SF State Transportation Survey 2014 FINAL

In response to the requirements of the MOU, San Francisco State University has conducted an online transportation survey and cordon count every three years beginning in April, 2008 with

San Francisco State University 2014 Transportation Survey Results

FINAL

August 2014

4 Cordon Count 4-1

Introduction 4-1 Methodology 4-1 Results 4-3

5 Carbon Emissions 5-1

Introduction 5-1 Methodology 5-1 Results 5-4

Appendix A: Survey Instruments

Cordon Count Survey Form i Online Survey ii

Table of Figures

Page

Figure 3-1: Adjusted Faculty/Staff and Student Responses 3-4 Figure 3-2: Population Scale 3-5 Figure 3-3: Mode of Arrival to Campus 3-8 Figure 3-4: Number of Legs in Journey to Campus 3-9 Figure 3-5: All Modes Used to Get to Campus 3-9 Figure 3-6: Cost of Commute 3-10 Figure 3-7: Peak Hour and Total Auto Trips (N = Total Campus Population) 3-10 Figure 3-8: Mode Split by Affiliation 3-11 Figure 3-9: Daily Muni trips by Muni route (N = Total Campus Population) 3-12 Figure 3-10: Peak Hour Muni Trips for the SF State Peak Period (N = Total Campus

Population) 3-13 Figure 3-11: Peak Hour Muni Trips for the Muni System Wide Peak Period of 5:00 PM to 6:00

PM 3-13 (N = Total Campus Population) 3-13 Figure 3-12: Peak Hour, Peak Direction Riders for M line (N = Total Campus Population) 3-14 Figure 3-13: Peak Hour, Peak Direction Riders for Bus Route 28/28L (N = Total Campus

Population) 3-14 Figure 3-14: Home County of BART Riders (n=726) 3-14 Figure 3-15: Parking On and Near Campus 3-16 Figure 3-16: Parking Costs 3-17 Figure 3-17: Programs to Encourage Drivers to Use Alternative Modes 3-18 Figure 3-18: Willingness to Purchase a Universal Transit Pass 3-18 Figure 3-19: Affiliation with San Francisco State University 3-19 Figure 3-20: Place of Residence 3-19 Figure 3-21: Campus Affiliates by Zip code 3-21 Figure 3-22: Location of SF State University Affiliates 3-1 Figure 4-1: Cordon Count Locations 4-2 Figure 4-2: Number of Vehicles Entering and Exiting by Location 4-3 Figure 4-3: Count of Vehicles Entering and Exiting by Location and Time 4-4 Figure 4-4: Count of Persons Entering and Exiting by Mode and by Hour 4-5 Figure 5-1: Total Passenger Miles Travelled per Day by Mode 5-4 Figure 5-2: Total Pounds of CO2 per Day by Mode 5-5 Figure 5-3: Pounds of CO2 Emissions per Passenger Mile 5-6 Figure 5-4: Total Miles Travelled and CO2 Emissions per Day 2014 5-6 Figure 5-5: Passenger-miles travelled, pounds CO2 per mile, and total CO2 per year by

mode 5-8

1 EXECUTIVE SUMMARY

In October 2007, the City and County of San Francisco and San Francisco State University

entered into a Memorandum of Understanding (MOU) The purpose of the MOU is to address the impact on the City and County of San Francisco from the implementation of the University’s campus master plan and anticipated increase in enrollment on the campus The MOU identifies a number of measures that the University must take, including the establishment of a traffic

monitoring and mitigation program

In response to the requirements of the MOU, San Francisco State University has conducted an online transportation survey and cordon count every three years beginning in April, 2008 with subsequent surveys taking place in April 2011 and April 2014 Survey data is used to track a number of key factors such as mode split, peak hour vehicle trips, peak hour Muni ridership, and GHG emissions

Key Findings

Key findings from the 2014 transportation survey include the following:

 Since 2008 the drive-alone rate for commute trips to the University has decreased by 32% with 26% of campus affiliates driving alone to campus in 2008 compared to 19.7% in

2014

 The percentage of campus affiliates who arrive on campus on foot has increased by 27.6% between 2008 and 2014

 Transit usage has increased with 46.8% of campus affiliates using Muni for some portion

of their trip to campus and 26.4% using BART This is an increase of 22.4% and 19.3%, respectively, since 2008

 Between 2008 and 2014 the number of peak hour vehicle trips has decreased by 10.6%

