Trip and Parking Generation Study of the Peaks Ice Arena Introduction The Brigham Young University Institute of Transportation Engineers student chapter (BYU ITE) completed a trip and parking generation study as proposed to the ITE Western District. The data were collected at a local ice skating rink in Provo, Utah. This corresponds to Trip Generation Land Use Code 465. This project was a great learning experience for the student chapter. Ryan Hales, P.E., PTOE, AICP, of Hales Engineering, provided mentoring support and project review for this data collection effort. Dr. Mitsuru Saito and Dr. Grant Schultz, both of BYU, have provided valuable help and support and data collection equipment for the project. Site Information Data were collected on three different days at the ice skating rink. An aerial picture of the study location is shown in Figure 1. Figure 1 Aerial View of Study Location.
The ice skating rink is called the Peaks Ice Arena and is located at 100 North Seven Peaks Boulevard in Provo, Utah. The parking lot has two access points, which are both located on Seven Peaks Boulevard. The site characteristics are presented in Table 1. Table 1 Site Characteristics Characteristic Value Gross Floor Area 110,000 ft 2 Number of Employees 60 Number of Seats 1800 Number of Parking Stalls 208 (7 ADA) Methodology Data were collected on Thursday, March 13, 2014, through Saturday, March 22, 2014. Three consecutive days were proposed for data collection, but problems occurred on Saturday, March 15, 2014, so data were collected again on March 22 for this study. As stated in the proposal, trip generation was counted between the hours of 7 a.m. and 7 p.m. for Thursday and Saturday, and between the hours of 9 a.m. and 9 p.m. for Friday. For the study, the BYU Traffic Data Collection Trailer was used to collect data at the site. The trailer is equipped with two video cameras that recorded each access point to the site during the specified hours. Permission to park the trailer at the site parking lot to collect data was obtained by the building manager. The data collection trailer at the site is presented in Figure 2. Figure 2 Data Collection Trailer The recorded videos from the data collection trailer were then used to manually count vehicles entering and exiting the site through each access, as shown in Figure 3. The total counts for the two access points were taken for each hour. The results of the trip generation are summarized in the attached Trip Generation Data Forms.
Figure 3 Data Reduction Results The trip data for the morning peak period, the afternoon peak period, and the peak hour of the generator are shown in Table 2, Table 3, and Table 4, respectively. The data were collected starting at 9 a.m. on Friday, so the morning peak data were not available for that day. Data about vehicle occupancy was not collected during this study. Bicycle trip data were also collected as part of this study and can be found in the attached Trip Generation Data Forms. The bicycle trip counts proved negligible. Data on pedestrian trips were collected, however no pedestrians were observed using the two recorded accesses on any day. This is most likely due to the additional access points for pedestrians that were not observed as well as the fact that the location of the arena has a very small amount of pedestrian activity. The trip rates shown are rates per number of employees, 1000 square feet of gross floor area (GFA), and number of seats. A summary of trips counted each day of the study along with the entry/exit distribution is presented in Table 5. Table 2 Morning Peak Period Trip Data for the Ice Skating Rink Variable Thursday 3/13/2014 Friday 3/14/2014 Saturday 3/22/2014 Peak Hour 7:00-8:00 AM N/A 7:30-8:30 AM Total Trips 19 N/A 25 Trip Rate (per employee) 0.32 N/A 0.42 Trip Rate (per 1,000 sqft. GFA) 0.17 N/A 0.23 Trip Rate (per seat) 0.01 N/A 0.01 % Entering 36.8% N/A 60.0% % Exiting 63.2% N/A 40.0%
