage by CMV drivers throughout the United States, and collect the data to determine the baseline usage rate.
C. DATA COLLECTION PROCEDURES
The development of the data collection protocol involved two specific activities. First, a wide variety of photo-imaging techniques were investigated. Once it was determined that the development of sophisticated automatic imaging techniques was beyond the scope for this study, procedures to be followed for a manual observation protocol were developed. These two processes are described below.
A variety of different photo imaging techniques were investigated. These include videotape; digital cameras and high-speed digital flash imaging. Both the videotape and digital camera provided an inadequate image of the trucks observed. Visibility issues, especially glare, made many of the images very difficult to accurately code.
One of the photo imaging techniques examined did provide fairly reliable images of the truck drivers' restraint usage. The technique was developed for a racial profiling study on the New Jersey Turnpike. It uses still digital images, a flash is used to minimize glare, and allow night data collection. Unfortunately, the procedure requires that a van be set up along the shoulder and a flash is activated as the truck passes, raising serious issues regarding observer safety and inconspicuousness. The technique would also require that permission be obtained from the cognizant agency at each study site. For these reasons, this technique was not used for this project.
Manual Observation Protocol
Extensive pilot testing of various manual observation procedures were conducted in six states: Virginia, Illinois, Indiana, Ohio, Pennsylvania, and Maryland. The pilot testing determined what types of observational procedures could identify safety belt usage by commercial motor vehicle operators. Since commercial motor vehicles vary greatly in size, the approach must be flexible enough to allow observations of many different vehicle types at many different types of locations. Observing commercial vehicle belt use is also complicated by the presence of small windshields, small side windows, tinted windshields, tinted and mirrored side windows, wide windshield center divider strips, oversize rear view mirrors, objects hanging from rear view mirrors, objects and wires hanging from cab roof, sun visors, windshield wipers that park in the up position, and large overhanging windshield sun shades.
The following technical issues were considered when developing the observational protocol:
- Safe and Inconspicuous - The protocol must be safe for the observers and inconspicuous to the trucks being observed.
- Replicable and Accurate - The protocol must be one that can be accurately done by different observers at different types of locations across the country.
- Flexible - The protocol must be one that will work equally well across a wide variety of truck types at a wide variety of locations.
- Comparable - The protocol should be one that allows comparisons to be made with the National Occupant Protection Use Survey (NOPUS).
- Logical/Defensible - The protocol should avoid those situation/locations that may affect belt usage (e.g., toll plazas and weigh stations where police presence may change driver behavior).
It was concluded that standard visual observation provides the best method for observing commercial truck drivers' seat belt usage. This method allowed researchers to deal with most of the driver and vehicle factors, a variety of weather conditions, and site types. The method also allowed the observer the flexibility needed to avoid appearing conspicuous.
Manual observations were used at many different types of locations including: rest areas, truck stops, and exit ramps on or near interstates. In addition, it also worked well at signalized intersections on major and minor arterial roadways. It was possible to capture all truck types at each of these types of sites.
The manual observational procedure allowed the observer to move around and gain the best observation angle. At many locations it was possible to see vehicles as they arrive, wait, and pass the observer. At locations where the driver negotiated a turn the variety of angles available for observations was increased. Observer positioning flexibility also made it possible to work with windshield glare issues and use the sunlight to the observer's advantage.
D. SAMPLING METHODOLOGY
A three-stage sample selection procedure was used. In the first stage, a sample of twelve states was selected. At the second stage a sample of one county group was selected from each of the twelve states. At the third stage, observations were done at locations in each sampled county group.
Sample of States
States were sampled with a probability proportional to total truck vehicle miles traveled (VMT). Data on truck VMT as of October 2001 was obtained from the U.S. Department of Transportation. States were sorted by Census region, two urbanicity categories within each region, and truck VMT within urbanicity category. The four Census regions are Northeast, North Central, South and West. For this survey the most relevant way to define urbanicity categories survey was on the basis of truck VMT on urban highways vs. on rural highways. States with percentage of VMT on urban highways above the median percentage for urban highways were in the high urban category, whereas other states were in the low urban category.
A systematic sample of 12 states was then selected from the sorted ordering of states using the proprietary Westat program WESSAMP (see Appendix A).
Sample of County Groups
County groupings were defined before they were selected. Since the observer planned to spend about two days collecting data in a county group from each of the 12 sample states, the county group must be large enough to have sufficient sites, but not so large that observers would spend most of their time driving from one site to another. In general, observations were to take place at rest areas, truck stops and primary and secondary roadways near limited access roads. Thus, counties that have no limited access roads are not eligible for sample selection. In general, for each sample state, contiguous counties that have some limited access roads were combined into groups that have a minimum number of 300 limited access highway miles.