 Peak hour ridership on the Muni M Line and bus routes 28/28L has decreased slightly between 2008 and 2014

 An increase in the daily student population and miles travelled has resulted in a 15% increase in GHG emissions from 2008 to 2014, compared with 30% increase in miles travelled over the same time period The inverse relationship between GHG emissions and miles travelled is due to more miles being travelled on public transportation rather than in private vehicles

 Private vehicles have the highest levels of CO2 emissions per passenger mile More than half of all daily passenger miles are travelled on BART, but only 11% of the total daily pounds of CO2 emissions are generated by BART

 Less than half of the total daily passenger miles are in private vehicles, however persons driving alone are the largest contributors to San Francisco State University’s CO2

commute travel emissions, representing 77% of the total daily pounds of CO2 emissions

2 INTRODUCTION

In October 2007, the City and County of San Francisco and San Francisco State University

entered into a Memorandum of Understanding (MOU) The purpose of the MOU is to address the impact on the City and County of San Francisco from the implementation of the University’s campus master plan and anticipated increase in enrollment on the campus

The MOU identifies a number of measures that the University must take, including the

establishment of a traffic monitoring and mitigation program The MOU states that the purpose

of the traffic monitoring and mitigation program is to monitor and determine whether the

University’s expanded Transportation Demand Management (requirement 1 in Section B of the MOU) is successfully minimizing or avoiding new peak hour trips As part of the traffic

monitoring and mitigation program the MOU states that the University must conduct a new baseline cordon count and intercept survey no less than 12 months following the certification of the master plan EIR Furthermore, additional cordon counts must be conducted at intervals of no more than every three years or no later than the enrollment of each 1,000 new headcount

students to the University

In fulfillment of the requirements stated in the MOU, San Francisco State University conducted the baseline cordon count and intercept survey on the main campus at 1600 Holloway Avenue on Wednesday, April 30, 2008 A Wednesday was selected in order to ensure that the cordon count and intercept survey would be representative of a typical day on campus, when classes are in session and most affiliates are on campus The cordon count covered 15 vehicle, pedestrian, and bicycle entry points to campus and intercept surveys were conducted at seven entrances to campus In total, 1400 intercept surveys were completed A subsequent cordon count was

conducted on Wednesday, April 27, 2011 The second cordon count covered 16 vehicle,

pedestrian, and bicycle entry points to campus In 2014, the cordon count methodology was revised significantly to focus on vehicle entry points to campus The third cordon count was conducted on Wednesday, April 23, 2014 at nine locations

In addition to the cordon count, the University also conducted an online survey in 2008, 2011 and

in 2014, which was sent to all University affiliates An online survey was not identified in the original MOU; however the creation of an online survey was a result of discussions between the University and the San Francisco Municipal Transportation Agency regarding methodology and the best way to capture the data required as part of the MOU For the 2014 survey, University affiliates were asked questions similar to those asked in the 2011 online survey regarding their journey to campus on Wednesday, April 23, 2014 The purpose of the online survey is to provide more detailed information on travel behavior than can be collected during an intercept survey or cordon count In total, 3,959 University affiliates completed the online survey It should be noted that an intercept survey was not conducted in 2011 or 2014, as the MOU only stipulates that a baseline intercept survey should be conducted and information collected in the online survey is

This report provides in-depth analysis of the three surveys with a discussion of methodology, survey design and accompanying results, comparing 2014 survey results to 2011 and 2008 survey results The report concludes with a carbon footprint analysis for commute trips, using the data gathered in the online survey

3 ONLINE SURVEY

INTRODUCTION

In April 2014, San Francisco State University conducted an online survey that asked University affiliates how they travelled to and from campus on Wednesday, April 23rd A total of 3,959 University affiliates responded to the survey, and out of the 3,959 total respondents, 3,077

persons stated that they were on campus on Wednesday, April 23rd In 2011 a total of 3,599 University affiliates responded to the survey, and out of the 3,599 total respondents,

approximately 2,764 persons stated that they were on campus on Wednesday, April 27th

In 2008 a total of 4,386 University affiliates responded to the survey, and approximately 3,300 persons stated they were on campus on Wednesday, April 30th Only those persons who stated they were on campus are included in this analysis unless otherwise noted

SURVEY DESIGN

The online survey was designed to gain an in depth understanding of how University affiliates commute to and from campus Respondents were asked to provide travel information on up to four legs of their journey to and from campus For example, someone who drove to BART and then took the San Francisco State University shuttle from the Daly City BART station to campus would enter trip information for three legs Similarly, if a respondent transferred from one Muni route to another Muni route, they would enter trip information for two legs

