Trip Generation Study: American Fork Commuter Rail Station ... - BYU.pdf · Trip Generation Study:...

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Trip Generation Study:

American Fork Commuter Rail Station

Land Use Code: N/A Similar Land Use Codes: 90 and 93

Introduction

The Brigham Young University Institute of Transportation Engineers (BYU ITE) student chapter

completed a trip generation study, as proposed to the ITE Western District. The data were

collected at the American Fork Commuter Rail Station in American Fork, Utah. This facility

includes a commuter rail (FrontRunner) station and shuttle service and is similar to the ITE Trip

Generation Land Use Codes 90 and 93 for the “Park-and-Ride Lot with Bus Service” and “Light

Rail Transit Station with Parking” land uses, respectively.

Land use 90 refers to a parking area that are used to transfer people from private vehicles to

buses. These sites generally have shelters for waiting passengers and circulation facilities for

buses and other vehicles. Land use 93 refers to a transportation station with the purpose of

transferring people from private vehicles to light rail transportation. It is anticipated that the

commuter rail facility could correspond to a new commuter rail center land use.

The funding from this project will allow members from our student chapter to participate in ITE

Western District meetings, local ITE Utah Chapter luncheons, and student chapter activities.

This experience was a great learning opportunity for the student chapter and the students who

were involved in the process.

Ryan Hales, P.E., PTOE, AICP, and Jeremy Searle, P.E., PTOE, of Hales Engineering, provided

mentoring support and project review for this data collection effort. Dr. Mitsuru Saito, P.E. and

Dr. Grant Schultz, P.E., PTOE, both of BYU, provided valuable help and support and data

collection equipment for the project.

Site Information

The American Fork Commuter Rail Station is located at 782 West 200 South in American Fork,

Utah. The property is owned and operated by Utah Transit Authority (UTA) and is located on

the north side of 200 South in a rural area that is growing into a suburban, non-Central Business

District (CBD) area. There are two access points to the property at 200 South as illustrated in

Figure 1. These two access points are the only access points to the property for all transportation

modes, including pedestrians and bicyclists. There are a total of 552 marked parking stalls at the

station. The site characteristics are summarized in Table 1.

INSTITUTE OF TRANSPORTATION ENGINEERS BYU STUDENT CHAPTER

2017 ITE Data Collection Report

Data used in the study were collected on four weekdays. The BYU data collection trailer was

used to collect data for the project on three weekdays. The trailer was parked within the property,

with the cameras pointed towards the two entrances along 200 South. Manual counts were

performed on one of the weekdays to account for lost video data. Parking counts were performed

on one weekday as well. Figure 2 shows one of the access points to the American Fork

Commuter Rail Station from 200 South. Figure 3 shows the traffic trailer set up at the site.

Figure 1: Aerial view of study area, traffic trailer location, and accesses.

Table 1: Site Characteristics

Characteristic Overall

Parking Stalls 552

Total Acres 7.65

Trains Arriving per Peak Hour 4

Daily Trains 54

Average Train Headway during Peak Hours (minutes) 15

Average Train Headway during Off-Peak Hours (minutes) 30



(a) (b)

Figure 2: West (a) and east (b) accesses to American Fork Commuter Rail Station from 200

South.

Figure 3: Traffic trailer used for data collection in American Fork.



Methodology

Data used in the study were collected from Tuesday, March 14, 2017 to Thursday, March 16,

2017. Three weekdays of data were collected, as outlined in the proposal. Trip generation was

counted between the hours of 6:00 AM and 7:00 PM for all three days.

For this study, the BYU Civil Engineering Traffic Data Collection Trailer was used to collect

data at the site. The trailer is equipped with two video cameras and a mast arm that can raise the

cameras as high as 30 feet. The traffic trailer was parked within the site, between the entrances

to the property. Both cameras were pointed at the entrances to the site. The Data Collection

Trailer was set up on Monday, March 13, 2017, with the 13-hour recording schedule set. In

order to run the trailer, a gas-powered generator was used. The data collection trailer had to be

visited once in the morning, once during the day, and once at night in order to turn the trailer and

equipment on and off and to verify that the trailer had sufficient fuel to keep the equipment

running all day. The trailer was retrieved from the site on Friday, March 17, 2017, and the video

recordings were extracted.

The three 13-hour video recordings were manually reviewed to count vehicular, bicycle, bus, and

pedestrian movements. The 13-hour driveway counts were aggregated into 15-minute periods,

identifying a count of all vehicles, buses, bicyclists, and pedestrians within the time period.