Once the county groups were formed, one county group was randomly selected from each sample state. Large county groups were given a higher probability of selection than small county groups. There was no data by county on the ideal measure of size, truck VMT. In a few states, VMT for all vehicles by county was available and was used for the measure of size. For other states, the total population from the 2000 Census was used as the measure of size. Sampling was done directly proportional to the measure of size. Two other possibilities were considered: 1) Sample proportional to the square root of the measure of size; or 2) Form approximately 3 size categories for each state and assign the same measure of size for each county group within a category (with the largest size category getting the largest measure of size). In thinking about how sample weights would be determined, researchers concluded that there would be no way to determine correct weights if either of these measures of size were used, and thus decided against them.
Ten different samples of PSUs were selected in the twelve states. For each sample, the researchers determined the proportion of limited access highway mileage that is inside a metropolitan statistical area (MSA). (A PSU that had some counties inside an MSA and some counties outside an MSA was assigned a proportion based on the total limited access highway mileage in an MSA for the PSU.) The sample used had the proportion inside an MSA closest to the average estimate (expected value) across all possible samples from the set of states. See Valliant et al (2000) for a discussion of this "balanced" sampling. This methodology is not biased and assured that a bad luck sample that badly under-represents MSAs or that badly over-represents MSAs was not obtained.
Observations were conducted in Primary Sampling Units (PSUs)-groups of counties-in 12 states. The 12 states were randomly selected with the probability of selection proportional to annual truck vehicle miles traveled. The PSUs are groups of contiguous counties that have at least 300 miles of limited access roadway. The states and the sampled county group within each state are shown below:
|State||PSU - Counties|
|Arkansas|| Benton |
| || |
| Henry |
| Leslie |
| Preble |
| || |
| Snohomish||Whatcom |
Selection of Observation Sites
With the sample of county groups selected, observers visited each sampled county group and selected locations where the safety belt usage of commercial trucks could be observed. The first step in the selection of observation sites was the examination of detailed maps of the selected PSU - both county and city maps as applicable. A route through the area was laid out so that most of the major roadways, exit and entrance ramps, rest areas and truck stops could be visited.
When potential observation sites were located, the observer parked in a suitable location and began observing. If truck traffic volumes were acceptable - at least 2 commercial vehicles in 5 minutes - and the vantage point adequate, the observer began data collection. If the vantage point was not acceptable but truck volumes were acceptable, the observer attempted to find another vantage point. Once it was determined that a given location provided both adequate truck volumes and a suitable vantage point, data collection began. Thus, convenience sampling was used to select the specific observation locations. A listing of the specific location of each data collection site is included in Appendix B.
E. OBSERVATION PROCEDURE
Shoulder belt usage in all Class 7 and Class 8 trucks was observed. Observations were made over a 2-day period in each of the 12 states. A minimum of 10 hours was spent observing safety belt usage in each of the 12 states.
At each potential observation site (see previous section), the following protocol was followed:
Pilot tests potential site for 10 minutes.
- Record name of state, name of county, site number, roadway name and/or number and cross street, weather, date and begin and end time of day for each data collection session.
- Record direction of travel (e.g., site 1 = southbound; site 2 = northbound) at locations with more than one site.
- Record an observation number for each driver observed.
- Observe truck class and trailer type (e.g., class 8-flatbed; class 7-2 axle van).
- Observe fleet type (e.g., major US fleet, local carrier).
- Observe driver seat belt use, non-use or misuse.
- Observe HAZMAT placard.
- Record the data points (5, 6, 7 and 8 above) and look up to observe the next driver to arrive at the site.
- Observe alternate direction of travel, if possible, for locations where more than one site is observed simultaneously.
- Conduct observations for a minimum of 45 minutes per site.
The following data was recorded on each vehicle observed:
Shoulder Belt Usage - Yes, No, Incorrect
- Truck Type
- Class 7: Heavy Duty - 6 or more tires
- Single Van
- Single Tanker
- Single Dump
- Other (refuse, concrete, etc.)
Class 8: Heavy Duty - 10 or more tires
- Single Van
- Single Tanker
- Single Dump
- Double Trailer
- Other (refuse, concrete, etc.)
- Hazardous Materials Placard - Yes or No
- Time of Day
Data was collected in June, July and August of 2002.
