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Commercial Driver Rest Area Requirements:
Making Space For Safety
Appendix C - How to Determine Commercial Drivers'
Requirements For Parking at Rest Areas
Report No. FHWA-MC-96-0010
Prepared by:
Trucking Research Institute
2200 Mill Road
Alexandria, VA 22314-4677
Apogee Research, Inc.
4350 East West Highway, Suite 600
Bethesda, MD 20814
Wilbur Smith Associates
2921 Telestar Court
Falls Church, VA 22042
Prepared for:
Federal Highway Administration
U.S. Department of Transportation
400 7th Street, SW
Washington, DC 20590
February 1996
Purpose and Organization of the Guide
The purpose of this guide is to help state and FHWA transportation officials develop a successful "safe rest area" program that meets the needs of commercial drivers and the traveling public. The process requires that a need or demand be identified, that the extent of that need be determined and that solutions be developed through an orderly planning process. This guide will answer most, if not all, of the questions likely to arise, including:
A good "safe rest area" program requires sound approaches to planning, location and design and is fully integrated with the state's transportation program. This introduction describes why this issue arose, how to implement such a program and how to use this guide. Subsequent sections provide instructions oh how to implement the process, from inventorying resting facilities to administering the survey, applying the model and analyzing and reporting the results. A rest-area form has been appended.
Motivation for Improving Truck Parking at Rest Areas
Rest areas on interstate highways are heavily used by trucks, particularly during the late evening and early morning hours. Many were built early in the interstate program to a design that typically provided about 35 diagonal parking spaces for cars and 12 parallel spaces for trucks. Because commercial drivers are reluctant to back parallel or out of double pull-through spaces, these spaces are not used efficiently and, as a result, the 12 spaces may contain only 6 to 8 trucks at any time.
Although, this parking capacity has been expanded in some areas and provisions for truck parking in some areas are much improved, most rest areas, including those on the Primary system of highway, now lack sufficient truck parking space. Consequently, overflow parking of trucks occurs on shoulders of entrance and exit ramps. There is a perception that commercial drivers who cannot find space at rest areas may park on entrance and exit ramps at nearby interchanges. In addition to damaging shoulders and adjacent highway appurtenances, this practice reduces the available pavement width and sight distance on both types of ramps, creating traffic safety hazards.
While some states are improving existing facilities, other have been identifying rest areas for closure because funds are not often available for improvement. The passage of the Intermodal Surface Transportation Efficiency Act of 1991 (ISTEA) has made funds available to upgrade highways of national significance. These upgrades should include consideration of the strategic locations of rest areas, service areas (on system and off system) and multiple bottom assembly and breakdown locations. Optimizing the location of and access to such facilities will contribute greatly to the overall efficiency, security and safety of truck transport and the safety and efficiency of the National Highway System.
Several issues have been identified:
How States Should Use This Guide
This guide will help planners collect the information needed to assess how effectively the public rest-area program for commercial drivers performs its functions. It can be used to
How to Determine Commercial Driver Rest Area Requirements
The process of determining commercial drivers' requirements consists of activities that contribute to the overall goal of assessing current demand/capacity for truck parking at highway rest areas. This process consists of four distinct research activities: an inventory of state highway rest areas; a direct observation survey of actual truck parking activities; a survey of commercial driver habits, attitudes and preferences; and use of a truck parking demand model. This process is most effective when state DOTs conduct there activities as the following tasks:
Each task is detailed in a separate section. Each section discusses the goals of the task, the research methodology, implementation issues and the relationship of each task to the process as a whole.
Task 1. Inventory of Highway Resting Facilities
In Task 1, DOTs should conduct an inventory of highway public rest-area facilities in their states. The purpose is to collect information needed for the truck parking demand model in Task 4. This information includes site location, physical facilities, day and night use patterns and traffic statistics. An inventory data collection sheet is included in Appendix A.
A complete detailed inventory of public rest areas is essential for determining rest-area demand and capacity. The data supplied to FHWA to conduct this study on commercial driver rest-area requirements should be verified as a first step. The data submitted by agencies responsible for highway rest areas (primarily state DOTs) were used to create the truck demand model for predicting rest-area parking requirements for commercial vehicles. Some key data elements are necessary to refine the model even further:
These data elements will play an important role in the accuracy of the model.
