Trip Generation Study: Provo Assisted Living Facility Land Use Code: 254

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1 Trip Generation Study: Provo Assisted Living Facility Land Use Code: 254 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 Provo Assisted Living (PAL) site in Provo, Utah. 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. Grant Schultz, P.E., PTOE and Dr. Mitsuru Saito, P.E., both of BYU, provided valuable help, support, and data collection equipment for the project. Project Summary The PAL site is located at 462 South 900 East in Provo, Utah. The property is family owned and operated and is located on the west side of 900 East in a suburban non-central Business District (CBD) area. There are two vehicular access points to the property on 900 South as illustrated in Figure 1. There are 25 marked parking stalls on the site. There are 44 beds on the site, with 42 currently occupied beds. Additionally, the site has 37 employees. The site characteristics are summarized in Table 1. The PAL facility is currently expanding its facility on the west side of the property to add more capacity. The construction of this expansion was ongoing during the data collection process. However, all construction vehicles accessed the site from State Street on the west side and not from 900 East. No details were provided by the owner for the new expansion, however, it is anticipated that additional beds will be added. Only the original site characteristics were used for the analysis as they were the current conditions for the data collected. Data used in the study were collected on three weekdays from February 13-15, Manual counts were performed at the site for the adjacent street traffic on 900 East. Figure 2 shows both accesses to the site as viewed from the north. BRIGHAM YOUNG UNIVERSITY 368 CLYDE BUILDING PROVO, UTAH (801) / FAX: (801)

2 Figure 1: Aerial view of study area in Provo, Utah (Google Earth). Table 1: Site Characteristics Characteristic Overall Square Footage of the Facility 20,000 Total Number of Beds 44 Number of Occupied Beds 42 Number of Employees 37 Page 2

3 Methodology Figure 2: North and south accesses to the property. Data used in the study were collected from Tuesday, February 13, 2018 to Thursday, February 15, Three weekdays of data were collected, as outlined in the proposal. Vehicles and pedestrians entering and exiting the site were counted between the hours of 6:00 AM and 7:00 PM for all three days. For this study, members of the BYU ITE student chapter counted traffic on the adjacent street (900 East) and the traffic entering and exiting the site through both the north and south access. For the manual counts one student was positioned at both the north and south access to count the entering and exiting traffic. Each student counted the adjacent street traffic. This allowed for a comparison between the two counts for quality control purposes. The three 13-hour counts included counts for vehicles and pedestrians. The 13-hour driveway counts were aggregated into 15-minute periods, identifying a count of all vehicles and pedestrians within the time period. In addition to the passenger vehicles and trucks on 900 East, it was observed that a number of bicyclists and transit buses traveled on the roadway. These vehicle types were not counted separately but were included in the total vehicle count to determine the peak hours of the adjacent street traffic. It was observed that there is a bus stop located just south of the PAL facility. Parking data was collected manually on Wednesday, February 14, The counts were done every hour on the hour. BYU ITE members walked through the parking lot to get the parking counts for each hour. Results The 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 trip rates are calculated per square footage, bed, occupied bed, Page 3

4 and employee. These rates were calculated using the data collected during the same day that it was collected. A summary of trips counted each day of the study along with the entry/exit distribution is presented in Table 4. The number of passengers in each vehicle was not counted; therefore, the trip rates shown below are vehicle trips only. Variable Table 2: AM Peak Period Vehicle Trip Data for the PAL Site AM Peak Hour of the Adjacent Street Tuesday (02/13/2018) Wednesday (02/14/2018) Thursday (02/15/2018) Average Peak Hour 7:45-8:45 AM 7:45-8:45 AM 7:45-8:45 AM 7:45-8:45 AM Total Trips Trip Rate (per 1000 S.F.) Trip Rate (per Bed) Trip Rate (per Occupied Bed) Trip Rate (per Employee) % Entering 33% 60% 33% 42% % Exiting 67% 40% 67% 58% Variable Table 3: PM Peak Period Vehicle Trip Data for the PAL Site PM Peak Hour of the Adjacent Street Tuesday (02/13/2018) Wednesday (02/14/2018) Thursday (02/15/2018) Average Peak Hour 4:45-5:45 PM 5:00-6:00 PM 4:30-5:30 PM 4:30-5:30 PM Total Trips Trip Rate (per 1000 S.F.) Trip Rate (per Bed) Trip Rate (per Occupied Bed) Trip Rate (per Employee) % Entering 36% 44% 50% 44% % Exiting 64% 56% 50% 56% Page 4