Our objective was to collect an hour of data at each of 10 sites in each state, and to get about 300 observations in each state. However, locating suitable observation sites was difficult in some of the states. In some cases it was necessary to go to additional locations to obtain the desired sample. In some states additional sites could not be located so it was necessary to return to a site that had been previously productive. There were a total of 117 sites; 8 of these sites were visited a second time. The time spent at sites was an average of one hour and twenty-seven minutes in duration. The table below shows the number of sites and the total number of trucks observed in each state.
|State||Number of Observation Periods ||Percent of Total Number of Observation Periods|| Number of Trucks Observed ||Percent of Total Observations|
|Arkansas|| 9|| 7.7|| 340|| 8.7|
|California ||12 ||10.3 ||326 ||8.3|
|Georgia ||10 ||8.5 ||348 ||8.9|
|Idaho ||9|| 7.7 3||08 ||7.9|
|Illinois ||10 ||8.5 ||356 9.1|
|Kentucky ||10 ||8.5 ||326 ||8.3|
|Missouri ||7 ||6.0 ||329 ||8.4|
|Ohio ||10 ||8.5 ||353 ||9.0|
|Pennsylvania ||10 ||8.5|| 318|| 8.1|
|Texas ||9|| 7.7 ||276|| 7.1|
|Virginia ||11 ||9.4 ||313|| 8.0|
|Washington ||10 ||8.5 ||316 8.1|
| Total|| 117 ||100.0|| 3,909|| 100.0|
A total of 3,909 trucks were selected for observation. To obtain national estimates for seat belt usage, the weight for each observed truck was V./(12*nis) where V. is the estimated truck VMT for the U.S. and nis is the number of trucks observed in county group i in state s. Standard errors were computed using the WesVar software program developed at Westat, Inc. Of these 3,909 trucks the observer was unable to see belt usage in a total of 67 or 1.7% of the cases. The observer missed a total of 30 or 0.8% of the cases. A total of only 13 cases (0.3%) of incorrectly worn safety belts were observed and these cases were excluded from the analysis. All usage rate data described in this section is based on the 3,799 valid observations that were made.
Observations were made at a total of 117 locations on interstate exit/entrance ramps and near trucks stops, as well as at signalized intersections. The following shows the distribution of the different kinds of data collection locations:
|Location|| Percentage of Sites|
|Truck Stops/Rest Areas||39%|
|Signal Controlled Intersections - Primary Highways||37%|
|Interstate Exit/Entrance Ramps||15%|
|Signal Controlled Intersections - Secondary Highways||9%|
Of the vehicles observed about 10% were Class 7 (6 or more tires, commercial vehicles). The remaining 90% were Class 8 (10 or more tires). Thus, the majority of the vehicles observed were the larger commercial vehicles weighing over 33,000 lbs. gross vehicle weight (GVW). Vehicle classes 1 through 6 with a GVW of less than 26,000 lbs. were not observed.
Usage Rates - Truck Class
The overall safety belt usage rate by truck class is shown in Figure 1. Class 7 trucks, those with at least six tires, but less than ten, had a safety belt usage rate of 54%. Class 8 trucks, those with more than 10 tires, had a usage rate of 47%. The overall safety belt usage rate for all commercial vehicles was 48%, as recorded during this study in 2002. For comparison purposes safety belt usage rates from the June 2003 NOPUS survey are included in the figure. Although passenger cars (81%) and SUV/vans (83%) have relatively high usage rates, pickup trucks (69%) have a usage rate closer to that of the commercial vehicles. These data suggest an inverse relationship between safety belt usage and vehicle weight. The belt usage rate of all commercial vehicles (48%) is 31% lower than that of all passenger vehicles (79%).
Figure 1. Safety Belt Usage Rate of Drivers by Vehicle Type and Class of Truck
(Standard errors in parentheses) (Passenger vehicle data from NOPUS, June 2003), (Truck data collected in 2002)
Usage Rates - Fleet Type/Truck Type
Figure 2 shows the commercial vehicle usage rate by fleet type. The usage rates for those units where the tractor was identified as a major regional or national fleet was 55%. For trucks that were either independent or local fleets the usage rate was lower at 44%. Educational programs used by many of the major carriers may have resulted in higher usage rates among their drivers.