The inventory of highway rest area facilities should include the following data elements:
Data should be collected using the form in Appendix A; the data may then be entered into a computer spreadsheet (e.g., Microsoft Excel, Lotus 1-2-3, dBase) for analysis.
Task 2. Direct Observation of Rest Area/Truck Stop Use
In Task 2, DOTs should identify the important trucking corridors in their states and conduct a direct observation survey along each corridor. This survey ideally would be conducted at all public rest areas and truck stops in the state but also be conducted on a more limited scale if necessary. It will provide primary data to feed into the truck parking demand model, as well as information for DOTs on how commercial vehicles actually use the highway rest areas in their states.
The primary goal of the survey is to collect data that can be used to meet the goals of the entire process:
The primary data collected will help determine actual demand for parking spaces - and whether current facilities are adequate to meet that demand. Systematically observing and recording the actual usage of truck parking spaces will generate empirical data on supply and demand that are not available from any other source. Analyzing these data will help identify and quantify the characteristics of parking facilities that account for utilization and demand, particularly during peak periods.
Observer teams should conduct a trial run of the observation procedures before the actual survey, o they become comfortable with the methodology and resolve any questions. State agencies responsible for maintaining highway rest areas, as well as the highway patrol, should be notified of the dates and times of the survey for the safety of the observers. Observers should be paired and instructed to check in and make regular status calls by telephone, as a standard precaution. A supervisor should also make on-site visits to ensure that all activities conform to proper procedures and quality assurance measures.
The steps involved in implementing the survey are as follows:
Step 1. Select Trucking Corridors
Selecting the appropriate corridor(s) to study depends on the priorities each DOT has identified. The following criteria should be considered when choosing a corridor:
Step 2. Select Individual Sites
The sites will be determined by the choice of corridor, and the precise timing and number of observation shifts will depend on local logistics and budget constraints. Sites should be selected with the corridor selection criteria in mind; that is, they should be accessible to observer teams and offer suitable access points for observers to perform their responsibilities safely, effectively, and efficiently. If private truck stops are included, permission must be obtained from the truck stop operator before observation activities can be conducted at the facility.
Step 3. Measure Demand and Capacity
To gather the level and type data needed, the survey plan calls for making direct observations at each monitoring site along the corridor during peak periods of use of over a five-day period. Observers must work in pairs during specific nighttime shifts at each site throughout the five-day period to ensure accurate data collection and personal safety.
Rest Area Observations
Each team of observers must be trained and instructed to record the parking
activities of tractor-trailers during their watch at their truck parking facility.
Observations should be made every half-hour from 10 p.m. to 6a.m. at each site
from Sunday through Thursday. Observations should be made simultaneously at
each site for a total of 18 observations per night per site1.
This schedule is the most cost-effective way to measure the rise and fall of
demand in peak usage periods (based on anecdotal and qualitative information
indicating that long-term parking needs diminish during that day and on Friday
and Saturday evenings).
Observers should be given a map of the rest area with numbers to each designated parking place that could be used by trucks. They should inspect the parking spaces at the top and bottom of each hour during their shifts. During each inspection, they should identify each specific truck using each space, by noting the type of truck and by using the letters and digits from a license plate or company marking. Observers should also note when a space is not occupied. Observers should count the number of trucks parked in unauthorized spaces or on the rest area ramps, within visual range, as well. They should mark their observations in each parking space on their site maps (see Chart 1). Approximate measures of length of stay will be inferred from these data.
Observers must be trained to identify truck types. Trucks may be coded as straight trucks (not pickups), bobtails (truck cabs with trailer detached), or one of six types of tractor trailers: tanker, car carrier, flat bed, double box, normal box (van, or refrigerated), or "other." Observers should also indicate whether the truck has a sleeper cab.
The observation teams should be instructed to make their observations from a distance and should wear safety -colored reflective clothing or baseball caps to identify themselves as part of the survey team. For safety reasons, they should not be asked to walk along the interstate or the rest area ramps.
