Community-based Assessments ofTransportation Needs
Artist: Aurélia Durand

http://arcg.is/1XOnbH

Living Cully
Community Mobility
Needs Assessment is
an assessment created
byVerde in
partnership with
Hacienda Community
Development
Corporation (CDC),
Forth, the Cully
Boulevard Alliance,
and the City of
Portland.

Method
The assessment collected both qualitative and quantitative data through the
administration of 102 surveys and a focus group of over 35 participants.
Survey Goals
1. Understand participants current transportation needs and behaviors;
2. Understand participants’ familiarity with alternative forms of transportation
such as electric vehicles (EVs), electric bikes, and ridesharing/carsharing;
3. Identify participants’ ideal future state in regard to transportation solutions;
4. Identify what solutions for the Living Cully Plaza/Las Adelitas redevelopment
are most popular among participants and;
5. Understand the basic demographic profile of participants.

41% of residents preferred method of transportation was driving and
40% of residents preferred using public transportation (Figure 4).
Carshare was listed as a survey choice but not one resident
indicated this as their preferred transportation. This could be due
to the lack of presence carsharing companies choose to have in the
Cully neighborhood and the technology associated with this
particular form of transportation. Similarly, more residents preferred
to use a taxi service than a rideshare service such as Uber or Lyft.
Participants commute times were highly variable and 75% of
responses were evenly distributed amongst the 15-60 minute
categories. However, when compared with the method of
transportation, those who took public transit most commonly
responded with a commute time of 30-60 minutes while those
who drive responded 20-30 minutes.

Collaborative Research - OPAL, Forth and PSU with support from the 11th-Hour Project, the City of
Portland, and the National Institute for Transportation and Communities at PSU
Community-based Assessment ofTransportation Needs to
inform City of Portland Smart Cities Plan
Aaron Golub, Toulan School of Urban Studies and Planning, Portland State University
Vivian Satterfield, Director of Strategic Partnerships at Verde (formerly of OPAL Environmental Justice Oregon)
Michael Serritella, Portland Bureau of Transportation
Jai Singh, (formerly of OPAL Environmental Justice Oregon)

Smart mobility
Transportation services, operations and/or traveler information systems
assisted by fast, real-time, wireless, distributed data streams
Autonomous, electric, connected and shared mobility technologies
Almost always require traveler to have internet connectivity and direct
linking to bank or credit card accounts
Early/current examples: Bikeshare/e-scooters, ridesourcing (Uber/Lyft, etc),
transit information apps, smart transit fare payment systems

https://www.portlandoregon.gov/transportation/69999
Portland Smart Cities
UB Mobile PDX
proposal to DOT

As public transportation providers and agencies move to
payment, information, trip-planning and last/first-mile
connectivity systems which require travelers to have access to
private internet and banking services
What steps can be taken to ensure that the coming wave of
“smart” transportation innovations will benefit all groups
equitably?
Or even better - achieve transportation justice?

Existing research on these issues
• FDIC 2015 survey on banking access: ~20% underbanked, 7% unbanked
• Much higher for low-income and POC
• Low incomes, fees and trust/privacy issues are primary causes
• Digital divide issues are widely noted in existing research on smart mobility (see
reference list on last frame of this presentation)
• For example – work done here at PSU on equitable access to bikeshare found:
• Lack of diverse payment methods and wifi/internet access a barrier to use
• Recommended increasing payment options, improve connectivity with transit systems,
and more robust outreach and educational programs

Research Questions
● How can smart mobility technologies address the current and future needs
of transportation disadvantaged communities?
● What are the barriers to using smart mobility technologies experienced by
different communities?
● What potential solutions show the most promise in overcoming these
barriers?

Transportation disadvantaged
communities
• Low-income
• Communities of color
• Mobility challenged
• Age
• English proficiency

Transportation disadvantaged
communities
• Low-income
• Communities of color
• Mobility challenged
• Age
• English proficiency
Focus on East Portland

Source: Metro 2018 regional transportation plan - Appendix E – Transportation Equity Evaluation

Source: Metro, Regional Snapshot
Displacement of People of
Color

Methods
Two focus groups
Bus Riders Unite
Lower-income East Portland residents
Larger sample survey
Online and in-person at several community events and intercepts on buses and transit stops
August - October of 2017
308 survey responses
Representing a racially, socio-economically diverse group of individuals
46% of survey respondents identifying themselves as people of color
55% reporting lower than the study area’s median income; solid distribution of ages