Figure 2. CMV Safety Belt Usage Rate by Fleet Type
(Standard errors in parentheses)
The safety belt usage rate by trailer type and the presence of hazardous materials (HAZMAT) placard is shown in Figure 3. All of the vehicles in this figure were class 8 trucks. The highest safety belt usage rates were observed among the single tankers-61%. Doubles also had relatively high usage rates at 56%. The lowest rates were seen in single trailer dumps (26%) and in bobtails (33%). The usage rate for the most common trailer type, the single trailer enclosed van, was 51%-very close to the overall average of 47% for all class 8 vehicles.
The right-hand side of Figure 3 shows the usage rates for the HAZMAT tractor-trailer combinations. The drivers of tractors pulling trailers with a HAZMAT placard displayed had the highest usage rate of any of the various categories observed-67%. Although the exact reason for this relatively high usage rate is largely conjecture, it would appear that the increased safety education and awareness that is provided their drivers may account for the higher safety belt usage rate among this group.
Figure 3. Safety Belt Usage Rate by Trailer Type and HAZMAT/Not HAZMAT
(Class 8 only) (Standard errors in parentheses)
Usage Rates - Location/Day of Week/State
The usage rates for all truck types for the various kinds of observation locations is shown in Figure 4. As discussed the observations were made at locations in the selected counties where it was possible to safely observe the driver and where a reasonable amount of truck traffic was present. The locations varied from exit and entrance ramps on interstate highways to signal controlled intersections on local highways. Similar usage rates were found at the interstate entrance and exit ramps (52%) and at locations near trucks stops near the interstates (50%). Lower, but similar, usage rates were found at signalized intersections on principal highways (44%) and at signalized intersections on secondary highways (45%).
Figure 4. Safety Belt Usage Rate by Type of Location
(Standard errors in parentheses)
Figure 5 shows the usage rate by day of week. During weekdays usage varies from a low of 46% on Mondays to a high of 50% on Wednesdays. Because the Sunday rate is so low (43%) the usage rate for weekends (45%) is lower than it is during weekdays-49%. This usage pattern is exactly reverse of what is seen in passenger vehicles. Passenger vehicle usage tends to be 2% or 3% higher on weekends for drivers. Usage rates for passengers in passenger vehicles are typically 5% or 6% higher on weekends.
Figure 5. Safety Belt Usage Rate by Day of Week
(Standard errors in parentheses)
Figure 6 shows the safety belt usage rate by state. Usage rates for all passenger vehicles observed in the 2001 State belt use surveys and for the commercial motor vehicles observed in this study are shown. The commercial vehicle safety belt usage rates vary from a low of 41% in Texas to a high of 58% in Washington State. The passenger vehicle usage rate shows considerably more variation than the truck data. Usage varies from a low of 55% in Arkansas to a high of 91% in California. Arkansas had average (48%) commercial vehicle belt usage and California had below average commercial vehicle belt usage (46%). The highest commercial vehicle usage state, Washington, also has relatively high passenger vehicle usage-83%.
It should be noted that the stratified sample of states was randomly selected to be nationally representative. The reader should be cautioned that additional analyses of selected subsets of the sample (e.g., geographic regions, primary/secondary seat belt laws) were not the objective of the sampling procedure and would not be appropriate.
Figure 6. Safety Belt Usage Rate by State for Passenger Vehicles and Commercial Vehicle (Standard errors in parentheses) Passenger Vehicle Data Source: 2002 State belt use surveys conducted in accordance with section 157 of title 23, United States Code. Commercial Vehicle Data Source: FMCSA Safety Belt Usage Study, Sept. 2003
MEMOS FROM WESTAT DESCRIBING
SELECTION OF STATES AND COUNTY SAMPLES WITHIN STATES
AND THE CALCULATION OF SAMPLE WEIGHTS
This memo specifies how Westat researchers will sample states for the U.S. Dept. of Transportation survey of seat belt use among commercial trucks. First, Westat will sample 12 or 13 states with probability proportional to Total Truck Vehicle Miles Traveled (VMT) using WESSAMP. Then county level truck VMT data will be obtained for counties in the sampled states by other project staff. Westat will then group counties in each sampled state using WESPSU, after eliminating counties containing no Interstate highways. A sample of county groups will be selected with probability proportional to size using WESSAMP. Within each sampled county group, data collectors will be sent to observe seat belt use at truck stops along the Interstates or highway access ramps. The truck stops and other observation points will be chosen as a convenience sample by the data collectors.
State Sampling Frame
The input file for sampling states will be an Excel spreadsheet called TRUCKS2000.XLS (see attached). This spreadsheet should be converted to a permanent SAS file named TRUCKS2000 containing 51 records: one for each state, plus the District of Columbia. The variables should be STATE, REGION, RURALVMT, PctTruckRural, URBANVMT, PctTruckUrban, TotalTruckVMT, PctUrbanTruckVMT. Run a PROC CONTENTS and PROC FREQ on each variable.
