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Shared-Use Path Level of Service Calculator

A User's Guide

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4. APPLYING THE MODEL TO YOUR TRAIL

The SUPLOS model is applicable to a variety of trail planning and design problems related to crowding and to accommodating diverse user groups. It is especially useful for trail planning and design tasks that need to augment qualitative criteria with quantitative measures to strengthen the basis for making trail design decisions. The following is a list of potential uses for the analysis tool:

• To plan appropriate widths and cross sections for new trails.
• To evaluate LOS provided on existing trails.
• To guide the design of improvements for existing trails, where additional capacity is needed.
• To determine how many additional users a trail may be able to serve, given a minimum LOS threshold.
• To evaluate LOS for specific timeframes when particular trip purposes need to be served, such as weekday morning and evening periods when commuting trips are heaviest.
• To determine LOS at a particular location on a trail, such as a narrow pinch point, an unusually high–use area, or an area with many reported user conflicts.

To enable the easy use of the model by practitioners, it has been programmed into a spreadsheet tool called the Shared–Use Path LOS Calculator. The spreadsheet tool provides the LOS for a path segment based on only four inputs from the user: estimated or counted one–way user volume in the design hour, mode split percentages, trail width, and presence or absence of a centerline. This chapter will help the reader understand how to apply this tool effectively and to generate results that are appropriate for the particular problem at hand. To make the best use of the calculator, it is important to understand the limits of its application and how contextual factors should be considered when collecting or structuring the input data.

LINK ANALYSIS

The SUPLOS model is a link analysis tool designed to provide an LOS evaluation for a particular link or segment of a linear trail. It is not designed to evaluate trail/roadway intersections, rest stops, or trailheads. It only provides LOS along a particular segment of pathway.

In general, segment length is not a limiting factor in selecting a link for analysis. The key to determining how much trail can be evaluated with one calculation is whether or not the trail conditions and use characteristics remain the same over the entire length that has been selected. However, because of the limits of the data used to calibrate the model, trail segments under a 0.40 km (0.25 mi) are not recommended for analysis. Moreover, because typical trip distances for some trail users are limited, and user turn–back rates will begin to undermine the accuracy of volume and mode split data on longer segments, 3.2–4.8 km (2.0–3.0 mi) is the recommended maximum segment length.

Each practitioner should exercise professional judgment in making these decisions. To aid that effort, the following list of conditions and characteristics should remain roughly the same over the entire distance of trail being considered as one link (segment):

• Trail width.
• Trail user volume.
• Trail user mix (mode split).
• Presence of a centerline stripe.
• An absence of significant flow interruptions such as stop signs, signalized road crossings, or other grade crossings (see box below).
• An absence of spur trails, trailheads, or other access points that may significantly affect user volumes or mix.

If any of these characteristics change significantly over the length of a trail segment, it is recommended that the segment be divided into one or more links using road crossings, access points, or other locations where characteristics change as endpoints for the smaller segments. Moreover, when considering establishing a trail volume and user mix profile for a single segment that is longer than 1.6 km (1.0 mi) based on counts taken in only one location, it is important to determine if turn–back rates for pedestrians or other users might be significant enough to affect the accuracy of this data for the sections of the segment that are farthest from the data collection point. In other words, if users often turn around partway through, a single count may not represent the whole segment very well.

As with any model, the quality and accuracy of the output can be no better than that of the inputs. It is understood that the quality and accuracy of input data will vary for each user of the tool. Moreover, each user and/or situation does not demand a uniform level of accuracy to produce a useful result. For these and other reasons, professional judgment is critical in determining what level of accuracy is required for the data to be used in any particular application. In most situations, slight variations in data may not affect LOS scores significantly, and the tool itself can be used to test variations in data and to determine what impact they have on LOS results.

The SUPLOS model does not factor in potential delay and other impacts from stop signs, signalized road crossings, or other grade crossings that interrupt the flow of trail traffic. The model is designed to generate LOS scores for trail segments of 0.40 km (0.25 mi) or longer with no flow interruptions. If LOS is desired for a length of trail that includes these types of interruptions, the trail should be segmented at these locations, and if possible, separate volume and mode split data should be developed for each segment.

DATA REQUIREMENTS

Only four data inputs are needed for the model to generate an LOS score and grade–trail width, presence of a centerline, one–way user volume and mode split. The following discussion of data requirements is provided to help readers apply the tool correctly and effectively to their unique situation.