Survey sample

Study Area vs
Survey
responses
Portland
Gresham

Income comparison
Study area Survey sample
Median household income $43,700 ~$35,000
Poverty rate 23.7% ~32%
Source: 5-YR American Community Survey

Age profiles for the study area and survey sample

Race/ethnicity profiles for the study area and survey sample

Analysis methodology
• Analyze focus group and survey data for overall results
• Compare survey responses between:
• Non-HispanicWhite and respondents of color
• Low-income and high-income
• Baby Boomers, Gen-X and Millennials (see report)
• Do responses differ?
• Differences tested for statistical significance

Sample breakdown:
Low-income = <$50k (~70% of AMI)

Results

Basic transportation issues
https://pamplinmedia.com/go/42-news/368510-250722-trimet-to-decriminalize-fare-evasion

Transportation access
Overall Income Race/ Ethnicity
How many cars, trucks, vans, or motorcycles are available in
your household for you to use? [Multiple choice]
Almost 30% had no
vehicle; 40% had
one vehicle
Higher more ND
Does your employer / school provide you a transit pass?
[Y/N]
28% Higher more ND
Does your employer / school provide free parking? [Y/N] 23% Higher more ND
Does your employer / school provide secure onsite bicycle
parking? [Y/N]
26% Higher more ND
Does your employer / school provide you a Biketown
subscription? [Y/N]
4% ND ND

Transportation access
Overall Income Race/ Ethnicity
How many cars, trucks, vans, or motorcycles are available in
your household for you to use? [Multiple choice]
Almost 30% had no
vehicle; 40% had
one vehicle
Higher more ND
Does your employer / school provide you a transit pass?
[Y/N]
28% Higher more ND
Does your employer / school provide free parking? [Y/N] 23% Higher more ND
Does your employer / school provide secure onsite bicycle
parking? [Y/N]
26% Higher more ND
Does your employer / school provide you a Biketown
subscription? [Y/N]
4% ND ND
Higher income – more access to
support for commuting

Commuting behavior
Overall Income Race/ Ethnicity
The most common mode of travel to work: Drive alone [Y/N] 27.5% Higher more ND
The most common mode of travel to work: Carpool [Y/N] 5% Lower more ND
The most common mode of travel to work: Public transportation [Y/N] 36% Lower more POC more
The most common mode of travel to work: Walked [Y/N] 12% Lower more ND
The most common mode of travel to work: Bicycle [Y/N] 23% ND ND
The most common mode of travel to work: Ridesourcing (TNCs) [Y/N] 2.3% Lower more
(4.1 vs 0%)
ND
The most common mode of travel to work: Work at home [Y/N] 6% Higher more NHW more

Commuting behavior
Overall Income Race/ Ethnicity
The most common mode of travel to work: Drive alone [Y/N] 27.5% Higher more ND
The most common mode of travel to work: Carpool [Y/N] 5% Lower more ND
The most common mode of travel to work: Public transportation [Y/N] 36% Lower more POC more
The most common mode of travel to work: Walked [Y/N] 12% Lower more ND
The most common mode of travel to work: Bicycle [Y/N] 23% ND ND
The most common mode of travel to work: Ridesourcing (TNCs) [Y/N] 2.3% Lower more
(4.1 vs 0%)
ND
The most common mode of travel to work: Work at home [Y/N] 6% Higher more NHW more
Lower income – more multi-modal and
users of ridesourcing (TNC) for
commuting

Paying for transit
Overall Income Race/ Ethnicity
How do you typically pay for the TriMet fare: On board [Y/N] 42% Lower more (51 vs
33%)
POC more (49 vs 37%)
How do you typically pay for the TriMet fare: TriMet or retail store
[Y/N]
10% ND ND
How do you typically pay for the TriMet fare: School or Work [Y/N] 15% Higher more ND
How do you typically pay for the TriMet fare: Online or Phone App
[Y/N]
35% Higher more (42 vs
32%)
NHW more (41 vs
31%)
How do you typically pay for the TriMet fare: Social service agency
[Y/N]
3% Low more ND