5 Table 4: Vehicle Directional Distribution by Day Peak Hour of Adjacent Street AM PM Tuesday Wednesday Thursday Entering Exiting Total Entering Exiting Total Entering Exiting Total % 67% 100% 60% 40% 100% 33% 67% 100% % 64% 100% 44% 56% 100% 50% 50% 100% Table 5 compares the directional distribution percentages for these trips by percentage to the percentages provided by from ITE Trip Generation, 10th Edition. It should be noted that the values presented in Table 5 represent the average of the three data collection days. It can be observed that the overall distribution percentages are very different during both the AM and PM peak hours. Table 5: Vehicle Direction Distribution Comparison Time Direction Actual ITE AM Peak Hour PM Peak Hour Entering 42% 78% Exiting 58% 22% Entering 44% 30% Exiting 56% 70% The number of samples used in creating the ITE Trip Generation rates for land use 254 ranges from 2 to 24 studies. Though the sample sizes are small, the rates from this data can be compared with the ITE rates because it is in within the independent variable range. The vehicle trip generation rates calculated for the peak hours and weekday periods are shown in Table 6. It should be noted that the values presented in Table 6 represent the average of the three data collection days. As shown, the average AM and PM peak hour trip rates for the PAL site are very similar to those provided by ITE. The weekday ITE vehicle trip generation rates are smaller than the calculated rates from this study. Due to visiting hour limitations, it was assumed that most of the trips to and from the site would be made during the course of the 13-hour count. However, additional trips were added to extrapolate 24-hour counts. Based on conversations with the owner, it is anticipated that a few shift changes occur during the night, though the owner did not say how many. Based on the parking counts on Wednesday, February 14, 2018, four vehicles were parked at the beginning of the count in the morning, and seven vehicles were parked at the end of the count in the evening. It was assumed that the seven vehicles parked in the evening would leave sometime after the 13-hour count and the four vehicles in the morning would have arrived prior to the next day s 13-hour count. Therefore, 11 vehicles were added to the average weekday count in order to estimate the weekday trip generation. Page 5

6 Table 6: Vehicle Trip Generation Rates Comparison Independent Variable Trip Rate (per 1,000 sq ft) Trip Rate (per Occupied Beds) Trip Rate (per Beds) Trip Rate (per Employee) Weekday AM Peak Hour Weekday PM Peak Hour Calculated ITE (Land Use 254) Calculated ITE (Land Use 254) Calculated Weekday ITE (Land Use 254) Figures 4 through 7 show the hourly variations for entering and exiting vehicles and pedestrians, respectively, for Tuesday, Wednesday, and Thursday. As shown in the data, there was a large variability of pedestrians entering and exiting the site throughout the day. However, a peak in the pedestrians exiting the site was seen at approximately 2:00 PM on the site. Overall, the volume of pedestrians 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. Page 6

7 Figure 5: Hourly variation of total vehicles exiting. Figure 6: Hourly variation of total pedestrians entering. Page 7

8 Figure 7: Hourly variation of total pedestrians exiting. Vehicle occupancy was not collected during the study period. However, based on observations during the study, it was assumed that vehicle occupancy was about 1.4 persons per vehicle. From this assumption, it was calculated that the site generated 234 total person trips per day over the study period, with 224 trips by vehicle, and 10 trips by foot. From this total person trip generation, a modal split of 95 percent vehicle trips to 5 percent pedestrian trips was calculated. Hourly parking counts were conducted every hour on Wednesday, February 14, 2018 and summarized results are shown in Table 7. As shown, the hour with the highest parking occupancy was from 12:00 PM to 1:00 PM with 60 percent of stalls occupied. The average occupancy for the day was 36 percent. A graph showing the parking occupancy by hour on Wednesday, February 14, 2018 is shown in Figure 8. A parking generation form summarizing the parking counts can be found in Appendix B. Table 7: Parking Count Summary Parking Occupancy Peak Hour Occupied Stalls 15 12:00 PM - 1:00 PM % Occupancy 60% Average Weekday Occupied Stalls 9 % Occupancy 36% Page 8

9 Figure 8: Parking occupancy by hour on Wednesday, February 14, Peak parking generation for the site occurs during the noon hour, with a parking demand of 15 stalls. An independent variable of dwelling units was established in order to compare the data to ITE Parking Generation. It was assumed that there is only 1 bed per dwelling unit, leading to a total of 44 dwelling units for the site. The peak period parking demand for the site was then calculated to be 0.34 vehicles per dwelling unit, which is the 33 rd percentile rate for this land use type. Table 8 below summarizes these findings. Table 8: Parking Generation Summary Variable Wednesday (02/14/2018) Peak Hour 12:00 1:00 PM Peak Period Parked Vehicles 15 Dwelling Units 44 Peak Period Parking Demand (Vehicles Per Dwelling Unit) 0.34 Page 9

10 Conclusions The results from this data collection provide another sample that is comparable to the ITE Trip Generation data for land use 254. The calculated trip rates for this sample of data will allow ITE s trip rates to be a better representation of actual conditions. This study shows a difference in rates in all independent variables when compared to land use 254. However, despite the low number of studies seen in land use 254, the trip rates and number of trips observed were very similar. 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. Level of Effort Approximately 17 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 8. As shown, approximately 90 collective hours were spent on this project. This is slightly higher than the 80 hours in the original proposal. Task Table 8: Level of Effort Number of Students Total Hours Training 5 5 Traffic/Parking Data Collection Data Reduction/Analysis 4 10 Analysis and Report 4 10 Total: 90 Page 10

11 Appendix A Trip Generation Forms Page 11

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24 Appendix B Parking Generation Form Page 24