2.0 COMMERCIAL TRUCK PARKING DEMAND

2.1 INTRODUCTION

This section summarizes an analysis that was conducted to develop a nationwide estimate of the peak hour demand for commercial truck parking facilities resulting from the need to comply with Federal hours-of-service rules. Federal hours-of-service rules have been in effect in their current form since 1962 (49 CFR 395). The rules allow for commercial motor vehicle drivers in interstate commerce to be on duty up to 15 hours and drive up to 10 hours after 8 consecutive hours off duty. Weekly limits provide that if a motor carrier operates commercial motor vehicles every day, its drivers may not drive after being on duty 70 hours in 8 consecutive days. These rules, therefore, typically require drivers of commercial motor vehicles to complete a period of rest while en route to a destination if the driver is unable to return home for the required rest.

While drivers are required to obtain extended rest, there is no single agency, organization, or group that is responsible for providing drivers extended rest locations. Essentially, drivers find such locations themselves and typically rely upon two primary options: commercial truck stops and travel plazas or public rest areas. (Drivers also use other facilities such as loading areas or terminals, shopping centers or plazas, and other similar facilities. This study concentrates on the supply of public rest area parking and parking provided at commercial truck stops and travel plazas as required by Section 4027.) Driver preferences for a particular type of facility to park for rest are influenced by a number of factors, including the anticipated length of the rest period and whether the facility provides for non-rest related activities, such as refueling and maintenance or eating a meal.⁽⁸⁾ Commercial truck stops and travel plazas are designed to provide drivers an opportunity to fulfill many non-rest related activities while public rest areas provide the driver with only minimal services.

A questionnaire concerning truck drivers needs and preferences was developed for this study to help derive travel demand estimates. A survey of commercial truck drivers was administered to more than 2,000 truck drivers in selected regions across the United States. Survey responses were used to determine truck drivers' needs, preferences, and travel patterns (e.g., why, when, and where they park). This information was used to calibrate several of the parameters in the model so that they would more accurately represent drivers' behaviors and travel patterns. Driver survey results were used to develop default values for the following parameters: average hours spent loading/unloading per week, average hours spent at home per week, average hours spent parking for rest at shipper/receiver per week, and the portion of demand for public rest area and commercial truck stop and travel plaza spaces.

The importance of determining the values of the loading/unloading time, at-home time, and time spent resting at shipper/receiver was to calculate the amount of time a driver requires parking along the highway in a typical week. Similarly, values of total parking demand for public rest areas and commercial truck stop and travel plaza spaces were derived based on responses to questions in the driver survey (from both short- and long-haul drivers) regarding where they prefer to stop for different purposes (e.g., long-term rest, restroom, meal, etc.). For a thorough discussion of the driver needs and preferences survey and how questions from the survey were used to develop travel demand estimates, refer to references 8 and 9.

2.2 NATIONAL SURVEY OF DRIVER NEEDS AND PREFERENCES FOR PARKING

A clear understanding of truck drivers' parking-related needs, preferences, and decision making is necessary to accurately assess truck parking supply and demand.

To measure truck driver parking needs and preferences, the Commercial Vehicle Driver Survey: Assessment of Parking Needs and Preferences⁽⁸⁾ study employed a nationwide survey of truck drivers. The survey sought to determine the following:

• How truck drivers plan for and address their parking needs.
• How truck drivers select when, where, and at which facilities they park.
• What truck drivers think of the adequacy of current parking facilities.

Surveys were distributed to a national sample of truck drivers both directly, through site visits to truck stops, and indirectly, through mailings to truck stops. A total of 2,046 completed surveys were collected. During site visits, survey teams collected 1,042 completed surveys. Surveyors experienced overwhelmingly high response rates (above 80 percent) after briefly explaining the purpose of the survey to drivers. An additional 4,400 surveys were mailed out to 22 truck stops across the country. Close to 1,100 surveys were returned, yielding a response rate of 24 percent for the mail-out distribution.

Locations for the site visits and mail-out distributions were chosen in order to reach a nationally representative sample of drivers. Before embarking on the major data collection task, the survey team tested distribution methods by visiting both public and commercial truck parking facilities on the east coast. During this pilot test, drivers made it clear that when at public rest areas they do not have time to participate in the study. However, at commercial truck stops and travel plazas, drivers generally agreed to fill out the survey during their stay. To determine whether omitting public rest areas from the list of distribution locations would limit the sample of short-haul drivers, the survey team asked short-haul drivers if they use commercial truck stops and travel plazas as often as they use public rest areas. Short-haul drivers consistently indicated that they use both types of facilities equally. Therefore, to maximize response rate and minimize negative impact on drivers' time, commercial truck stops and travel plazas were used exclusively for the survey distribution.

To ensure that the sample would be representative of a national sample of drivers, survey distribution sites were located in 27 States along major trucking corridors on the NHS. All regions of the United States were included.