A More In-Depth Approach
The plan described above dictates that observations be made twice an hour to
allow for better analysis of truck turnover per space. Ideally, the analysis
of space turnover would be conducted as a separate but concurrent activity for
a number of nights, or instead of the twice-hourly observations for the duration
of the survey. A group of observers could be assigned to monitor all parking
activities for every space, noting times of arrival and departure. Conducting
such an intensive data collection would provide a key variable, Vehicles per
Hour per Space (VHS), for input to the parking demand model, a variable that
is not currently available. Should a state decide to collect data in this manner,
the specifications for the capacity utilization may be altered and a figure
from the direct observation survey could be used. This option is discussed further
in Task 4.
Truck Stop Observations
The plan for conducting the survey of truck parking at private truck stops differs
somewhat. Here, the observer teams simply count the total number of trucks parked
in each facility at the top and bottom of each hour, marking their totals on
their site maps (see Chart 1). Conducting the
complete, space-by-space identification of trucks in these facilities has been
deemed to be unsafe because of the amount of moving truck traffic in the parking
areas.
Truck Traffic Counts
In order to link demand for truck parking on the corridor to ADT data, observer
teams at all sites should count the number of trucks passing their sites. A
15-minute count of truck traffic should be performed at each site once each
hour. These figures can then be multiplied by four to get and estimate of hourly
truck traffic passing each site. More accurate highway ADT counts could be conducted
using electronic traffic metering equipment, if it is available. Traffic meters
would provide a more accurate ADT count and could also help determine the percentage
of truck traffic on the road. These figures will be essential inputs to the
demand model in Task 4.
From the data collected at both public highway rest areas and private truck stops, the utilization of each authorized parking space for long- or short-term parking and the total amount of "spillover" by day of week, time of day, and type of facility on that corridor will be evaluated. This will allow for direct comparisons of actual supply and demand. Additional analysis can then link location, characteristics, or features with usage patterns and possible shortages.
Data analysis first requires converting the recorded observations into a data stream that is machine-readable and interpretable for analysis and modeling. This will entail coding the observations (before entering the data) to distinguish different types of trucks, long-and short-term parking and legal and illegal parking.
Trucks should be classified by the length of their parking stay:
Trucks should be identified as "legally" parked if they are in a designated parking space. Trucks not in a designated parking space but somewhere in the rest area or on the ramps and interstate shoulder should be identified as "illegally" parked. Trucks parked along the shoulder of the interstate within site of the rest area should also be classified as "illegally" parked.
As noted above, the goal of the direct observation survey is to collect data that can be used to
The first three goals can be accomplished through the use of descriptive statistics and appropriate graphics (see Charts 2 and 3). From this information, inferences can be made about
The analysis can also include an examination of differences between the rest areas and truck stops with respect to truck type, length of stay and times of peak activity. In some cases, statistical tests such as Chi-square, t-tests, analysis of variance, or logistic regression may be used to determine whether apparent differences are statistically significant. The dependent variable in these analyses is the percentage utilization of parking spaces. Possible independent variables include the time of day, day of week, type of facility, type of services or facilities and perhaps relative location or distance measures and level of highway traffic.
ADT data on trucks may be used to establish the relationship between the proportion of traffic flow stopping at rest areas and truck stops and other independent variables noted above (e.g., time of day, day of week), but also with the distance from major cities or other rest areas and the features, services, or amenities that are available at each.
Task 3. Commercial Driver Survey
In Task 3, DOTs can conduct a market research survey of truck drivers along the selected corridors. Surveying the actual users of truck parking facilities will give a clear picture of driving habits, behaviors, attitudes and preferences. This information is invaluable for understanding the parking behavior observed during the survey in Task 2.
A survey of commercial drivers will allow DOTs to
The survey questionnaire seeks to elicit information in the following areas:
The survey research plan calls for conducting structured intercept survey interviews with commercial vehicle operators at truck stops and rest areas along a selected trucking corridor; ideally the same corridor used for the direct observation of truck parking activity. Interviews should be conducted at a combination of public rest areas and private truck stops to capture the opinions of drivers who use both types of facilities.
Interviews should be conducted by trained, professional interviewers from market research field service firms located along the corridor. Standard interview procedures and guidelines should be incorporated into training and enforced through strict monitoring and field supervision by research team members.