Table 3 Afternoon Peak Period Trip Data for the Ice Skating Rink Variable Thursday 3/13/2014 Friday 3/14/2014 Saturday 3/22/2014 Peak Hour 5:00-6:00 PM 5:15-6:15 PM 4:30-5:30 PM Total Trips 88 52 176 Trip Rate (per employee) 1.47 0.87 2.93 Trip Rate (per 1,000 sqft. GFA) 0.80 0.47 1.60 Trip Rate (per seat) 0.05 0.03 0.10 % Entering 54.5% 28.8% 40.3% % Exiting 45.5% 71.2% 59.7% Table 4 Peak Hour of Generator Trip Data for the Ice Skating Rink Variable Thursday 3/13/2014 Friday 3/14/2014 Saturday 3/22/2014 Peak Hour 1:30-2:30 PM 5:15-6:15 PM 4:30-5:30 PM Total Trips 95 52 176 Trip Rate (per employee) 1.58 0.87 2.93 Trip Rate (per 1,000 sqft. GFA) 0.86 0.47 1.60 Trip Rate (per seat) 0.05 0.03 0.10 % Entering 52.6% 28.8% 40.3% % Exiting 47.4% 71.2% 59.7% Table 5 Summary of Daily Trip Data Thursday (3/13/2014) Friday (3/14/2014) Saturday (3/22/2014) Entering Exiting Total Entering Exiting Total Entering Exiting Total 1028 905 1933 867 723 1590 2154 1949 4103 53.2% 46.8% 100.0% 54.5% 45.5% 100.0% 52.5% 47.5% 100.0% The trips generated from this study have been calculated and are shown in Table 6 alongside average trip rates from ITE Trip Generation, 9 th Edition for comparison. Since the ITE trip generation data was based on only one observation, there were several trip generation rates that were not available. The comparison of actual number of trips and predicted number of trips based on ITE trip generation rates is presented in Table 7.
Independent Variable Table 6 Comparison of Calculated and ITE Trip Generation Rates Saturday Peak Hour Average Weekday AM Peak Hour Average Weekday PM Peak Hour Calculated ITE Calculated ITE Calculated ITE Number of Employees 2.93 N/A 0.32 N/A 1.17 N/A Gross Floor Area (1,000 sqft.) 1.60 N/A 0.17 N/A 0.64 2.36 Seats 0.10 N/A 0.01 N/A 0.04 0.02 Table 7 Comparison of Actual and Predicted Trips Saturday Peak Average Weekday AM Average Weekday PM Independent Hour Peak Hour Peak Hour Variable Actual Predicted Actual Predicted Actual Predicted Number of Employees 176 N/A 19 N/A 70 N/A Gross Floor Area (1,000 sqft.) 176 N/A 19 N/A 70 260 Seats 176 N/A 19 N/A 70 36 Since the existing data provided by ITE was limited, it is difficult to make observations from the differences between the trip generation data collected in this study and predicted values based on ITE trip generation rates. For the limited data available, it can be seen that the trip rate calculated from this study is substantially lower than the trip rate provided by ITE based on gross floor area. Also, the trip rate calculated from this study is higher than the trip rate provided by ITE based on the number of seats at the skating rink. Activities at the arena for these three days included a combination of open skating, pick-up hockey, figure skating classes and practices, hockey classes and practices, group rentals, and birthday parties. It is important to note that the arena opened earlier than the start time for each day. Private figure skating practice began at 6:00 AM each day of observation. Likewise, the arena closed well after the end times of the study, with some activities beginning as late as 10:00 PM, such as College Night on Friday. After speaking with the building manager, the schedules for the three observed days were typical for the respective days of the week. The only exception was a figure skating club performance from 11:45 AM to 1:45 PM on Saturday, March 22, 2014. While a performance does not happen every Saturday, the manager said that performances as well as hockey games take place regularly. Additionally, the manager said that Saturday is consistently the busiest day of the week independent of performances and games. Because of the nature of the land use, the trip rates will most likely fluctuate due to seasons. The ice skating rink chosen for this study also included an indoor soccer field. Thus, the data