Data from the national sample were analyzed to examine driver opinions with respect to parking patterns and preferences. Drivers' responses to the survey demonstrated definite preferences and priorities when it comes to choosing where they will park. When drivers park their trucks, most expect to satisfy only their basic needs. Drivers prefer parking facilities that provide food, fuel, restrooms, telephones, and showers. They also consider safety and convenience important when they park their trucks. When it comes to safety, drivers appear to value well-lighted parking lots even more than they value security presence. Drivers do not consider entertainment and other "luxuries" to be necessary characteristics of a parking facility. As one driver urged, "I just want to find a place to park that is safe and available." Because truck stops typically provide showers, restaurants, and repair facilities, it is not surprising that drivers generally prefer commercial truck stops and travel plazas to public rest areas. When drivers park for quick naps, they prefer to park in public rest areas.

2.3 NATIONAL COMMERCIAL VEHICLE PARKING DEMAND MODEL

A modeling approach was used to develop an estimate of the demand for commercial vehicle parking at commercial truck stops and public rest areas. The details of this model can be found elsewhere, but the general concepts underpinning the model are described in the following paragraphs.⁽⁹⁾

The model predicts commercial truck parking demand for a highway segment based on total truck-hours of travel and the time and duration of stops. The model considers the effect of Federal hours-of-service regulations on parking demand as part of the basis for estimating the average number of hours spent parking per hour spent driving. The model also considers the observation from the driver survey that drivers use public and private parking spaces for different parking purposes by using the survey results to estimate the fraction of total parking demand that is for private and public parking spaces. Although the corridor model limits the conclusions that can be drawn about a specific commercial truck stop and travel plaza or public rest area (e.g., the need for lighting, additional parking, etc.), it was considered more appropriate to reflect a roadway segment's or corridor's supply and demand characteristics.

The model develops corridor-level estimates of demand rather than estimates of demand for individual public rest areas or commercial truck stops and travel plazas along a route. This approach is based on the theory that demand for parking is explained by hours of driving rather than the attributes of an individual truck stop or rest area. Building the modeling framework around this system-level approach provided a basis to examine the influences of HOS regulations as well as driving time and distance on parking demand.

The modeling framework begins by estimating the truck-hours of travel for each highway segment using the annual average daily traffic, the percent of trucks, the length of the roadway segment being analyzed, and the speed limit or average truck speed. A key parameter in the model is the number of hours of parking required by drivers given the number of hours they traveled. Thus, Federal hours-of-service regulations have an indirect, but very real, effect on parking demand: the more hours of parking required for a given period of time on the road (i.e., the higher the ratio of parking time to driving time), the higher the estimated parking demand. Using these factors for a particular highway segment, the model produces a peak-hour, segment-wide estimate of parking spaces demanded at public rest areas and commercial truck stops and travel plazas.

The calibration of model parameters involved an iterative, trial-and-error effort that sought to produce parameter values that successfully replicated the results of field observations for selected corridors within an acceptable degree of error. Calibration of the model was accomplished by varying parameters' values in the model until an acceptable level of error was achieved. The resulting parameters were then applied to estimate demand.

Field data collection studies were completed to assist in the calibration of model parameters. Model parameters were calibrated using overnight field observations of parked trucks in eight States: Arkansas, Georgia, Idaho, Mississippi, Missouri, Pennsylvania, Tennessee, and Virginia. Observational studies were performed on 29 segments of highway in these eight States representing four regions and nine corridors. The parking demand estimates produced by the model are highly variable at the segment level. For example, the model estimates are within ±10 percent of the observed parked trucks for only 4 of the 29 segments (14 percent), ±20 percent for 11 of the 29 segments (38 percent), and ±30 percent for 20 of the 29 segments (69 percent). At the corridor level, on the other hand, the model is much more accurate. Model estimates are within ±10 percent of the observed parked trucks for six of the nine corridors (67 percent), ±15 percent for seven of the nine corridors (78 percent), and ±20 percent for eight of the nine corridors (89 percent).

This variance can be attributed to several factors. First, the model does not take into account the spatial distribution of available truck parking spaces. Although the amount of available parking does not affect the amount demanded, the spatial distribution of the supply will affect where, geographically, the demand is met. In other words, if a segment has no available supply, drivers who need or want to park will seek parking on adjacent segments. In addition, the model does not take into account typical freight movement (e.g., north to south, east to west, region to region). Typical travel patterns may result in locations experiencing a high demand for parking on a particular day(s) of the week. These peaking characteristics, which may have been captured in the field counts, are not reflected in the model estimates. Thus, it might be necessary to adjust the default value for the peak parking factor to meet the demand. Finally, the use of only two short-haul to long-haul ratios (i.e., 0.36/0.64 for urban and 0.07/0.93 for rural segments) may not adequately reflect the variations across regions and corridors. To better understand the variability in the short-haul to long-haul ratio, origin-destination surveys should be conducted in a variety of different locations that represent a range of distances from metropolitan areas with different populations.