Each leg of the journey is treated as a separate question, and respondents are asked to identify the mode they took in each leg, providing the distance they travelled on that mode If respondents took Muni, they were asked to select the Muni route they took, and if a respondent selected BART

or Caltrain, they were asked to identify their start and end stations

Respondents who stated that they drove or carpooled to campus were asked a series of questions related to parking, including their parking location and how much they paid for parking All respondents were asked to answer a number of background questions, such as their place of residence and affiliation with the University

A copy of the online survey instrument is provided in the Appendix A for reference

Constraints and Limitations

Two questions that were previously asked in 2011 and 2008 were mistakenly deleted from the online survey during the survey design process These questions asked respondents when they

methodology was developed to calculate peak hour vehicle trips and Muni M-line and bus route 28/28L ridership The revised methodology is described in further detail in the following section

METHODOLOGY

Prior to conducting data analysis for the online survey, data cleanup and restructuring as well as the establishment of location-based weights were necessary This section provides a discussion of these processes and describes how the results were scaled up to the campus population

Weights

Based on the distribution of online surveys between students and faculty/staff, a weight was created and applied to all online survey analysis On an average day 23,372 students and 2,608 faculty and staff members are on campus (Figure 3-1 and Figure 3-2) However, the student to faculty/staff ratio of the online survey sample was not equivalent to the population, so it was necessary to weight the number of student and faculty/staff responses It should be noted this weight is for those online survey respondents who stated they were on campus on April 23, 2014 Respondents who stated they were not on campus on April 23rd were not included in this analysis

In order to appropriately weight the online survey responses by affiliation, an overall weight was established using the ratio of the total campus population (33,148) to the total number of online survey responses who stated they were on campus (3,077)1 The adjusted weight for students and faculty/staff was then determined by dividing the ratio of population to the sample for students and faculty/staff by the overall weight The weighted number of cases is equal to the number of online survey responses multiplied by the adjusted weight

Figure 3-1: Adjusted Faculty/Staff and Student Responses

Total Population Online Responses Adjusted Weight Response Weighted

Scaling to the Campus Population

In order to scale the online survey data to represent the San Francisco State University population

as a whole, it was necessary to determine how many faculty, staff and students are on campus on

an average day The total campus population was obtained from University Facts brochure and the online survey was used to determine the percentage breakdown by affiliation of those persons who are on campus From this an adjustment factor was established

1 When calculating the weighting factor, those respondents who said they were on campus but who stated an affiliation

of “Visitor/Contractor” or “Other” were not included

Figure 3-2: Population Scale

Affiliation Total Population 2 Adjustment

Factor Daily Population on Campus

The total population was then multiplied by the adjustment factor to determine the daily

population for students and faculty/staff The daily population is used to scale the survey results

to represent the actual San Francisco State University population

Data Clean-up and Data Restructuring

A number of steps were taken to clean and restructure the online survey responses in order to properly format them for analysis

As described in the survey design section, the format of the online survey made it possible for respondents to put multiple legs of their trip in one field In addition, a number of survey

respondents did not input the legs of their trip to campus in a logical or feasible way Listed below are the measures taken to clean-up the data

1 A total of 145 respondents stated that they arrived at campus via Caltrain or BART Since this is not physically possible, the last leg of their journey was adjusted For respondents with a last leg mode of Caltrain, their record was adjusted to reflect Muni M-line

2 For respondents stating that they arrived on campus via BART, their record was adjusted

to reflect SF State Shuttle or Muni Route 28 as their last mode3

Mode Split

In order to determine the mode split for University affiliates commuting to and from campus it was necessary to create several new variables The newly created variables are as follows:

1 Primary Mode To (Arrival Mode) – The “primary mode to” is the mode by which

respondents arrived at campus For the trip to campus, the last leg of the trip was

determined to be the primary mode, as respondents could have between one and four legs

to their trip

2 Secondary Mode To – The “secondary mode to” is the mode respondents used before their primary mode to campus This trip may have occurred on leg 1, 2, or 3 of their trip, depending on the total number of legs Respondents who used only one mode of

transportation to arrive on campus have no recorded secondary mode

2 Source: Faculty and staff population numbers courtesy of University Facts brochure at

3 Primary Mode From (Departure Mode) – The “primary mode from” is the mode by which respondents left campus

In addition to creating new variables, the existing data needed to be restructured in order to meet the requirements of the MOU between the University and the City and County of San Francisco The MOU requires that all persons who park and walk within 10 minutes of campus should be classified as drivers rather than walkers when determining the mode split and peak hour auto trips The following steps were taken to address this requirement:

1 Persons with a primary mode to campus of walking and a secondary mode to campus of driving or carpooling were identified using the primary mode to campus variable and the secondary mode to campus variable

2 A primary mode distance variable was then calculated using the responses given in the survey to the question “Please estimate the distance you travelled in this segment of your trip” Persons whose walk segment was 0.5 mile or less were classified with an auto primary mode Half a mile was used because the average speed of walkers is 3 miles an hour, meaning a 10 minute walk is equivalent to approximately 0.5 miles

3 For persons who did not provide a distance, the location where they parked their car was used Respondents who drove or carpooled and parked on or near campus were asked to select the zone which corresponded to their parking location on a map of the area

surrounding campus The map covers the area bounded by I-280, Lake Merced

Boulevard, Sloat Boulevard, Santa Clara Avenue, Victoria Street, and Head Street

Respondents were given 19 zones to choose from Using a 0.5 mile radius, the zones which are within a 10 minute walk to campus were identified Zones where part but not the entire zone is within a 10 minute walk are considered to be within the 0.5 radius Of the 19 zones, only three are not within the 0.5 mile radius

4 The same steps were then repeated for the trips from campus

A similar methodology was applied to persons whose primary mode is walk and their secondary mode is Muni in order to more accurately determine the peak hour number of Muni trips as required by the MOU The following steps were taken to address this requirement:

1 Using the primary mode distance variable, persons whose walk segment was 0.5 miles or less were reclassified with a Muni primary mode For persons who did not provide a primary mode distance, the “Muni route taken” was used Persons travelling on routes directly serving campus (17, 18, 28, 28L, 29, 88, M) were reclassified with a Muni primary mode Persons travelling on any other Muni routes retained walk as their primary mode

2 The same steps were then repeated for the trips from campus

Vehicles Trips during the Peak Hour

Per the MOU, San Francisco State University is required to establish a baseline of PM peak hour vehicle trips As noted in the constraints and limitations section, questions asking respondents at what time they arrived and departed from campus were mistakenly deleted Given this, data collected as part of the vehicle cordon count was used to establish the peak hour for vehicle trips and to determine what percent of vehicle trips occur during the peak hour

The following steps were taken to determine the number of vehicle trips during the peak hour:

1 Using the cordon count data, a PM vehicle peak hour of 3:00 PM to 4:00 PM was

established with 10% of vehicle trips occurring during this time period This is earlier

than the 2011 peak hour of 5:00 PM to 6:00 PM and the 2008 vehicle peak hour which occurred between 4:00 PM to 5:00 PM

2 The primary mode to and primary mode from campus were used to determine the total number of trips for drive alone, carpool, and drop off and pick up trips

3 The number of carpool trips was reduced by a factor of 2.42 for trips to campus and 2.60 for trips from campus, which is the average number of people in a carpool for trips to and from San Francisco State University The average number of persons in a carpool was determined using responses to the question “how many people were in your carpool”

It should be noted that while the methodology for establishing the PM peak hour for vehicle trips changed, the percentage of trips occurring during the peak hour is approximately the same (10%)

as in previous survey years

Muni Trips during the Peak Hour

Per the MOU, San Francisco State University is required to establish a baseline of peak hour Muni trips for both the campus Muni peak hour as well as the Muni system wide peak hour (5:00 PM to 6:00 PM) As noted in the constraints and limitations section, two questions were mistakenly deleted from the 2014 online survey These questions asked respondents at what time they arrived and departed from campus Given this, the campus Muni peak hour of 9:00 AM to 10:00

AM from the 2011 survey was utilized for this analysis

The following steps were taken to determine the number of Muni trips during both the campus peak hour and Muni system wide peak hour:

1 Using the mode split by time analysis from the 2011 online transportation survey, a campus Muni peak hour of 9 AM to 10 AM was established This is an hour later than the

2008 campus Muni peak hour, which occurred between 8 AM and 9 AM

2 Using the mode split by time analysis from the 2011 online survey, the percentage of Muni trips occurring during the campus Muni peak hour was established