collected for this study could vary from a typical ice skating rink. The indoor soccer field is scheduled and used in the same way as the rinks for large groups and birthday parties; there are no regularly scheduled events for the field. Figures 4, 5, and 6 show the hourly variations of parking demand, entering vehicles, and exiting vehicles for Thursday, Friday, and Saturday, respectively. 60 50 Parking Entering Exiting 40 30 20 10 0 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 Figure 4 Hourly Counts for Thursday 50 45 40 35 30 25 20 15 10 5 0 Parking Entering Exiting 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 Figure 5 - Hourly Counts for Friday
120 100 Parking Entering Exiting 80 60 40 20 0 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 Figure 6 - Hourly Counts for Saturday For this study, data on parking generation were also collected. The hourly variations of parking demand can be seen in Figures 4, 5, and 6, for the three different days. The comparison of actual parking demand and predicted parking demand based on ITE parking generation rates is presented in Table 8. Independent Variable Friday Peak Period Parking Demand Count Observed (8:30 PM) Table 8: Parking Generation Summary Friday Peak Period Parking Demand Rate Predicted Calculated ITE Saturday Peak Period Parking Demand Count Observed (3:30 PM) Saturday Peak Period Parking Demand Rate Predicted Calculated ITE Number of Employees 48 N/A 0.80 N/A 119 N/A 1.98 N/A Gross Floor Area (1,000 48 46 0.44 0.42 119 64 1.08 0.58 sqft.) Seats 48 N/A 0.03 N/A 119 N/A 0.07 N/A ITE parking generation rates for this land use are based on one study. That study only used the gross floor area independent variable. The actual values for Friday are very close to the predicted values from ITE. The Saturday predicted values are about half of the actual values. As discussed earlier, there was a performance on Saturday from 11:45 AM to 1:45 PM. And while Figure 6 shows a slight increase in parking during that range, the peak of parking demand is in the 3:00 PM hour. This is after the performance and during regularly scheduled practices, classes, and free skating periods. And after consulting with the building manager, these values are typical for a Saturday during this time of year.
Level of Effort Many different BYU ITE student members were involved in this study. BYU ITE student chapter officers especially 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. Table 9: Level of Effort Number of Total Task Students Hours Training & Planning 5 10 Repair & Set-up Equipment 5 10 Data Collection 7 48 Data Reduction 9 13 Write Report 1 5 Total: 86
Parking Demand Survey Form Institute of Transportation Engineers (fill in all highlighted cells - * are required data) Land Use Code* 465 Name of Site Peaks Ice Arena Brief Description of Site Transit* No Ice skating rink Area* CND City Provo TMP* No State Utah Country USA Parking Price* $ - Daily Rate 0 Hourly Rate Site Size* 110,000 Units* Square Feet Occupancy* Site Size 60 Units Employees Occupancy Site Size 1,800 Units Seats Occupancy Site Size Units Occupancy Land Use Number of Parking Spaces Provided at Site 208 Highest Observed Parking Demand for the following hours of the day (hour beginning)* Date 13-Mar-14 14-Mar-14 22-Mar-14 Day Thursday Friday Saturday 12 Mid 1:00 AM 2:00 AM 3:00 AM 4:00 AM 5:00 AM 6:00 AM 7:00 AM 15 12 8:00 AM 10 16 9:00 AM 5 6 17 10:00 AM 13 9 34 11:00 AM 18 15 43 12 Noon 40 36 58 1:00 PM 50 43 63 2:00 PM 40 29 57 3:00 PM 52 11 105 4:00 PM 23 29 100 5:00 PM 36 40 93 6:00 PM 44 17 59 7:00 PM 39 22 69 8:00 PM 38 9:00 PM 39 10:00 PM 11:00 PM Person Seishi Yamagata Organization BYU ITE Student Chapter Phone 801-422-2811 Fax 801-422-0159 Email byuite@gmail.com Notes Enter data on the web at www.ite.org Comments to: ite_staff@ite.org IF not entered on web site, please mail to: Institute of Transportation Engineers, 1627 Eye Street, NW Suite 600; Washington, DC 20006 Form version 1.4