Interviewers should be trained to select every "nth" truck driver entering the facility. This will ensure that interviewers intercept respondents at random – not merely haphazard – manner, minimizing interviewer bias due to physical appearance, demeanor, or accessibility of individual drivers. This precaution is necessary to ensure that the sample is truly representative of the target population and not simply those drivers who are easy to approach.
Interviewers should conduct the interviews with drivers after they have left their cabs to use the rest area or truck stop. Interviews should be held during daylight hours only for interviewer safety. To encourage participation, drivers should be provided with assurances and mechanisms necessary to maintain confidentiality of their responses.
After the survey is done, the information on the questionnaires can be entered into a computer database for analysis. From this database, cross-tabular results can be printed to aid in the question-by-question analysis of driver responses.
It may have not been possible within the scope or budget of many DOTs to conduct a statewide survey. The lack of comprehensive, current and reliable mailing lists makes it difficult and cost-prohibitive to conduct an adequate mail survey with this particular target population. The low incidence of truck drivers in the general population precludes the use of random-digit dialing and screening techniques to identify qualified respondents by telephone in a cost-effective manner. Consequently, the sampling and interviewing of commercial truck drivers must be conducted in field locations where they are likely to congregate – public highway rest areas and privately owned truck stops on the interstate highway system.
Although commercial drivers at these sites are selected for interviews at random, the sample is representative only of the population of drivers who stop or travel along the selected corridor. The survey results thus cannot be projected to the population of commercial drivers statewide. Budget restrictions may require that these interviews be conducted at a limited number of sites in a concentrated area. Coupling these interviews with the direct observation exercise offers the potential advantage of establishing a closer link between the drivers' perceived needs and preferences and parking practices actually observed.
Task 4. Apply Truck Parking Demand Model
In Task 4, DOTs should apply the truck parking demand model developed by the FHWA research team to determine the demand/capacity for truck parking at highway rest areas.
Apogee has developed and tested two quantitative models to analyze public rest area usage by trucks and the need for additional truck parking spaces at rest areas along the interstates. The first model, referred to as the Capacity Utilization model, identifies the factors influencing the use of public rest area parking spaces by trucks. This model was estimated using econometric techniques with a sample of 709 rest areas located across the country. The second model, the Truck Parking Demand Model, was developed to estimate the need for additional truck parking spaces at public rest areas. This model was based on the modification of the recommendations of the 1981 Minnesota Department of Transportation (MnDOT) model for estimating truck parking spaces and the 1994 Virginia Department of Transportation (VDOT) study of the parameters used in truck parking estimation models. The findings of the Capacity Utilization model were then incorporated into the modified Truck Parking Demand model to generate the formula for predicting the need for truck parking spaces at public rest areas.
B. Overview of the Modeling Process
The fundamental unit of analysis in the modeling process is an individual public rest area. The modeling framework includes the identification of rest areas for analysis, the collection and coding of data on the variables included in the model and the application of the demand formula to estimate the need for truck parking spaces. Figure 1 provides a general outline of the modeling process. The individual steps are explained in detail below.
The modeling process for estimating the number of truck parking spaces required at a public rest area involves five steps (see Figure 1).
The first step is to identify the rest areas that are to be included in the analysis. They may range from an individual rest area to a group of rest areas along a specific corridor within the county or state. The choice should depend on the
The following list of identifiers needs to be created for each rest area:
The Capacity Utilization model developed by Apogee has identified a number of factors that affect the utilization of truck parking spaces at public rest areas. These factors are used in the demand formula in Step 4 of the modeling process. Step 2 involves the collection and coding of data for each of the capacity utilization factors identified. Table 1 summarizes the factors and data required for each factor.