3 The primary mode to and primary mode from campus were used to determine the total number of Muni trips

4 In order to determine the distribution of Muni trips over the six routes directly serving campus (as required in the MOU), two new variables were created that identified which Muni route was taken for the “primary mode to” campus and for the “primary mode from” campus The frequency of the new Muni route variables provided the number of trips taken on each Muni route This distribution was then applied to the total population number of Muni trips

Areas for Additional Consideration

Currently, there are a number of respondents who use the San Francisco State Shuttle in their journey to campus but it is not classified as their mode of arrival on campus, or “primary mode” However, it is highly unlikely that someone who took the San Francisco State Shuttle on their journey to campus would not arrive on campus via the San Francisco State Shuttle Thus, it is recommended for the next survey period that this issue is addressed during the data clean up and

RESULTS

The following section discusses the results of the online survey, focusing on mode split, Muni ridership on the lines that directly serve the campus, parking, and demographics At the end of the chapter, results for a number of demographic questions that were asked of all respondents regardless of whether or not they were on campus that day, are presented Unless otherwise noted, results shown in this section are for only those respondents who stated that they were on campus on April 23, 2014

Figure 3-3: Mode of Arrival to Campus

How Online Survey

Respondents Get to

SF State

2014 (n=3,013)

2011 (n=2,684)

2008 (n=3,292)

% Change

2008 - 2014

% Point Change

Other bus provider

(AC Transit/Golden Gate

Figure 3-4: Number of Legs in Journey to Campus

In 2014 47% of respondents used Muni for a portion of their journey to campus compared to 36%

in 2008, a 22% increase The percentage of respondents stating that they drove for a portion of their trip to San Francisco State University decreased from 34% to 30% between 2008 and 2014,

a 12% decrease In 2014, approximately 26% of respondents took BART, compared to 21% in

2008 and 25% took the San Francisco State University shuttle for one leg of their trip compared

to 21% in 2008 The percentage of respondents walking or biking for a portion of their trip to campus increased between 2008 and 2014

Figure 3-5: All Modes Used to Get to Campus

How Online Survey

Respondents Get to

SF State

2014 (n=3,013)

2011 (n=2,684)

2008 (n=3,292)

% Change

2008 - 2014

% Point Change

students (30.2%), followed by Muni (22.3%) The percentage of graduate students walking increased significantly from 5.8% in 2008 to 12.2% in 2014 Approximately 40% of faculty and staff drive to campus, with the second most common mode being Muni, at 18.8%

All University affiliates participating in the survey, regardless of whether or not they travelled to the main campus on April 23rd, were asked how much they spend each day on their commute to and from campus (Figure 3-6) Fifteen percent do not spend anything on their commute, while 34% spend between $1 and $4 per day Nineteen percent of University affiliates spend $5 to $9 per day, and 19% spend $10 to $14 per day

Figure 3-6: Cost of Commute

Amount Spent on Daily Commute

2014 the peak hour shifted earlier to 3:00 PM As shown in Figure 3-7 the number of peak hour and total daily auto trips has steadily declined since 2008 The number of peak hour trips has decreased by 10.6% and the number of total daily auto trips has decreased by 30.3%

Figure 3-7: Peak Hour and Total Auto Trips (N = Total Campus Population) 4

10 minutes or less to or from campus were also counted as vehicle trips rather than walk trips as required by the MOU

Figure 3-8: Mode Split by Affiliation

How Online Survey

Respondents Get to SF

State Freshman Other Undergraduate Graduate Student

Staff/Admin Faculty

(AC Transit/Golden Gate

Transit/SamTrans) 3.8% 1.2% 1.2% 2.9% 2.2% 1.8% 2.9% 2.0% 0.6% 1.4% 1.5% 1.1% Drove Alone 5.3% 8.5% 11.1% 17.6% 21.0% 23.5% 30.2% 25.9% 30.8% 41.4% 38.4% 45.1%

Motorcycle/Moped 0.0% 0.4% 0.0% 0.5% 1.3% 0.6% 0.7% 1.5% 1.2% 0.2% 0.5% 1.2%

Transit

Muni and BART are the transit systems most heavily utilized by the campus population, with 47%

of San Francisco State University commuters riding Muni and 26% riding BART for some portion

of their journey to campus Two thirds (66%) of campus affiliates take some form of public transportation to get to campus.5