Labels STATE = "State Name"
REGION = "Census Region"
RURALVMT = "Annual VMT for Rural Highways"
URBANVMT = "Annual VMT for Urban Highways"
PctTruckRural = "Pct of Annual Rural VMT for Trucks"
PctTruckUrban = "Pct of Annual Urban VMT for Trucks"
TotalTruckVMT = "Total Annual VMT for Trucks"
PctUrbanTruckVMT = "Pct of Total Truck VMT for Urban Areas"
Create a temporary input file for WESSAMP by deleting records for Alaska (AK) and Hawaii (HI) and combining the following states: Maryland (MD) with District of Columbia (DC), Rhode Island (RI) with Delaware (DE). For the combined MD, DC record, set
RURALVMT = 16104; URBANVMT = 37568; TotalTruckVMT = 4407; PctTruckRural = 11.5; PctTruckUrban = 6.8; PctUrbanTruckVMT = 58.3; STATE="MD_DC"; REGION = "S";
For the combined RI, DE record, set
RURALVMT = 4386; URBANVMT = 12213; TotalTruckVMT = 991; PctTruckRural = 9.7; PctTruckUrban = 4.6; PctUrbanTruckVMT = 57.2; STATE="RI_DE"; REGION = "NE";
(These were obtained by summing RURALVMT, URBANVMT, and TotalTruckVMT and obtaining the weighted average of PctTruckRural, PctTruckUrban, and PctUrbanTruckVMT for the two states.)
On the temporary file, create an indicator variable for Above/Below the median Percent Urban Truck VMT (PctUrbanTruckVMT) in each region as follows:
If REGION = W or S then MEDPCTURB = 30;
Else if REGION = NE then MEDPCTURB = 40;
Else if REGION = NC then MEDPCTURB = 33;
If PctUrbanTruckVMT > MEDPCTURB then HIURBTRKVMT = 1 ;
Else HIURBTRKVMT = 0;
If HIURBTRKVMT = 0 then SORTSERP = TOTALTRUCKVMT;
Else if HIURBTRKVMT = 1 then SORTSERP = - TOTALTRUCKVMT;
Labels MEDPCTURB = "Median Pct Urban Truck VMT"
HIURBTRKVMT = "1=Pct Urb Truck VMT > Median, 0=otherwise"
SORTSERP = "Third sort variable for sampling states"
HIURBTRKVMT and SORTSERP will be used as sort variables within REGION prior to sampling states. The effect of using SORTSERP in the SORTVARS parameter of WESSAMP is to create a serpentine sort on TotalTruckVMT within HIURBTRKVMT.
Create a dummy stratification variable DUMMY = 1 for every record.
Select State Sample
Select a sample of 12 states using the attached WESSAMP parameter sheet. Save the WESSAMP output sample and frame files to permanent SAS files. Run a PROC CONTENTS and PROC PRINT for both files. If the combined MD, DC or RI, DE records are sampled, split them back into separate states with the original uncombined variable values.
Output the final sample file to a permanent SAS file and an Excel spreadsheet. On the Excel spreadsheet, keep only variables STATE REGION RURALVMT URBANVMT TOTALTRUCKVMT PCTTRUCKRURAL PCTTRUCKURBAN PCTURBANTRUCKVMT.
For this survey, weighting is complicated by the fact that there is not a fixed and known probability of selection of sites and of trucks within each sampled county group. The probability of selection of states and of county groups is known. The correct weight is specified, which includes an unknown term, and can therefore not be used. An approximation is given which then permits the calculation of sample weights. Finally, the survey discusses variance estimation.
Let Vis be the estimated truck VMT for county group i in state s,
Vs = Ʃ Vis, the estimated truck VMT for state s,
Vi = Ʃ Vs, the estimated truck VMT for the US,
Mis = the measure of size for county group i used in sampling county groups in state s (in four states, the measure of size was annual VMT for all vehicle types; in the remaining eight states, the measure of size was total population),
Ms = Ʃ Mis is the sum of the county group measures of size for state s, and
nis is the number of trucks observed in county group i in state s.
The probability of selection for a state is (12)( Vs)/V., and
The probability of selection for a country group is Mis / Ms.
Thus, an appropriate weight for each observed truck is
wis = [V./((12)(Vs))][ Ms / Mis][ Vis / nis].
