stadium view trip generation report - ite western district - msu.pdf · stadium view trip...

Stadium View Trip Generation Report

2017-2018

Institute of Transportation Engineers at Montana State University

Table of Contents


Table of Contents

Chapter 1. Introduction ................................................................................................................................. 1

1.1. Scope of Work ..................................................................................................................................... 1

1.2. Site Description ................................................................................................................................... 2

Chapter 2. Study Methodology...................................................................................................................... 3

2.1. Level of Efforts .................................................................................................................................... 4

Chapter 3. Study Results ................................................................................................................................ 5

3.1. Vehicle Traffic ..................................................................................................................................... 6

3.2. Pedestrian Traffic ................................................................................................................................ 7

3.3. Bicycle Traffic ...................................................................................................................................... 9

3.4. Parking .............................................................................................................................................. 10

Chapter 4. Conclusion .................................................................................................................................. 12

4.1. Special Thanks ................................................................................................................................... 13

Appendix A. Trip Generation Forms ............................................................................................................ 14

Appendix B. Parking Forms .......................................................................................................................... 27

Introduction


1

Chapter 1. Introduction

This report summarizes the work performed by ITE @ MSU for the ITE Western District Student Data

Collection Program. The project was performed in southwest Montana’s city of Bozeman. Although ITE

@ MSU has a storied history, we have been fairly dormant over the last few years due to a high level of

student turnover. However, the club currently has a strong base of students passionate in transportation

engineering and we are excited for what our future holds. In the fall semester, we hosted ITE

International President-elect, Michael Sanderson, for a large transportation presentation. We also held

an informational session by representatives from the design and planning firm, Kittelson & Associates.

The club was able to reach out to middle school students in town at an interactive station at MSU’s

annual Engineer-A-Thon. For the first time in our club’s history, we sent student members to the ITE

Student Leadership Summit. We are also thrilled to be further involved with the upcoming annual

conferences of the ITE Western District and the ITE Intermountain Section. We are currently involved in

a pilot project involving the addition of bike lanes at Montana State University on existing campus

sidewalks. With all the new knowledge our members will gain from these events and projects, we plan

on giving back to our university by supporting transportation initiatives such as bike safety, better

parking, and additional public transportation. Multiple members of the club were involved with this data

collection project, as provided in section 4.1 of this report.

1.1. Scope of Work

This project included two main activities:

• Collection of continuous trip generation data for vehicles, bicycles, and pedestrians, grouped

into 15-minute intervals.

• Collection of parking lot occupancy every hour throughout the duration of study.

This work occurred over three different days of study, Wednesday February 21st, Thursday February

22nd, and Saturday February 24th. Data collection occurred between 7 AM and 6 PM.

Introduction


2

1.2. Site Description

The study site was the Stadium View apartment complex, following

Land Use Code 225: Off-Campus Student Apartment. As shown in

Figure 1, the complex is located directly west of the MSU football

stadium on South 11th Avenue. It is a half mile south of the

intersection of S. 11th Ave. and W. Grant St., the major

intersection on the southwest corner of the MSU campus. This

apartment complex was built in 2015 and serves primarily as off-

campus student lodging. It currently houses approximately 500

residents and encompasses an area of six city blocks. Stadium View

also has a sandwich shop on the first floor facing S. 11th Ave. There

is on-street public parking along S. 11th Ave and private, permit-only

parking for residents on-site.

Bozeman’s only public transportation system, the Streamline bus service, does not serve the complex.

The nearest bus stop is one mile away at MSU’s student union building. Because most bus routes in

south Bozeman are designed to service the university, the complex was deemed too close to justify

being included in a route.

This site was of interest because MSU, and Bozeman in general, has a rising population trend. Bozeman

was recently ranked as the fastest growing “micropolitan” area in the United States (2018 U.S. Census

Bureau). In addition, MSU set the 10th straight spring enrollment record in 2018, at a growth rate of 37%

(February 14, 2018 Bozeman Daily Chronicle). New housing developments will continue to be built

around the city, creating new concentrations of trip generations. In addition to ITE, the data collected

will be helpful to planners who seek to incorporate popular modes of transportation into new

developments.

Table 1: Statistics of Stadium View Apartments

Buildings 8

Stories 3

Apartments (approx.) 130

Residents (approx.) 500

Parking Spaces 515

Bike Racks* 10 * Bike racks each hold approximately 10 bicycles.

Stadium View

Apartments

11th

Ave

To

MSU

Vehicle

Vehicle

Veh

icle

Ped/Bike

Kagy Blvd

Figure 1: Site Overview (image taken from Google Maps).