| Factor | Data Required |
| One-way Average Daily Traffic (ADT) | Current ADT figures for the interstate on which the rest area is located |
| Distance from the Previous Rest Area | Distance (in miles) between the rest area being analyzed and the previous rest area on the corridor, calculated as the difference between the Milepost Numbers of the two areas |
| Distance to the Next Interchange | Approximate distance (in miles) from the rest area begin analyzed to the next interchange (e.g., interstate exit, major or minor intersection) |
| Welcome Center | Official rest area classification. Enter "Yes" if rest area is classified as welcome center, or "No" if it is not. |
| Type of Truck Parking Spaces at the Rest Area | Enter "DPT" if the truck parking spaces are the diagonal pull-through type or "NDPT" if they are not. |
| Rest Area Food Facilities | Enter "Yes" if food facilities (restaurants, vending machines, etc.) are available, or "No" if they are not. |
| Rest Area Lighting | Enter "Yes" if lighting in the rest area is considered adequate, or "No" if it is not. ("Adequacy" can be based on a survey of truck drivers or on qualitative judgement.) |
| Availability of Rest Area Attendant | Enter "Yes" if an attendant is available on rest area premises, or "No" if one is not. |
| Parking Spaces at Private Truck Stops | Current Estimate of the total number of parking spaces in private truck stops located within a radius of 10 miles of the rest area. |
After the data on the variables are collected, they must be coded to facilitate applying the decision rules in Step 3. The coding format for each variable is presented in Table 2.
| Factor | Data Coding Format |
| One-way Average Daily Traffic (ADT) | Enter data as collected |
| Distance from the Previous Rest Area | If distance from previous rest area exceeds 50 miles, code this variable as "1", if it does not, code it as "0." |
| Distance to the Next Interchange | If distance to the next interchange exceeds 10 miles, code this variable as "1", if it does not, code it as "0." |
| Welcome Center | Code all "Yes" responses as "1" and all "No" responses at "0." |
| Type of Truck Parking Spaces at the Rest Area | Code all "DPT" responses as "1" and all "NDPT" responses as "0." |
| Rest Area Food Facilities | Code all "Yes" responses as "1" and all "No" responses as "0." |
| Rest Area Lighting | Code all "Yes" responses as "1" and all "No" responses as "0." |
| Availability of Rest Area Attendant | Code all "Yes" responses as "1" and all "No" responses as "0." |
| Parking Spaces at Private Truck Stops | Enter data as collected. |
This step of the modeling process involves applying the decision rules in order to select the appropriate parameter values to use in the Apogee Truck Parking Demand model. The formula for the Demand model is as follows:
| NTSPACES
= ADT x P x DH x Dt x PF VHS |
where
| NTSPACES | = | Number of truck parking spaces required |
| ADT | = | Average Daily Traffic with access to rest areas |
| P | = | Total percentage of mainline traffic stopping at rest area |
| DH | = | Design hour usage2 |
| Dt | = | Percentage of truck parking spaces |
| PF | = | Peak factor, ratio of average day of five summer months to average day of year |
| VHS | = | Vehicles parked per hour per space |
This is the formula that will be used in Step 4 to estimate the total number of truck parking spaces required at the rest area. Before using the formula, certain assumptions regarding the values of the model parameters must be made. Table 3 summarizes the recommended parameter values based on the research findings of Apogee Research, Inc., MnDOT and VDOT. Note that these parameter values are recommended only if specific direct observation and commercial driver surveys are not conducted. Ideally, a survey would be conducted for each of the selected rest areas, in order to collect primary information on the parameter values included in the demand model.
| Parameter | Recommended Value |
| Average Daily Traffic (ADT) | Use one-way ADT data collected in Task 2 |
| Percentage of Mainline Traffic Stopping at Rest Area (P) | 0.12, plus
decision rule modifications
(explained below) |
| Design Hour Usage (DH) | Based on
decision rules
(explained below) |
| Percentage of Truck Parking Spaces Out of Total Parking Spaces at the Rest Area (Dt) | 0.25 |
| Peak Factor Ratio (PF) | 1.80 |
| Trucks Per Hour Per Truck Parking Space | 2.0 |
Decision Rules
There are no fixed recommended parameter values for the percentage of mainline traffic stopping at the rest area (P) and the design hour usage (DH). The values for these two parameters vary depending on the decision rule adopted. The decision rules for each of these parameters follow.