Paying for transit
Overall Income Race/ Ethnicity
How do you typically pay for the TriMet fare: On board [Y/N] 42% Lower more (51 vs
33%)
POC more (49 vs 37%)
How do you typically pay for the TriMet fare: TriMet or retail store
[Y/N]
10% ND ND
How do you typically pay for the TriMet fare: School or Work [Y/N] 15% Higher more ND
How do you typically pay for the TriMet fare: Online or Phone App
[Y/N]
35% Higher more (42 vs
32%)
NHW more (41 vs
31%)
How do you typically pay for the TriMet fare: Social service agency
[Y/N]
3% Low more ND
Lower income and POC – Less use of
online/phone apps and higher use of
on-board (cash) payment

Barriers to Access: Documentation, Data and Banking

Access to data and internet
Overall Income Race/ Ethnicity
How frequently do you use email and/or the internet? [Frequency,
times per month]
88.8 Higher more (96 vs 84) NHW more (93 vs 85)
At your home, do you have access to the Internet? [Y/N] 92% Higher more (98 vs
88%)
NHW more (97 vs 87%)
If you work, at your workplace, do you have access to the Internet?
[Y/N]
79% (out of 84% who
work)
Higher more (99 vs 87%
of those who worked
outside the home)
ND
Is your cell phone a smartphone? [Y/N] 89% ND POC more (91 vs 89)
If you have a cell phone, how frequently do you use public Wi-Fi in
order to reduce your data use? [Multiple Choice]
65% connect to Wi-Fi
whenever possible or
occasionally
Lower more (72 vs 63%) ND
Have you ever had to cancel your cell phone service for a period of
time because of cost? [Y/N]
25% Lower more (35 vs 12%) POC more (33 vs 18%)

Access to data and internet
Overall Income Race/ Ethnicity
How frequently do you use email and/or the internet? [Frequency,
times per month]
88.8 Higher more (96 vs 84) NHW more (93 vs 85)
At your home, do you have access to the Internet? [Y/N] 92% Higher more (98 vs
88%)
NHW more (97 vs 87%)
If you work, at your workplace, do you have access to the Internet?
[Y/N]
79% (out of 84% who
work)
Higher more (99 vs 87%
of those who worked
outside the home)
ND
Is your cell phone a smartphone? [Y/N] 89% ND POC more (91 vs 89)
If you have a cell phone, how frequently do you use public Wi-Fi in
order to reduce your data use? [Multiple Choice]
65% connect to Wi-Fi
whenever possible or
occasionally
Lower more (72 vs 63%) ND
Have you ever had to cancel your cell phone service for a period of
time because of cost? [Y/N]
25% Lower more (35 vs 12%) POC more (33 vs 18%)
Internet and data access fairly high for
everyone
Lower income and POC – Lower use of
internet and access to cell/data/internet

Access to banking and credit
Overall Income Race/ Ethnicity
Do you have a credit card or prepaid card account? [Y/N] 72% Higher more (90 vs 60%) NHW more (79 vs 64%)
Do you have a checking or savings account? [Y/N] 90% Higher more (98 vs 85%) NHW more (95 vs 84%)
How comfortable are you in linking your bank account or
credit card to transportation apps on your phone? [Likert]
3.3 Higher more (3.7 vs 3.1) NHW more (3.6 vs 3)
Do you have a driver’s license? [Y/N] 80% licensed Higher more (95 vs 70%) NHW more (89 vs 67%)

Access to banking and credit
Overall Income Race/ Ethnicity
Do you have a credit card or prepaid card account? [Y/N] 72% Higher more (90 vs 60%) NHW more (79 vs 64%)
Do you have a checking or savings account? [Y/N] 90% Higher more (98 vs 85%) NHW more (95 vs 84%)
How comfortable are you in linking your bank account or
credit card to transportation apps on your phone? [Likert]
3.3 Higher more (3.7 vs 3.1) NHW more (3.6 vs 3)
Do you have a driver’s license? [Y/N] 80% licensed Higher more (95 vs 70%) NHW more (89 vs 67%)
Clear banking / credit access
issues

Familiarity and comfort with smart mobility
technologies
https://www.theverge.com/2018/1/12/16880978/gm-autonomous-car-2019-detroit-auto-show-2018

Impressions of new transportation technologies
Overall Income Race/ Ethnicity
How familiar are you with electric cars? [Likert] 3.3 Higher more NHW more
How interested are you in owning an electric car? [Likert] 3.5 ND ND
How familiar are you with autonomous vehicles? [Likert] 2.7 Higher more NHW more
How comfortable would you be riding in an autonomous vehicle? [Likert] 2.6 Higher more ND