N

Study Methodology


3

Table 1 shows relevant statistics of the Stadium View apartment complex. There are a variety of

apartment sizes within the complex including studio, 1, 2, 3, 4, and 5-bedrooms. The exact number of

each apartment size was not readily available, however there are approximately 3.8 bedrooms per

apartment. The vast majority of bedrooms within the complex contain only one resident. Therefore, it

was assumed that there are approximately 500 bedrooms within the complex. Due to the high demand

for housing in Bozeman, the complex has been fully occupied since it opened.

Chapter 2. Study Methodology

For the three days of data collection, members of ITE

@ MSU volunteered to collect data in shifts ranging

between one hour and six hours. There were always

two members on site, each performing one of two

roles. The first role consisted of observing

pedestrians, vehicles, and cyclists from the position

indicated in Figure 2. This position allowed the

observer to record the entire flow of traffic in and

out of the complex, as both the north and northeast

entrances were clearly in the line of sight of the

observer while looking southwest. Pedestrians,

vehicles, and cyclists were recorded by their respective mode of transportation and whether they were

entering or exiting the complex.

The second role filled by club members consisted of

recording the total volume of vehicles within the

complex. One volume was recorded for each hour

throughout the duration of the study. A drone was

used for some of the counts as it allowed the user to

quickly get an aerial view of the complex and record

the total volume of vehicles. When the drone was not

used, the counts were performed on foot, bike or by

car.

Stadium View Apartments

11th

Ave

To

MSU

Observation Location

Figure 2: Observation Location (image taken from Google Maps).

Figure 3: View from the observation location (taken from http://www.stadiumviewliving.com/)

N

Study Methodology


4

In February, Montana was the only state whose average temperature was rated by NOAA as “much

below average.” Montana experienced its sixth coldest February on record with a monthly temperature

of 9.7°F below average, being the coldest for the state since 1989. Even though no precipitation

occurred during the collection days, it is important to note that Montana’s statewide precipitation

(snowfall) was rated as “much above average” for the entire month. Due to the cold temperatures

during each day of study, all data collection (with the exception of some hourly manual parking counts)

was performed within a heated car parked at the study location indicated in Figure 2.

Table 2: Weather during days of study (NOAA).

Day Maximum

Temperature

Minimum

Temperature Precipitation

Average

Wind Speed Sunrise Sunset

Wednesday 15 °F -15 °F 0 In 2.4 MPH 7:17 AM 6:00 PM

Thursday 18 °F -5 °F 0 In 3.5 MPH 7:15 AM 6:02 PM

Saturday 32 °F 13 °F 0 In 8.9 MPH 7:12 AM 6:04 PM

Although the weather during the 3 days of study may have impacted how residents decided to commute

to school, the complex’s proximity to the university makes driving impractical under any conditions.

Unless a resident were to drive to the university earlier than 7:30, the closest available parking is only

several hundred feet from the complex (and still about a 10-minute walk from most university

buildings). Therefore, the vast majority of residents still walk to the university regardless of the weather

conditions. Because of icy conditions, some residents may have opted to walk instead of bike.

2.1. Level of Efforts

Each day of study lasted for 11 hours with at least 2 students always on site. Therefore, 66 total hours

were spent on data collection. The project manager spent an additional 4 hours preparing for the study

by building data collection sheets, outlining study instructions, and consulting with ITE @ MSU’s

professional mentor. The final 10 hours were spent analyzing the data and writing this report.

Preparation of this report was performed by 5 ITE @ MSU members.

Study Results


5

Chapter 3. Study Results

A full summary of counted trips by mode and day can be seen in Table 3. Note that the numbers reflect

11 hours of total data collection (7 AM – 6 PM) for each day. The total number of trips generated over

the three-day period is 3,568. The number of vehicles (2,110) and pedestrians (1,360) are far greater

than those on bicycles (98). The different modes of transportation percentages are summarized in

Table 4. The weekdays had much larger trip generation (1,297 on Wednesday and 1,581 on Thursday)

than the weekend (690). Note that for the vehicle trips in Table 3, the numbers shown represent only

the number of vehicles that were counted and does not consider the occupancy of each vehicle. Vehicle

occupancy was not counted in this study, however the average occupancy rate was likely close to 1.

Table 3: Summary of peak hour and daily averages of trips/h.

Table 4: Percentage of transportation modes for each day.