Overall, the model produces acceptable estimates of parking space demand, with an error of only -2 percent for the 29 segments combined, an estimate within 269 spaces of the observed parked trucks. However, the model is not microscopic enough to accurately predict segment-specific demand. Because the model is driven by the number of long-haul trucks on a segment, the accuracy of the estimates is highly sensitive to input values such as annual average daily traffic and percent trucks. If these input values are not accurate, the model estimates cannot be expected to reflect actual conditions. Also, at the time the observational studies were conducted, the observed parked trucks exceeded the supply along half of the 29 segments, and therefore, may not be an accurate representation of the total demand for parking. Because the model was calibrated to the observed parked trucks, the use of this model will result in a conservative estimate of truck parking demand. Additional details concerning the calibration effort can be found elsewhere. ⁽⁹⁾

2.4 NATIONAL DEMAND FOR COMMERCIAL VEHICLE PARKING

The modeling approach was applied to appropriate NHS roadway segments throughout 49 States (excluding Hawaii). For analysis purposes, only segments carrying more than 1,000 commercial motor vehicles per day were considered. Segments falling below this threshold are less likely to generate sufficient demand warrant either truck stop or public rest area facilities comply with Federal hours-of-service rules.

Partners in each State reviewed these estimates and provided comments and suggestions that were used to improve the estimates. In many cases, adjustments were made to better reflect the volume of truck traffic on a segment, the speed limit, and other model factors.

Table 1 contains a summary of the modeling results for each State. The values presented in this table do not include any time that a driver may park for long-term rest at a loading or unloading facility. Demand estimates are provided for both public rest areas and commercial trucks stops and travel plazas. It is estimated that there is currently a peak hour demand for approximately 287,316 truck parking spaces at commercial truck stops and travel plazas and public rest areas nationally.^a Demand on Interstate highways was for 245,389 truck parking spaces (56,424 spaces at public and 188,965 at commercial facilities), and demand on non-Interstate highways was for 41,927 spaces (9,643 at public and 32,284 at commercial facilities). States with the highest daily demand include Texas and California as well as the mid-western States of Indiana, Illinois, and Ohio.

The estimate of public and private parking demand reflects the preferences for public versus private parking, as determined by the national driver survey. During this survey, drivers were asked for each of seven activities whether they preferred to stop at a public rest area or at a commercial truck stop for that activity. The relative preference for each type of parking space was estimated by taking an average of the preferences for each activity, rating each preference by the relative frequency of that type of activity and the duration of that activity. The proportions of total parking demand for rest area and truck stop spaces were estimated as 0.23 and 0.77, respectively.

Projections of the annual increase in parking demand over a 20-year period were also prepared and are presented in Table 1. The demand for parking in the year 2020 was estimated using the parking demand model. Most model parameters remained the same as when estimating the current parking demand. New input values to the model were obtained and derived from the following sources for the purpose of making a year 2020 forecast:

Table 1. Peak hour demand for commercial vehicle parking along Interstate highways and other NHS routes carrying more than 1,000 trucks per day, 2000

• Estimates for speed limit were based on the Highway Performance Monitoring System (HPMS) and comments provided by State Departments of Transportation (DOTs).
  
  
• Projected annual average daily traffic was derived from the HPMS, public rest area survey responses, and comments provided by State DOTs. If projections for the annual average daily traffic were not provided or obtained from HPMS then a growth rate for the annual average daily traffic of 3 percent per year was assumed.
  
  
• The percent trucks were derived from HPMS and data provided by the State DOTs.
  
  
• The demand was derived from the methodology contained in the Technical Guidance document. The demand shown in the table represents the number of spaces demanded for the peak hour along a corridor.

2.5 SUMMARY AND CONCLUSIONS

The primary purpose of this section was to develop an estimate of the demand for truck parking spaces at public rest areas and commercial truck stops and travel plazas that will serve in Section 4.0 as part of the basis for identifying parking space shortages on the NHS. A model for truck parking demand was developed based on the results of a national driver survey, and this model was calibrated by comparing observed parking volume against estimated volume. Development of the demand estimates did indicate the following:

• Driver surveys indicated that 23 percent of the demand is for parking at public rest areas and 77 percent of the demand is for parking at commercial truck stops and travel plazas.
  
  
• The 20-year forecasted growth rate of demand for truck parking at both public rest areas and commercial truck stops and travel plazas is estimated to be 2.7 percent annually.

[a] Because travel demand is variable, traffic engineering analyses generally focus on the peak periods of travel (e.g., peak hour of the day, peak month of the year). Peak demand for long-term truck parking typically occurs in the overnight hours between 10:00 p.m. and 6:00 a.m. As part of this study, commercial vehicle parking field surveys were conducted to record trucks parked during the peak hour in public rest areas, private truck stops, pull-out areas, interchange ramps, mainline and cross street shoulders, fueling stations, fast food restaurants, hotels, etc. These field counts were compared to the parking demand estimates from the model during the model calibration process.