Parking data were collected manually on Wednesday, March 15, 2017. The counts were done

every hour at 10 minutes past the hour to ensure that UTA customers had entered/exited the train

and left the parking lot in order to get an accurate parking count. BYU ITE members drove

through the parking lot to get the parking counts for each hour.

Comments about Data Collection

Prior to the study, between February 25 and February 28, 2017, the weather had been

unpredictably cold. Several snow storms prevented the data collection project from occurring

earlier in February as planned. The weather had been sunny for a few days prior to the data

collection day. On Wednesday, March 15, 2017, there was a glitch in the camera system and the

cameras did not properly record data from about 7:15 AM to 12:45 PM. Due to this large gap in

data the leadership of this project deemed it necessary to conduct a manual traffic count to

supplement the video data. Those counts were conducted on Wednesday, March 22, 2017.

Because the trends of both Wednesday counts were similar, the video counts were omitted and

replaced with the entire day of manual counts. The manual counts conducted have been included

in the report as the Wednesday counts.

Results

The vehicle trip data for the AM and PM peak periods for each day of data collected are shown

in Table 2 and Table 3, respectively. The vehicle trip rates are calculated per parking stall,

occupied parking stall, and acre. These rates are also calculated using specifically the data

collected during the same day. A summary of trips counted each day of the study along with the

entry/exit distribution is presented in Table 4.



Table 2: AM Peak Period Vehicle Trip Data for the American Fork Commuter Rail Station

Table 3: PM Peak Period Vehicle Trip Data for the American Fork Commuter Rail Station

Table 4: Vehicle Trip Entering and Exiting Distribution Summary

The observed vehicle trips generated from this study are shown in Table 5 alongside average

vehicle trip rates from ITE Trip Generation, 9th Edition for ITE land uses 90 and 93. The

comparison of the observed number of vehicle trips in this study and the predicted number of

vehicle trips based on ITE trip generation rates for land uses 90 and 93 are presented in Table 6.

No peak hour trip generation data is available for land use 93. Therefore, only rates and trips for

land use 90 were compared with the observed rates and trips. Table 7 compares the directional

VariableTuesday

03/14/17

Wednesday

03/22/17

Thursday

03/16/17

Peak Hour 6:45 - 7:45 AM 6:30 - 7:30 AM 6:45 - 7:45 AM

Total Trips 251 263 232

Trip Rate (per parking stall) 0.45 0.48 0.42

Trip Rate (per occupied stall) 0.85 0.89 0.79

Trip Rate (per acre) 32.81 34.38 30.33

% Entering 78% 76% 76%

% Exiting 22% 24% 24%

VariableTuesday

03/14/17

Wednesday

03/22/17

Thursday

03/16/17

Peak Hour 5:15 - 6:15 PM 4:30 - 5:30 PM 4:45 - 5:45 PM

Total Trips 285 262 234

Trip Rate (per parking stall) 0.52 0.47 0.42

Trip Rate (per occupied stall) 0.90 0.83 0.74

Trip Rate (per acre) 37.25 34.25 30.59

% Entering 23% 29% 24%

% Exiting 77% 71% 76%

Entering Exiting Total Entering Exiting Total Entering Exiting Total

195 56 251 200 63 263 177 55 232

78% 22% 100% 76% 24% 100% 76% 24% 100%

66 219 285 75 187 262 56 178 234

23% 77% 100% 29% 71% 100% 24% 76% 100%

Tuesday (3/14/2017) Wednesday (3/22/2017) Thursday (3/16/2017)

AM

PM

Peak



distribution percentages for these trips by percentage to the percentages provided by ITE in land

use 90. It can be observed that the overall distribution percentages are relatively similar.

Table 5: Comparison of Observed Average Vehicle Trip Rates and ITE Trip Generation

Rates for Peak Hours and Weekday Scenarios

Table 6: Comparison of the Average Observed Vehicle Trips and ITE Predicted Trips for

Peak Hours and Weekday Scenarios

Table 7: Directional Summary

The number of samples used in creating the ITE Trip Generation rates for land use 90 range from

3 to 17 studies. The number of samples for land use 93 is 2 studies. Though the sample sizes are

small, the trip rates observed in this project can be compared with the ITE rates because it is in

within the independent variable range.