Mode Split

Day Vehicle Walking Bicycle

Wednesday 49 % 47% 4%

Thursday 55% 42% 3%

Saturday 87% 12% 1%

Among the ITE Trip Generation Data Forms, part 2 had cells to provide AM and PM Peak Hour of

adjacent street traffic. The peak hours were determined by data collection done by Sanderson Stewart

(civil engineering design firm) on Wednesday, January 11th, 2018. The counts were collected at the

intersection of S. 11th Ave. and W. Kagy Blvd., just north of Stadium View Apartments.

Mode

Wednesday, February 21 Thursday, February 22 Saturday, February 24

AM

Pea

k (t

rip

s/h

)

PM

Pea

k

(tri

ps/

h)

Dai

ly R

ate

(tri

ps/

h)

Tota

l Tr

ips

AM

Pea

k

(tri

ps/

h)

PM

Pea

k (t

rip

s/h

)

Dai

ly R

ate

(tri

ps/

h)

Tota

l Tr

ips

AM

Pea

k

(tri

ps/

h)

PM

Pea

k (t

rip

s/h

)

Dai

ly R

ate

(tri

ps/

h)

Tota

l

Trip

s

Vehicle 50 94 58 637 92 102 79 870 61 101 55 603

Walking 75 61 56 612 75 82 61 666 13 12 7 82

Bicycle 7 7 4 48 9 7 4 45 1 3 0.5 5

All Modes 132 162 118 1297 176 191 144 1581 75 116 62.5 690

Study Results


6

3.1. Vehicle Traffic

The number of vehicles per hour is summarized in figures 4, 5, and 6. The weekday AM peak hour is

between 10:45 and 11:45 with an average rate of 71 trips/h. The PM peak is 16:15 – 17:15 respectively,

at a rate of 98 trips/h. The weekend peak hours are similar with an AM peak at 10:30 – 11:30, and a PM

peak at 16:45 – 17:45. Weekend peak rates were lower than weekday in the morning at 61 trips/h, but

higher in the evening at 101 trips/h. More vehicles are departing than arriving the apartment complex in

the morning, while the number of vehicles arriving and departing are more equal in the evening.

Figure 4: Wednesday vehicle trips.

0

10

20

30

40

50

60

70

80

90

100

7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Trip

s

Time

Wednesday Vehicle Trips

Enter Exit

Study Results


7

Figure 5: Thursday vehicle trips.

Figure 6: Saturday vehicle trips.

3.2. Pedestrian Traffic

The amount of pedestrian traffic is equal to that of vehicles on the weekdays but is significantly lower on

the weekend. The amount of foot traffic arrivals and departures throughout the day is summarized in

figures 7, 8, and 9. During the mornings, there is a greater number of people departing the apartments,

while in the evening there is a larger number of people arriving at the complex. AM peak hour for

0

20

40

60

80

100

120

140

7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Trip

s

Time

Thursday Vehicle Trips

Enter Exit

0

10

20

30

40

50

60

70

80

90

100

7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Trip

s

Time

Saturday Vehicle Trips

Enter Exit

Study Results


8

pedestrians is 9:30 – 10:30 at peak rate of 75 trips/h. The PM peak hour is at 15:15 – 16:15 at a rate of

71.5 trips/h. The peak hour rates for the weekend are much lower. The AM peak hour is 10:30 – 11:30

with a rate of 13 trips/h and the PM is 16:15 – 17:15 at a rate of 12 trips/h.

Figure 7: Wednesday pedestrian trips.

Figure 8: Thursday pedestrian trips.

0

10

20

30

40

50

60

70

80

7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Trip

s

Time

Wednesday Pedestrian Trips

Enter Exit

0

10

20

30

40

50

60

70

80

7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Trip

s

Time

Thursday Pedestrian Trips

Enter Exit

Study Results


9

Figure 9: Saturday pedestrian trips.

3.3. Bicycle Traffic

The amount of bicycle traffic had much lower trip generation compared to the other two modes of

transportation. The AM peak hour during the week is at 9:00 – 10:00 with a rate of 8 trips/h. The PM

peak hour is at 14:15 – 15:15 at a rate of 7 trips/h. There was minimal bicycle traffic during the weekend

with a total of 5 trips throughout the day.

Figure 10: Wednesday bicycle trips.

0

2

4

6

8

10

12

14

16

7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Trip

s

Time

Saturday Pedestrian Trips

Enter Exit

0

2

4

6

8

10

12

7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Trip

s

Time

Wednesday Bicycle Trips

Enter Exit

Study Results


10

Figure 11: Thursday bicycle trips.