The last term of the formula is the inverse of an estimate of pseudo sampling rate of trucks within in a county group. Note, however, that Westat does not have a probability selection of sites or trucks within a county group, and thus the probability of selection can vary considerably for different trucks within a county group. Westate has no way to account for this.
All quantities in this formula are known, except for Vis, the county-level truck VMT. Without Vis, the formula cannot be directly applied. If the following approximation holds, however, then Vis is not needed:
Mis / Ms = Vs /Vis
Westate then has wis = V./(12 nis). I recommend that this weight be used. For seat belt use rates, the value for V is not important, as it occurs in both the numerator and denominator of a rate. The national seat belt use rate R can be estimated as:
R = Ʃ wis Xis
? wis Yis
Where Xis = the number of belted truck drivers observed in county group i, Yis= the number of truck drivers observed in each county group i, and wis is the weight for observed trucks in the I-th county group. Note that each observed truck in the I-th county group gets the same weight in this formula.
SELECTED MEASURES FOR STATES
ANNUAL VEHICLE-MILES OF TRAVEL
RURAL URBAN TOTAL PERCENT
ANNUAL PERCENT ANNUAL PERCENT TRUCK URBAN
State Census Region VMT TRUCKS 3/ VMT TRUCKS 3/ VMT TRUCK VMT
Montana W 7,590 14.2 2,292 2.9 1,144 6%
Wyoming W 5,855 29.9 2,235 12.3 2,026 14%
New Mexico W 14,526 22.6 8,234 10.6 4,156 21%
Idaho W 8,549 19.4 4,985 9.3 2,122 22%
Alaska W 2,374 11.1 2,239 4.5 364 28%
Oregon W 18,689 16.9 16,321 7.7 4,415 28%
Nevada W 5,862 21.3 11,777 5.6 1,908 35%
Utah W 8,585 15.5 14,012 5.1 2,045 35%
Colorado W 16,480 14.0 25,291 4.9 3,546 35%
Arizona W 17,860 23.7 31,908 12.8 8,317 49%
Washington W 17,202 15.9 36,128 7.4 5,409 49%
Hawaii W 2,451 4.0 6,092 2.6 256 62%
California W 59,567 15.0 247,082 6.9 25,984 66%
Alabama S 28,873 5.3 27,661 1.6 1,973 22%
Arkansas S 18,736 16.4 10,431 8.7 3,980 23%
Mississippi S 24,416 18.1 11,120 11.8 5,731 23%
South Carolina S 29,009 12.1 16,529 6.7 4,618 24%
West Virginia S 13,955 14.3 5,287 12.8 2,672 25%
Oklahoma S 21,697 20.7 21,658 7.1 6,029 26%
Kentucky S 26,760 16.4 20,043 8.2 6,032 27%
Tennessee S 30,487 16.5 35,245 8.0 7,850 36%
Louisiana S 22,167 17.3 18,682 11.6 6,002 36%
Texas S 74,002 20.2 146,062 7.0 25,173 41%
Georgia S 47,523 12.9 57,487 7.8 10,614 42%
North Carolina S 44,140 12.4 45,364 9.2 9,647 43%
Virginia S 32,252 14.6 42,549 8.6 8,368 44%
Maryland S 16,104 11.5 34,070 7.1 4,271 57%
Delaware S 3,267 11.5 4,973 9.9 868 57%
Florida S 38,100 14.2 114,036 6.9 13,279 59%
Dist.of Columbia S - 0.0 3,498 3.9 136 100%
Maine NE 10,477 7.0 3,713 2.4 823 11%
Vermont NE 4,862 9.9 1,949 8.2 641 25%
New Hampshire NE 7,083 7.5 4,938 6.7 862 38%
Pennsylvania NE 45,820 15.0 56,517 8.1 11,451 40%
New York NE 36,715 11.2 92,342 5.4 9,099 55%
Rhode Island NE 1,119 4.5 7,240 1.0 123 59%
New Jersey NE 13,606 3.7 53,840 1.5 1,311 62%
Connecticut NE 7,709 7.8 23,047 5.9 1,961 69%
Massachusetts NE 8,823 2.2 43,973 1.1 678 71%
North Dakota NC 5,372 15.0 1,845 4.3 885 9%
South Dakota NC 6,519 15.9 1,913 6.6 1,163 11%
Nebraska NC 11,227 19.2 6,854 5.1 2,505 14%
Kansas NC 14,855 18.6 13,275 5.5 3,493 21%
Iowa NC 18,786 15.9 10,647 8.2 3,860 23%
State/Site Number Location
- Fina Fuel Stop and J & H Restaurant parking lot, exit 106 of interstate 30, State route 67, westbound traffic
- Same as site 02, eastbound traffic
- Rest stop along Interstate 30 at about milepost 96, located in median for eastbounders and westbounders, westbound traffic
- Same as site 03, eastbound traffic
- Pilot Truck Stop parking lot, interstate 30 exit 121
- Parking lot of Walgreen Pharmacy, intersection of State route 70 and 270 B (business), town of Hot Springs, all legs of intersection
- Phillip 66 Travel Center, exit 44 of interstate 30, any direction of travel
- Flying J Travel Center, parking across the street at Red Barn BarBQ, exit 7 of interstate 30 near exit ramp, eastbound traffic