The rates and number of trips observed in Tables 5 and 6 are very similar to the ITE rates. The

most significant comparison is in the weekday period between land use 93 and the observed

number of trips. The rates and trips for both parking stall independent variables are within 1

percent of each other. Land use 90 consistently gave higher trip rates and a higher number of

Time Direction ActualITE Land

Use 90

Entering 77% 69%

Exiting 23% 31%

Entering 25% 28%

Exiting 75% 72%

AM Peak

Hour

PM Peak

Hour



trips than what was observed at this site. However, the observed trip rates did fall within the

standard deviation of the trip rates of land use 90. It can be concluded that the American Fork

Commuter Rail Station land use aligns best with ITE land use 93 and is comparable to ITE land

use 90. Detailed trip generation data forms for each day of data can be found in Appendix A.

Figures 4 - 11 show the hourly variations for entering and exiting vehicles, buses, pedestrians,

and bicyclists, respectively, for Tuesday, Wednesday, and Thursday. As shown in the data, there

was a consistent flow of pedestrians and bicyclists entering the site throughout the day. However,

a peak in the pedestrians and bicyclists exiting the site was seen at approximately 5:00 PM on the

site. Overall, the volume of pedestrians and bicyclists entering and exiting the site was very low

compared to the vehicular volume entering and exiting the site.

Figure 4: Hourly variation of total vehicles entering.

Figure 5: Hourly variation of total vehicles exiting.



Figure 6: Hourly variation of total buses entering.

Figure 7: Hourly variation of total buses exiting.



Figure 8: Hourly variation of total pedestrians entering.

Figure 9: Hourly variation of total pedestrians exiting.



Figure 10: Hourly variation of total bicyclists entering.

Figure 11: Hourly variation of total bicyclists exiting.



Hourly parking counts were conducted 10 minutes after the hour on Wednesday, March 15, 2017

and summarized results are shown in Table 8. As shown, the hour with the highest parking

occupancy was from 11:00 AM to 12:00 PM with 85 percent of stalls occupied. The average

occupancy for the day was 67 percent. There are no parking generation data available for the ITE

land use 90. ITE land use 93 does have parking generation data available, however, the only

independent variable is daily boardings. Daily boardings at the observed site was requested from

UTA but were unable to be obtained. As such, no comparisons were made between the observed

parking generation and the ITE Parking Generation, 4th Edition. A graph showing the parking

occupancy by hour on Wednesday, March 15, 2017 is shown in Figure 12. A parking generation

form summarizing the parking counts can be found in Appendix B.

Table 8: Parking Count Summary

Figure 12: Parking occupancy by hour on Wednesday, March 15, 2017.

Peak Hour Occupied Stalls 446

11:00 AM - 12:00 PM % Occupancy 85%

Occupied Stalls 351

% Occupancy 67%Average Weekday

Parking Occupancy



Level of Effort

Approximately 30 different BYU ITE student members were involved in this study. BYU ITE

student chapter officers spent numerous hours organizing and carrying out the data collection

efforts. A summary of hours spent on the project by student members is shown in Table 9. The

total number of hours spent ended up being much higher than the proposed number of hours

because of the complications with the data collection trailer and the subsequent need to perform

additional counts to supplement the data collected.

Table 9: Level of Effort

Task Number of

Students Total Hours

Training 5 7

Traffic Data Collection 5 31

Parking Data Collection 6 26

Data Reduction 26 44

Analysis and Report 6 30

Total: 138

Conclusion

The results from this data collection provide another sample that is comparable to the ITE Trip

Generation data for land uses 90 and 93. The calculated vehicle trip rates for this sample of data

will allow the ITE vehicle trip rates to be a better representation of actual conditions. This study

shows a significant difference in trip rates in all independent variables when compared to land

use 90. However, the observed vehicle trip rates are in the standard deviation range of land use

90. Therefore, the observed rates are comparable to land use 90. Despite the low number of

studies seen in land use 93, the observed vehicle trip rates were very similar to those of land use

93. It can be concluded that the observed rates align best with those of land use 93.

Adding these rates to the existing pool of sample sites in both land uses will allow for a better

representation of trips generated by similar sites and will be beneficial to providing accurate

traffic impact analyses of future developments as they are created. In addition, this site, though

related to land uses 90 and 93, is not entirely represented in the ITE Trip Generation Manual and

it is recommended that a new land use be considered that better represents a commuter rail

station.

As shown in the trip curves, it is possible that the morning and evening peak hour volumes were

not entirely captured. For future data collection projects done at similar sites to the American

Fork Commuter Rail Station, it is recommended that counts be taken from 4 or 5 a.m. to 7 or 8

p.m. in order to capture all peak hour traffic.



Appendix A – Trip Generation Forms



Appendix B – Parking Generation Form

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