Muni

The figure below shows the percentage of Muni trips that were taken to and from campus via the six Muni routes that directly serve the University Of those commuters who ride Muni to campus, the most heavily traveled routes are bus route 28/28L and metro line M, with 34% and 30% respectively using these routes for the last portion of their journey to campus The percentage of commuters using bus route 28/28L has decreased by four percentage points while the number of riders on bus route 29 increased by four percentage points The percentage of commuters taking metro line M has continued to decline from a high of 45% in 2008 to 35% in 2011 to 31% in 2014

Figure 3-9: Daily Muni trips by Muni route (N = Total Campus Population)

2014

Number of trips

2011

% of all Muni Trips

2011

Number of trips

2008

% of all Muni Trips

PM Figure 3-10 shows the number of trips to and from campus on the routes serving campus during both the San Francisco State University Muni peak and the system-wide Muni peak As noted in the methodology section the 2011 peak period was used for this analysis due to the lack

of arrival and departure data

The peak hour trends are parallel to the daily trends in level of usage, with the metro line M and bus route 28 being the most heavily utilized in both the San Francisco State University peak hour and the system wide peak hour Similar to daily ridership trends, the number of peak hour trips

on the 28/28L and the metro line M has decreased while the number of riders on bus route 29 has increased for both time periods Ridership has remained relatively constant on bus routes 17 and

18

5 This calculation includes BART, Muni, Caltrain, and other bus providers It does not include the SF State Shuttle

Figure 3-10: Peak Hour Muni Trips for the SF State Peak Period (N = Total Campus Population)

Muni Route

Number of trips 9:00 AM – 10:00 AM

2014

Number of trips 9:00 AM – 10:00 AM

2011

Number of trips 8:00 AM – 9:00 AM

Figure 3-11: Peak Hour Muni Trips for the Muni System Wide Peak Period of 5:00 PM to 6:00 PM

(N = Total Campus Population)

direction This is the inverse of what is occurring in 2011 and 2014

Figure 3-12: Peak Hour, Peak Direction Riders for M line (N = Total Campus Population) 6

Figure 3-14: Home County of BART Riders (n=726)

County Percentage of BART Riders

7 Given the lack of time of arrival and departure data, 2011 directionality data was used for this analysis Northbound and southbound trips for the 28/28L line during the AM peak hour were determined by applying a 48% northbound - 58% southbound ratio to the total number of 28/28L line trips, scaled to represent the campus population, during the

AM peak hour This ratio was determined by using the home zip codes of online survey respondents to determine their direction of travel and the number of trips in each direction The same methodology was used in the PM peak and a ratio of 49% northbound – 51% southbound was applied

Parking

Approximately 20% of commuters arrive on campus via driving alone Forty one percent of those University affiliates who drive park on campus and 42% park near campus One percent of drivers stated that they parked at Daly City BART station while seven percent of drivers stated that they parked at a different BART station Less than one percent stated that they parked at a park and ride lot while seven percent of drivers selected “other” with regards to their parking location The April 2014 online survey asked respondents who stated that they parked on or near campus

to identify where they parked The number of responses was scaled to reflect the entire population

of the University Figure 3-15 provides a breakdown of parkers by location

Forty percent or 2,217 of on-campus parkers park in the main parking structure at the center of campus Close to campus, Font Boulevard/Holloway Avenue and Lake Merced Boulevard were the most highly utilized streets with 362 and 215 campus affiliates parking on these streets, respectively

This marks a shift in where campus affiliates are predominately parking near campus In 2011

463 university affiliates parked on 19th Avenue as compared to 98 persons in 2014 and

approximately 692 parked on Junipero Serra Boulevard in 2011 compared to 186 campus

affiliates in 2014

Figure 3-15: Parking On and Near Campus

Survey respondents who stated that they drove to campus were also asked how much they paid to park (Figure 3-16) The majority of those who drove, 52%, had free parking compared to 54% in

2008 Twenty percent paid between $4 and $7 dollars and 21% have a SF State University

semester or yearly parking pass, a significant increase from 2011 and 2008 when only 13% of parkers had a parking pass The Parking and Transportation Department has implemented a program where students are able to purchase Monday/Wednesday or Tuesday/Thursday permits for the semester which explains the increase in the percentage of parkers who use parking passes Given the large number of parkers on Font Boulevard, Holloway Avenue, Lake Merced Boulevard, and the surrounding neighborhoods, it is not surprising that the majority of drivers do not pay for parking

Figure 3-16: Parking Costs

Cost % of Respondents 2014 (n=845)

% of Respondents 2011 (n=1,042)