Percentage of Mainline Traffic Stopping at the Rest Area (P)
The Capacity Utilization model developed by Apogee identified six factors, in addition to one-way ADT, that have a statistically significant effect on increasing the usage of public rest area parking spaces by trucks:
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These factors correspond to the same variables that were recoded in Step 2. The coded values are used in the application of th edecision rule to modify the value of "P" as explained below. 3
Decision Rule 1
| Increase the default value (0.12) by 0.01 for each vaiable that ws coded as "1" in Table 2 of Step 2. |
For example, if a rest area's distance from the previous rest area was greater than 10 miles, then the parameter "P" would take the value of 0.13 (i.e., 0.12+0.01). Similarly, if the rest area's distance from the previous rest area was greater than 10 miles, AND the rest area was also classified as a welcome center, the "P" would take the value of 0.14 (i.e., 0.12+0.01+0.01). If none of the variables in Table 2 were coded as "1," than "P" would take the default value of 0.12.
Design Hourly Volume Ratio (DH)
The design hourly volume is generally considered to be the 30th highest hour of traffic flow in a year. The study conducted by the Transportation Planning Division of VDOT in 1994 suggests that as the ADT volume increases, the design hourly factor is reduced until the traffic volume reaches a particular level. The factor then stabilizes regardless of how high the average daily volume becomes. The VDOT recommendations and the findings of the study conducted by Apogee Research are used to develop the decision rules for the parameter value of the design hourly factor, "DH," as shown below.
Decision Rule 2
| For ADT Levels of
12,500 and below, use 0.15
For ADT Levels greater than 12,500 and less than 30,000, use 0.10 For ADT Levels of 30,000 and higher, use 0.075 |
The ADT data collected in Step 2 (Table 2) are used in applying this decision rule. For example, if a rest area is located on an interstate where the ADT volume is 9,600 a DH factor of 0.15 is used. Similarly, if the ADT is 26,500, the appropriate DH factor is 0.10. Finally, if the ADT is 34,000, the appropriate DH factor is 0.075.
Step 4. Estimate Truck Parking Spaces
This step involves the actual application of the Truck Parking Demand formula to estimate the total number of truck parking spaces required at a rest area. The data collected and coded in Steps 1 and 2 are plugged into the formula based on decision rules in Step 3. The model is then estimated using the formula shown below.
| NTSPACES
= ADT x P x DH x Dt x PF VHS |
For example, using the following parameter values:
| ADT | =12,000 | Dt | =0.25 |
| P | =0.14 | FP | =1.8 |
| DH | =0.15 | VHS | =2.0 |
The Demand formula may be rewritten as:
| NTSPACES= 12,000 x 0.14 x 0.15 x 0.25 x 1.8 |
| 2.0 |
The calculation yields an estimate of NSPACES equal to 31.5, indicating a need for approximately 32 truck parking spaces at the rest area.
Step 5. Interpret and Apply Results
The results of the Truck Parking Demand model indicate the truck parking requirements at a public rest area. The estimated number of spaces required, coupled with the number of truck parking spaces currently available at rest areas may then be subtracted from the total number of truck parking spaces estimated using the model in order to calculate the estimated shortfall in truck parking spaces at public rest areas.
Ideally, this modeling approach should be applied to a corridor or a state rather than an individual rest area. Estimating the total number of truck parking spaces required at public rest areas along a particular interstate corridor will be more useful in determining the overall truck parking space shortfall.
Example
In this section, a complete example is worked out to demonstrate the application of the truck parking spaces estimation model. The example is based on a set of three hypothetical rest areas. The tables at the end of this section correspond to the four steps used in the modeling process.
Step 1: Identify the Rest Areas
Three rest areas – XYZ001, XYZ002 and XYZ003 – are identified for analysis. The shaded portion (columns 1 through 4) in Table E1 shows information that needs to be collected in this step. The tabular format helps facilitate data entry and recoding in the next step.
Step 2: Enter and Recode Data
The shaded portion (columns 5 through 12) of Table E2 shows the data elements that need to be collected for the variables shown in table E1 and entered into the database. These are the variables that were identified as having a significant effect on public rest area truck parking spaces. The data for these variables may be collected through primary sources (such as surveys) or secondary data sources (such as past or current studies).
The shaded portion (columns 6 through 12) in Table E3 provides an overview of the recoding procedure. The coding is based on the values of the data collected in Table E2.