Trail widths should be measured in feet. Widths may be entered in half–foot increments, i.e., 8.0, 8.5, 9.0, etc. (1 ft = 0.305 m). The model is calibrated to address widths between 2.4 m and 6.1 m (8.0 ft and 20.0 ft). Widths greater or lesser than these amounts will produce score and grade outputs; however, the model is not designed to address widths outside a range of 2.4–6.1 m (8.0–20.0 ft). [6]

Centerline is a yes/no input, to be based on the existing striping pattern of each test segment or the proposed striping pattern for an unbuilt trail.

The volume data needed for the calculator can be provided in one of three ways, depending on how the tool is being applied:

• By using actual volume counts collected on an existing trail.
• By using estimated volume counts developed by extrapolating from actual volume data gathered on another trail that is determined to be similar to the test trail (this can be one of the trails addressed in this study).
• By developing projected user volumes such as for an unbuilt trail, where LOS calculations will be used to aid in the trail planning and design process.

Whether volume data are developed from estimates or actual counts, they should be structured, or restructured, in the following ways:

• One–way trail volume should be calculated for each separate segment (link) of trail for which an LOS score is desired. If counts are structured as total two–way volumes, an assumed 50/50 directional split is recommended for conversion to one–way volumes. Volume data should be expressed in users per hour.
• Volume data should include a total count of all user types (modes) that use the treadway being evaluated. If a separate parallel treadway such as a jogging track or equestrian trail exists in the same trail corridor, users on this treadway should not be included in the volume or user mix data used in the model.
• If new user counts are collected for use in this tool, it is recommended that a minimum of three two–way, hourly counts be taken on each trail segment for which an LOS score is desired. For each test trail segment, an average, one–way, per–hour volume can be created from the three, two–way hourly counts.

If actual user volume is not known and estimates need to be developed, options include:

1. Use the volume data collected on another trail in your community or region that is sufficiently similar to the one you wish to analyze.
2. The one–way trail volume for the average trail can be used. This can be accomplished by using the volume number provided in the SUPLOS model itself; also see the average trail in table 4.
3. Review the trail volumes of the 15 study trails (see appendix A and table 4), and use the volume from a study trail that seems to be similar to the trail you wish to analyze, i.e., if it is located in a similar community, has a similar setting, has a similar width, has a similar mode split, etc.

Mode split is expressed as a percentage of one–way trail users per hour. The model provides the opportunity to input a mode split percentage for up to five different modes: adult bicyclists, pedestrians, runners, in–line skaters, and child bicyclists. Mode split inputs can be round numbers or precise numbers using one decimal place. They need to add up to 100 percent, exactly. Zero is an acceptable entry for any mode. Given the entire set of user types that are found on shared–use paths, these 5 categories were developed based on the actual users that were observed on the 15 study trails.

Other users, such as push scooters, electric scooters (used by disabled persons), wheelchairs, etc., may be present or expected on trails where this tool is applied. If the mode split data being used for the test trail segment include a breakout of user percentages in categories other than the five used by the calculator, those additional categories should be added to one of the five modes used by the calculator; use the mode that has the closest corresponding travel speed. [7] For average travel speeds, see table 4.

If actual mode splits are not known and estimates need to be developed, options include:

1. Use mode splits from data gathered on another trail in your community or region that are sufficiently similar to the one you wish to analyze.
2. Use the mode split for the average trail. This can be accomplished by clicking a special button in the calculator spreadsheet labeled default mode split.
3. Review the mode splits of the 15 study trails (see appendix A and table 2) and use a mode split from one of the study trails that you judge to be similar to the trail you wish to analyze, i.e., if it is located in a similar community, has a similar setting, has a similar width, etc.

On many trails, user volumes and mix will vary considerably along different segments. When more accurate LOS scores are desired, trail segmenting should account for these variations. The following is a list of spatial and behavioral factors that can generate significant volume and mode split fluctuations and can be used to guide segmentation:

• Locations of trail access points, including junctions with other trails, spur trails, trailheads, park nodes along a trail, and access points between the trail and adjacent trip generators and destinations.
• Trip generators and destinations associated with points of access, such as housing developments, employment centers, schools, parks, university campuses, entertainment attractions, or other institutions or public properties.
• Typical trip lengths and turn back rates; these will vary by user type and from trail to trail, because they are influenced by a number of trail specific factors such as trail layout, trip purposes, landscape character, and the personal habits and needs of local trail users.

Additionally, when new user counts are planned, these factors may be used to inform the location, frequency, and timing of the counts. When volume and mode split estimates are being used for model inputs, the factors listed above may be used to make adjustments to the estimates to increase data accuracy.

Temporal factors such as season of the year, day of the week, and time of day may be the most significant factors affecting trail user volumes. Therefore, any LOS calculated by the model applies only to the timeframes in which the volume data counts were taken.