% of Respondents 2008 (n=1,373)

Incentives & Universal Transit Pass Program

Incentives to Use Other Modes

University affiliates participating in the online survey who stated that they drove to campus on April 23rd were asked what programs would encourage them to use a mode other than driving alone to get to campus They were asked to select their first, second and third choices from the list

of programs shown in the figure below (Figure 3-17)

Figure 3-17: Programs to Encourage Drivers to Use Alternative Modes

Incentives (n=1,030) 1 st Choice 2 nd Choice 3 rd Choice

Ride-sharing with someone who lives near me 23.9% 18.9% 14.6% Improved shuttle service from BART to the

A reduced fare transit pass for Muni was the most popular 1st choice, which was also the number one choice in 2011 Almost 24% of respondents selected ridesharing as their first choice and 19% selected this program as their second choice Twenty one percent of respondents selected

improved shuttle service from BART to the university as their second choice and 15% selected this

as their 3rd choice Approximately 16% of respondents stated that there were no programs which would encourage them to use alternative modes of transportation for their commute to SF State University

Universal Transit Pass

All University affiliates participating in the survey, regardless of whether or not they travelled to the main campus on April 23rd, were asked if they would support a student transportation fee aimed at providing a transit pass offering unlimited Muni rides, as well as a discount on BART travel system wide if it provided a savings for all students who ride Muni and/or BART Eighty nine percent of respondents said they would support a student fee for this purpose while 11% said they would not

Survey respondents were asked what was the most they would be willing to pay for unlimited Muni access as well as a discount on all BART travel throughout the BART system (Figure 3-18)

Figure 3-18: Willingness to Purchase a Universal Transit Pass

Price per Month

Approximately 81% of respondents would be willing to pay some amount of money to receive a universal transit pass, an increase in support from 2011 when only 70% of respondents stated that they would be interested in this type of pass Almost half of respondents (49%) would be willing

to pay up to $35 per month for this type of pass Given that Muni Fast Passes with unlimited BART access within San Francisco will cost $80 a month starting September 1, 2014, or about

$320 a semester, some subsidy from other funding sources will be necessary to implement a universal transit pass program

Background Information for All Survey Respondents

All online survey respondents, regardless of whether or not they were on campus on April 23rd, were asked to provide their affiliation with the University as well as information on where they live by providing their zip code and the name of their apartment or residence hall if they stated that they lived on campus Those respondents who were not on campus are referred to as “no respondents,” and respondents who did travel to the main campus are referred to as “yes

respondents”

The majority of “yes respondents”, 55%, stated that they were undergraduates (excluding

freshman) Staff or administrator was the second most common affiliation, 14%, followed by graduate student, at 10% The majority of “no respondents” are undergraduates, 49%, followed by graduate student, at 25%

Figure 3-19: Affiliation with San Francisco State University

Affiliation

Percentage Yes Respondents (n=3,105)

Percentage

No Respondents (n=854)

Percentage Overall (n=3,959)

Percentage

No Respondents

All survey respondents were asked what zip code they live in and responses to this question were mapped to show what parts of the Bay Area San Francisco State University affiliates live in As shown in Figure 3-21 the largest concentration of San Francisco State University affiliates live within San Francisco and more specifically within the direct vicinity of the University Outside of San Francisco the largest concentration of San Francisco State University affiliates are found in Daly City, followed by South San Francisco, San Bruno, Pacifica, and Alameda

Figure 3-21: Campus Affiliates by Zip code

Using the zip code data collected, San Francisco State University affiliates were grouped into four geographic regions; San Francisco, East Bay, North Bay, and Peninsula (Figure 3-22) As seen in the zip code map the largest concentration of San Francisco State University affiliates is in San Francisco with almost half living in the same city as the University Almost 28% percent of San Francisco State University affiliates live in the East Bay and 20% live on the Peninsula Only 3% of San Francisco State University affiliates live to the north of San Francisco in Sonoma or Marin counties

Figure 3-22: Location of SF State University Affiliates 8

Location

Percentage Yes Respondents (n=2,502)

Percentage

No Respondents (n=672)

Percentage Overall (n=3,801)

4 CORDON COUNT

INTRODUCTION

On Wednesday, April 23, 2014 a cordon count was conducted at San Francisco State University per the requirements of the MOU between the University and City and County of San Francisco The cordon count provides information on where University affiliates are entering and exiting campus and at what times of day they enter and exit The data collected from the cordon count provides a sense of how many people come to campus each day which is helpful when scaling up the online survey responses to the daily campus population