Step 3: Apply the Decision Rules
The decision rules given above for the "P" and "DH" factors are applied to determine their appropriate values. As shown in Table E4, rest area XYZ001 takes on a value of 0.16 for "P." This includes the default value of 0.12 plus a 0.01 increment for each of the following factors:
Based on the same methodology, the "P" value for rest areas XYZ002 and XYZ003 are 0.15 and 0.14. Note that the "P" value for XYZ003 is 0.14 because the 0.01 increments are added for only two of the factors (i.e., the distance from the previous rest area exceeding 50 miles and the presence of an attendant on premises.)
The design hourly factor (DH) varies for each of the rest areas, as shown in Table E3. The DH factor for rest area XYZ001 is 0.15, since the ADT is less than 12,500 (i.e., 8,650). The DH factor for rest area XYZ002 is 0.10, since the ADT recorded for that area fell within the 12,500-30,000 range (i.e., 16,656). The DH factor for rest area XYZ003 is 0.075, since the ADT recorded there exceeded 30,000 (i.e., 31,100). The parameter values for the other factors, such as percentage distribution of parking spaces between cars and trucks (Dt), the peak factor ratio (PF) and the vehicles per hour per space (VHS), are held constant across all three rest areas.
Step 4: Estimate the Truck Parking Demand Model
The modified mathematical formula for estimating the total number of truck parking spaces at public rest areas is shown in Table E5. The parameter values for each of the factors are entered into the formula along with the respected ADT volumes recorded for each rest area. The estimation equation is then solved to arrive at the estimates for total truck parking spaces. In this example, rest area XYZ003 is shown to have the largst requirements of truck parking spaces (73 spaces), whereas the estimated number of truck parking spaces required for rest areas XYZ001 and XYZ002 are 47 and 56 spaces respectively. As the estimates indicate, the total number of truck parking spaces required at a particular rest area not only depend on the ADT volumes passing the rest area, but also on the values of the other parameters used in the model.
Task 5. Analyze and Interpret Results
The results of the preceding four tasks will enable the user to determine
Results should be analyzed from three angles. First, the results from the inventory of existing rest areas documents are the current supply of commercial vehicle parking in highway resting facilities. Second, the direct observation and commercial driver surveys offer primary data on the demand for truck parking. Third, the results from the quantitative modeling process indicate the requirements for truck parking at public rest areas. These results should be evaluated separately then considered together to determine the overall truck parking space shortfall.
Task 6. Report and Use the Results
One of the goals of this process is develop a successful rest area program in a concise planning process. This process requires that after identifying a need or demand and determining the extent of it, solutions must be developed through an orderly planning process and stated in terms of a program. Commitments to a rest area development program should involve accepting program objectives, priorities and funding levels as part of overall state development objectives. This will ensure that development proceeds concurrently with related transportation programs. Without a commitment, rest-area program implementation and successful development are not given the appropriate support by management and eventually fail.
Transportation managers must recognize the need and value of rest areas. Their primary responsibility is to provide a safe highway system, and rest areas are one of the means of providing that safety. When commercial drivers use a rest area, they generally return to the road as safer drivers. Rest areas also provide travelers with a positive image of state, especially when well designed.
This guide has discussed the basic elements required to establish a successful planning process for developing rest areas. Using this approach, a statewide comprehensive rest area program can be developed. Following the procedures described here will result in a defensible, documented report. It should describe the results of the process and identify rest-area location requirements and develop guidelines. This report is the foundation for initiating a statewide comprehensive rest area program. It can be a bargaining tool for programming, planning, funding and implementation.
Survey of Parking at Rest Areas on Interstate Highways (.PDF file, 22K)
1 In the FHWA study, counts were made every hour from 10:00 p.m. to 6:00 a.m., Sunday through Thursday. In this survey, observations should be made evey half-hour, thus doubling the number of observations and keeping the observer teams more occupied during the long night shifts. More frequent oberservations will also allow for better analysis of turnover rates per space.
2 Design Hour (DH) compares the design hourly volume, usually the 30th – 50th highest volume, to the annual ADT, producing a factor that predicts a peak usage average-hour situation.
3 The rationale for this decision rule is based on the finding of the Capacity Utilization model developed by Apogee. They indicate that the variables in Table 2 that are coded "1" have a positive impact on capacity utilization of public rest area parking spaces. To control for the higher utilization of those rest areas possessing these variables, the percentage of mainline traffic entering the rest area or "P" is modified using the decision rule.
Last updated December 17, 1999