In most cases, trail analysts seek to understand trail operations under highest–use conditions. When this is the case, the volume data to use in the calculator should reflect those conditions. The volume data should be gathered during, or adjusted to reflect, the typical highest–use times. The exact number and duration of user counts needed to fully describe highest–use conditions may vary from case to case, depending on the level of detail desired for the volume profile and on how the resulting LOS score is to be used.

To make a decent accounting of the variation in user volumes one might expect on a trail, at least three one–hour counts are recommended for each trail segment evaluated. Assuming that the purpose of the LOS scores is to determine if and how to improve service during high–use periods, counts should be taken during the high–use season, on a high–use day(s), and at high–use times of the day.

In some cases, a trail manager's problem may center as much on determining the duration or extent of high–use periods as on the decline of LOS during high–use times. Poor levels of service experienced during a few weekends a year or for an hour or two on a weekend day may be more tolerable than if a trail is crowded all day long throughout the spring, summer, and fall. The duration of time that certain levels of service exist may be as important to know as the LOS score itself. In these cases, the volume data used in the calculator should be more extensive and reflect greater temporal diversity.

Some users of this tool may seek an LOS evaluation for a more specific purpose such as determining the LOS for bicycle commuters during an afternoon peak. In such a case, the data would be gathered on weekdays during the season(s) that generates the highest commuting rates and would focus on the particular afternoon hours when bicyclists are present on the particular trail segments.

ASSUMPTIONS AND DEFAULTS

This section describes the key assumption and default values built into the Shared–Use Path LOS Calculator and look–up tables in appendix C. Any of these values may be changed in the detailed spreadsheets of the calculator if the user has more specific information on hand.

The SUPLOS model assumes a 50/50 directional split.

The model uses the average speeds and standard deviations for each user as shown in table 7. The default speed for the test bicyclist is 20.6 km/h (12.8 mi/h), which is the same speed as the average bicyclist.

The model uses a default peak–hour factor (PHF) of 0.85. This factor was calculated using the data collected on the study trails. PHF is based on the observed one–way volume for the peak 15 minutes within the 1–hour volume count. The model applies a PHF of 0.85 to the one–way, per–hour user volume, which results in a volume boost of 17.6 percent. This factor ensures that the model results are responsive to typical flow peaking conditions found on trails.

This and other trail research has found that bicyclists on trails tend to operate in distinct lanes, whether or not lanes are indicated on the trail surface with striping. Typical operational patterns include two–lane, three–lane, and four–lane operations:

• In two–lane operations, passing maneuvers are made in the opposing lane.
• In three–lane operations, each direction of travel shares use of a middle lane for passing maneuvers.
• In four–lane operations, each direction of travel has its own passing lane.

Because no standards exist that correlate trail width with lane operations, this study assumed the correlations shown in table 8. The widths in table 8 roughly correlate with the AASHTO Bicycle Facility Design Guide's recommended 1.2–m (4.0–ft) minimum allocation of space for safe bicycle operation.

Table 8. Correlation of trail widths and operational lanes.

Lane configuration matters only in the model's calculation of a delayed–pass factor. The model automatically determines the correct lane configuration to use based on trail width, as shown in table 8. The delayed pass factor is computed differently for each of the three possible lane configurations using the overall trail volume, mode split, and average travel speeds to calculate the probability of encountering delay in a passing maneuver:

• Two–lane operation has the greatest potential for creating delayed passes because the bicyclist must use the opposing lane to pass a slower user, and that lane may be occupied by users traveling in the opposite direction.
• Three–lane operations provide the bicyclist with better conditions for passing slower users because of the presence of a center, shared passing lane. Delay is determined primarily by the likelihood that a trail user traveling in the opposite direction is already using the center lane to make a passing maneuver; there is less likelihood of delay than in two–lane operation.
• Four–lane operations provide still better passing conditions because, unless overall user volume is extremely high, the probability of a delayed passing maneuver is greatly reduced.

SHARED–USE PATH LOS LOOK–UP TABLES

Appendix C includes a series of look–up tables that have been developed to provide readers a quick reference for LOS grades and volumes.

Tables 12 through 14 (see appendix C) provide LOS grades for a variety of volumes and trail widths using the average trail mode split, a high bicycle share mode split, and a high pedestrian share mode split, respectively. Tables 15 through 17 provide maximum service volumes for each LOS grade for a variety of trail widths. Service volumes are the volumes at the boundaries between levels of service. Again, three mode split examples are provided: average trail, high bicycle share, and high pedestrian share.

FHWA-HRT-05-138