- Same as site 08, westbound traffic
- State route 111 southbound at Cole Road, near interstate 8, Calexico
- Same as site 01, northbound traffic
- Imperial Ave. exit from interstate 8 westbound traffic, on and off ramp
- Intersection of Highway 905 at Airway Blvd, near Otay Mesa International Center, Chula Vista, Highway 905 both directions of traffic
- Same as site 04, Airway Blvd both directions of traffic
- Intersection of Highway 905 at La Media Road, Chula Vista, Highway 905 both directions of traffic
- Same as site of 06, La Media Road both directions of traffic
- Grape Street and State Street at on ramp to interstate 5, northbound and southbound traffic, downtown San Diego
- Oceanside Blvd. at off ramp from interstate 5, Oceanside, California, both directions of travel, Oceanside Blvd and northbound traffic on ramp to interstate 5
- Same as site 09, northbound traffic off ramp from interstate 5 to Oceanside Blvd
- Intersection of Highway 905 at Heritage Drive, Chula Vista, Highway 905-both directions of traffic
- Same as site 11, Heritage Drive southbound traffic
State/Site Number Location
- Intersection of state routes 211 and 124, near exit 126 of interstate 85, route 211 both directions of traffic
- Same as site 01, route 126 both directions of traffic
- Pilot Truck Stop, exit 51 of interstate 285, southeast of Atlanta
- Boulder Crest Road, near junction of interstates 285 and 695, exit 51 of interstate 285
- Parking lot of T/A Motel and Travel Center near junction of interstates 285 and 675, junction is exit 52, traffic entering truck stop
- Intersection of Thurman Drive and McDonaugh Drive, all directions of traffic but not entering truck stop at site 05
- Williams Truck Stop, exit 221 of interstate 75
- Junction of routes 138 and 23, City of Stockbridge, near interstate 75, all directions of traffic
- Flying J Truck Stop, exit 201 of interstate 75
- T/A Travel Center, exit 201 of interstate 75
- Flying J Truck Stop, at state routes 20/26, exit 29 of Interstate 84
- Flying J Truck Stop at Federal Way, near exit 54 of interstate 84
- T/A Travel Center at exit 54 of interstate 84
- Boise Stage Stop, exit 71 of interstate 84, eastbound traffic
- Same as site 04, westbound traffic
- Pilot Truck Stop at Mountain Home, at exit 95 of interstate 84, both directions of travel
- Flying J Truck Stop, near Bliss, exit 137 of interstate 84
- Eastbound exit 157 ramp of interstate 84
- Westbound exit 157 ramp of interstate 84
State/Site Number Location
- Intersection of state route 59 at New York and Aurora Avenues, both directions of traffic on state route 59
- Same as site 01, New York Ave. traffic
- Intersection of state routes 64 and 53, near interstate 355, eastbound traffic of route 64
- Same as site 03, westbound traffic of route 64
- Same as site 03, both directions of traffic route 53
- Junction of state route 60 at exit from interstate 94, route 60 both directions of travel and entrance ramp to southbound interstate 94
- State route 31 near interstate 90, exit Elgin, southbound traffic
- Same as site 07, northbound traffic
- Intersection of state route 30 at Douglas Street, all directions of traffic
- Citgo Truck Stop, intersection of state routes 30 and 47, near interstate 88, all directions of traffic
- State route 25, exit 29 of interstate 75, eastbound direction of traffic
- Same as site 01, westbound direction of traffic
- Pilot Truck Stop, exit 29 of interstate 75
- Citgo Truck Stop, exit 29 of interstate 75
- BP Truck Stop, route 80 at exit 41 of interstate 75
- Intersection of state routes 80 and 421, Manchester, near exit 20 of Daniel Boone Parkway Toll Road, route 80 both directions of traffic
- Same as site 06, route 421 both directions of traffic
- State route 80, exit 41 near interstate 75, eastbound direction of traffic
- Same as site 08, westbound direction of traffic
- Southbound exit ramp 41 of interstate 75
State/Site Number Location
- T/A Travel Center at exit 58 of interstate 70, eastbound traffic