METHODOLOGY

The cordon count methodology was revised significantly from the 2011 survey to focus on vehicles entering and existing campus rather than pedestrians and cyclists The primary purpose for the change in methodology was to better capture the number of vehicle trips generated by SF State which is a metric that must be monitored per the MOU between the University and City and County of San Francisco

The count was conducted from 7:00 AM to 7:30 PM at 9 locations around the campus (Figure 4-1) This is the same time period used in 2011 when the duration of the cordon count was

extended by one hour as compared to 2008 to capture those students leaving after classes that end at 7 PM The locations were selected as they represent all public vehicle entry access points including access to interior roadways as well as parking facilities

At each location vehicles were counted in 15 minute increments Surveyors were instructed to distinguish between vehicles with only a single driver, carpools (vehicles with two or more

persons), motorcycles, and other vehicles Other vehicles included campus vehicles, delivery trucks, transit vehicles, and security vehicles Surveyors were instructed to include drop-offs as a carpool vehicle One counter was stationed at each location A copy of the cordon count tally sheet used by the surveyors is provided in Appendix A for reference

Figure 4-1: Cordon Count Locations

RESULTS

In total, from 7:00 AM to 7:30 PM a total of 9,638 distinct vehicle entries were counted entering and exiting campus on April 23, 2014 A comparison to 2011 and 2008 data is not presented due

to the fact that the cordon count methodology has changed significantly

Figure 4-2 provides a breakdown of vehicles entering and exiting campus by the 9 cordon

locations The entry point at State Drive and Lake Merced Boulevard saw the largest number of vehicles entering and exiting, largely due to the fact that State Drive connects to the primary parking facility on campus Holloway Avenue at Tapia Drive and Font Boulevard at Tapia Drive saw the second highest number of vehicle trips This is partially due to the fact that this is a popular area for drop-offs

Figure 4-2: Number of Vehicles Entering and Exiting by Location

Location Entering Exiting Total

1 Holloway Ave & Administration Bldg 55 59 114

2 Holloway Ave & Cardenas 53 46 99

3 Holloway Ave & Arella 82 83 165

4 Holloway Ave & Tapia Dr 1,066 NA9 1,076

5 Font Blvd & Tapia Dr NA10 1,027 1,027

6 Font Blvd & Mary Wald Hall 129 121 250

7 State Dr & Lake Merced Blvd 3,201 2,437 5,638

8 N State Dr & Lake Merced Blvd 435 765 1,200

The distribution of vehicles entering and exiting by time varies by cordon count location;

however, at most locations vehicle trips peaked between 9:00 AM and 11:00 AM (Figure 4-3) and 5:00 PM to 7:30 PM For the campus as a whole, the peak period for vehicles entering and exiting was 9:oo AM to 10:00 AM

Figure 4-3: Count of Vehicles Entering and Exiting by Location and Time

Location

7:00 AM - 9:00 AM

9:00 AM - 11:00 AM 11:00 AM - 1:00 PM 1:00 PM - 3:00 PM 3:00 PM - 5:00 PM 5:00 PM - 7:30 PM

1 Holloway Ave & Administration Bldg 17 28 16 20 9 24

4 Holloway Ave & Tapia Dr 100 198 168 197 218 185

7 State Dr & Lake Merced Blvd 1,014 1,104 962 762 883 913

8 N State Dr & Lake Merced Blvd 142 125 145 151 270 367

Total 1,423 1,786 1,605 1,391 1,672 1,761

When counting vehicles entering and exiting campus, surveyors noted if they were single

occupancy vehicles, carpools, motorcycles or other vehicles such as campus vehicles, delivery trucks, or security vehicles Figure 4-4 provides a count of vehicles by vehicle type for every hour

of the cordon count While the largest percentage of vehicle trips are single occupancy vehicle trips (80%), carpool trips made up almost 14% of all vehicle trips

Overall, the highest number of vehicles entering and exiting campus occurred between 9:00 AM and 10 AM, with 10.3% of vehicle trips occurring during this time period In the

afternoon/evening the peak period for vehicle trips occurred between 3:00 PM and 4:00 PM with 10% of vehicle trips occurring during this time period

Figure 4-4: Count of Persons Entering and Exiting by Mode and by Hour

Drive Alone Carpool Motorcycle Other Total Total

Trips % Trips by Hour