Figure 12: Saturday bicycle trips.

3.4. Parking

There is a general downward trend for parking occupancy throughout the day (Figure 13). As seen in

Table 5, the parking lot never reached over 67% full (indicating that almost a third of residents may not

own a vehicle). Over the course of the three days studied, there are on average less cars parked over the

0

1

2

3

4

5

6

7

8

9

10

7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Trip

s

Time

Thursday Bicycle Trips

Enter Exit

0

0.5

1

1.5

2

2.5

7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Trip

s

Time

Saturday Bicycle Trips

Enter Exit

Study Results


11

weekend than during the week. Note that with 515 spaces provided for 130 dwelling units, there is a

parking supply ratio of 4 spaces per dwelling unit.

ITE Parking Generation does not have student housing as a land use category. Land use category 221:

Low/Mid-Rise Apartments for suburban land use has an 85th percentile parking demand ratio of 1.94

vehicles/DU, which is below the observed demand ratios for this site.

Figure 13: Parking lot occupancy for each hour of study.

Table 5: Maximum parking supply ratio for each day.

Date Peak

Parking Observed

Parking Supply

(# of spaces)

Parking Occupancy

%

Parking Demand Ratio

(Per Dwelling Unit)

Wednesday 346 515 67% 2.7

Thursday 316 515 61% 2.4

Saturday 309 515 60% 2.4 * Parking Generation for Land Use Code 225 not found

Below in Table 6 is the Vehicle Trip Generation Peak Hour Generator values using the 10th Edition of the

ITE Trip Generation Manual. This was done based Land Use Code 225: Off-Campus Student Apartment.

Unfortunately there is no data from ITE that provides person trips for this specific land use. Therefore,

only comparison between vehicle trips was done.

200

220

240

260

280

300

320

340

7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00

Veh

icle

s

Time of Day

Parking Occupancy

Wednesday

Thursday

Saturday

Average

Conclusion


12

Table 6: Vehicle Trip Generation

Rate

Vehicle Trips per Bedroom

Vehicle Trips per Resident

% Vehicles Entering

% Vehicles Exiting

ITE Manual

Obs. ITE

Manual Obs.

ITE Manual

Obs. ITE

Manual Obs.

AM Peak “Hour” 0.12 0.17 0.13 0.17 41% 35% 59% 65%

PM Peak “Hour” 0.25 0.20 0.28 0.20 50% 46% 50% 54%

Weekday “Daily” Rate

3.15 1.27 3.65 1.27 50% 43% 50% 57%

Chapter 4. Conclusion

To conclude, the data collection resulted in relatively comparable results when compared to ITE Trip

Generation rates in the 10th Edition of the Trip Generation Manual. The observed weekday trip rates

varied quite a bit from the ITE manual rates. This is because the observed weekday daily rates do not

represent a 24-hour count. While the vehicle traffic observed from 7:00 to 18:00 represents a majority

of the traffic, it is likely there were also students that did not return to the apartment complex within

the study period of 7:00 to 18:00. More trips to and from the apartment complex beyond this time

frame is very likely as well. Percent rates for vehicles entering and exiting during peak hours were all

within 7% of the ITE Trip Generation rates for vehicle trips, showing little variance. ITE Parking

generation rates for Land Use Code 225 were not found, but our values provided may help to produce

rates for future editions of the manual. The data compiled and summarized may be used for future

analysis for planners.

Conclusion


13

4.1. Special Thanks

ITE @ MSU would like to give special thanks to the following individuals for their valuable help in

completing this project.

Danae Giannetti - Project Mentor, Montana Dept. of Transportation-Bozeman Design Unit

ITE @ MSU Members

• Joey Beran

• Matthew Campbell

• Matthew Bell

• Alia Peterson

• Bryce Grame

• Madeline Pernat

• Jaden Stewart

• Aldo Videa

• Wilson D’Souza

Faculty Mentors – MSU

• Ahmed Al-Kaisy

• Yiyi Wang

Doug Smith - MSU Surveying Instructor

Sanderson Stewart – Bozeman, MT office

ITE Professionals

• Lisa Fischer - Montana Chapter Vice President

• Cameron Waite - Intermountain District Past President

MSU Students

• Sarah Forseth

• Abram French

• Daniel Smithgall

• Nathan Ellis

• Audrey Stoltzfus

Trip Generation Forms


14

Appendix A. Trip Generation Forms



15



16



17



18



19



20



21



22



23



24



25



26

Parking Forms


27

Appendix B. Parking Forms

Parking Forms


28

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