- Same as site 01, westbound traffic
- Pilot Truck Stop at exit 101 of interstate 70, Booneville, and both directions of traffic
- State route 54, Petro and Conoco Truck Stops, coming and going from state highway and interstate 70 at exit 148
- State route 54, northbound and southbound near exit 148 of interstate 70 and interstate users, near McDonalds, Texaco and Phillips 66
- State route 54, eastbound traffic, near exit 148 of interstate 70
- Exit 121 of interstate 70, near Budget Inn and Conoco, both directions of traffic
- Pilot Truck Stop, state route 127, exit 10 of interstate 70, and eastbound traffic
- Same as site 01, westbound traffic
- BP Fuel Stop, state route 127, north of exit 10 of interstate 70
- Intersection of state route 127 at Lexington and Barron, Town of Eaton, route 127 traffic both directions
- Same as 04, Lexington Street and Barron Street traffic
- Intersection of state route 4 (truck route) and state route 129, route 4 both directions of traffic
- Same as site 06, route 129 both directions of traffic
- Intersection of State route 63 near interstate 75 south exit ramp number 29, route 63 westbound traffic
- Same as site 08, route 63 eastbound traffic
- Same as site 08, cross street traffic near Town of Monroe
State/Site Number Location
- Pilot Truck Stop adjacent to exit 32B of interstate 70, Bentleyville/Ginger Hill, westbound traffic
- Same as site 01, eastbound traffic
- Rest area near milepost 51 located on interstate 79 northbound, south of Pittsburgh
- Junction of state routes 30 and 18, Harshaville, all traffic directions
- Citgo Truck Stop, exit 1 northbound of interstate 79, northbound traffic
- Same as site 05, southbound traffic
- Petro Travel Center, exit 6 of interstate 70, westbound traffic
- Same as site 07, eastbound traffic
- Exit 19 of interstate 70, westbound traffic
- Same as site 09, eastbound traffic
- Love's Travel Stop, exit 142 of interstate 35, just outside of interstate 410, northbound traffic
- Intersection of state route 90 and county route 462-Avenue E, Town of Hondo, route 90 both directions of traffic
- Petro Truck Stop, exit 582 eastbound of interstate 10
- Pilot Truck Stop, exit 582 of interstate 10
- T/A Travel Center, exit 583 of interstate 10
- Flying J Truck Stop, exit 583 of interstate 10
- Texaco lot, exit ramp 585 of interstate 10
- Conoco Fuel stop, route 1604 (outer beltway loop), from interstate 37
- Same as site 01, southbound traffic
State/Site Number Location
- Petro Truck Stop at exit 29 of interstate 81, Glade Spring, northbound traffic
- Same as site 01, southbound traffic
- Intersection of state routes 11/19 at State Street, City of Bristol near Old Bristol Business Center, State Street westbound traffic
- Same as site 03, Route 11/19 northbound traffic
- Same as site 03, Route 11/19 southbound traffic
- Same s site 03, State Street eastbound traffic
- T/A Travel Center, town of Max Meadows, exit 41 of interstate 77
- Flying J Truck Stop, exit 77 of interstate 81, four way stop, northbound and southbound exit ramps
- State route 58 at route 2213, exit 14 of interstate 77, near Hillsville, southbound traffic
- Lancer Travel Center, state route 660, Clayton Lake, near exit 101 of interstate 81, exit ramp traffic
- Same as site 10, Travel Center traffic
- Intersection of Route 99-International Blvd. and 200th Street, City of Seatac, about 1-2 miles from interstate 5. International Blvd. traffic both directions
- Same as site 01, 200th Street, traffic both directions
- Intersection of State route 2 at Kelsy Street, City of Monroe, eastbound traffic
- Same as site 03, westbound traffic
- Exit roadway from interstate 5, exit 275, Blaine near customs to British Columbia, traffic going to Canada
- Same as site 05, traffic coming from Canada
- Interstate 5, exit 230-Burlington/Whidbey Island, on ramp traffic
- Same as site 08, off ramp traffic
- State route 18 at 244th Street, SE, King County, Route 18 traffic both directions
- Interstate 90, exit 25, exit ramp, eastbound traffic and westbound traffic