Impressions of new transportation technologies
Overall Income Race/ Ethnicity
How familiar are you with electric cars? [Likert] 3.3 Higher more NHW more
How interested are you in owning an electric car? [Likert] 3.5 ND ND
How familiar are you with autonomous vehicles? [Likert] 2.7 Higher more NHW more
How comfortable would you be riding in an autonomous vehicle? [Likert] 2.6 Higher more ND
Lower income and POC – Less
familiar/comfortable with new vehicle
technologies

Smart mobility applications
Overall Income Race/ Ethnicity
If you have a smartphone, how often do you use your phone to get public transportation
information? [Frequency, Days per Month]
13.4 Lower more POC more
If you have a smartphone, how often do you use your phone for navigation? [Frequency,
Days per Month]
15.8 ND ND
If you have a smartphone, how often do you use your phone to reserve a ridesourcing or
carsharing service? [Frequency, Days per Month]
2.2 Lower more ND
If you have a smartphone, how often do you use your phone to use bikesharing? [Frequency,
Days per Month]
1.2 ND ND

Smart mobility applications
Overall Income Race/ Ethnicity
If you have a smartphone, how often do you use your phone to get public transportation
information? [Frequency, Days per Month]
13.4 Lower more POC more
If you have a smartphone, how often do you use your phone for navigation? [Frequency,
Days per Month]
15.8 ND ND
If you have a smartphone, how often do you use your phone to reserve a ridesourcing or
carsharing service? [Frequency, Days per Month]
2.2 Lower more ND
If you have a smartphone, how often do you use your phone to use bikesharing? [Frequency,
Days per Month]
1.2 ND ND
Lower income and POC – More use of existing
smart mobility applications

Language
“I like the [transit] screens in downtown. I can read a little bit of English , but the time I
was lost, I had to ask because the instructions were only in English. So not everyone
can understand. In a situation that is unexpected like that, I don’t know what the
screen or the conductor is saying then it’s frustrating. It makes you fearful…”
Many smartphone apps, transit signage, etc. are not available in languages other than
English

Trust / privacy / security
“I do have a bank account, but am afraidTriMet will use it and share it.”
“I don’t have any information on my phone. I am afraid people will hack my phone. I
would rather pay cash.”
Identity theft could be devastating to a low-income person – these issues are likely to
be underappreciated by middle-class planners

Recommended Policies – Ranked
#1 Improve real time communication between buses and riders about crowding,
arrival time, etc.
#2 Public wifi and charging stations for smartphone/mobile technology
#3 Rebates or financing to help buy clean electric vehicles
#4 Smartphone apps for transportation services translated to languages other than
English
#5 Autonomous neighborhood shuttles and micro-transit

Relevant Findings
• Smart mobility technologies could potentially address many of the needs
of transportation disadvantaged communities
• Designed to facilitate multi-modal travel
• Respondents of color were more likely to own a smartphone than their
counterparts
• More regular users of currently available smart mobility applications
• Significant barriers exist which prevent smart mobility technologies from
benefiting all communities
• Un- and under-banked / Heavy reliance on cash
• Lower access to data and internet
• Language / translation

Thanks to our survey
respondents and focus group
participants…

Additional resources
• Papangelis, K.,Velaga, N., Ashmore, F., Sripada, S., Nelson, J., & Beecroft, M. (2016). Exploring the rural passenger experience, information needs and
decision making during public transport disruption. Research inTransportation Business & Management, 18, 57-69.
• Alessandrini, A., Campagna, A., Site, P. D., Filippi, F., & Persia, L. (2015). AutomatedVehicles and the Rethinking of Mobility and Cities.Transportation
Research Procedia, 5, 145-160.
• Rode, P., Floater, G.,Thomopoulos, N., Docherty, J., Schwinger, P., Mahendra, A., & Fang,W. (2017). Accessibility in Cities:Transport and Urban Form.
Disrupting Mobility, 239-273.
• Velaga, N., Beecroft, M., Nelson, J., Corsar, D., & Edwards, P. (2012).Transport poverty meets the digital divide: accessibility and connectivity in rural
communities. Journal ofTransport Geography, 21, 102-112.
• Acheampong, R.A.,Thomoupolos, N., Marten, K., Beyazit, E., Cugurullo, F., & Dusparic, I. (2018). Literature Review on the Social Challenges of
AutonomousTransport. ShortTerm Scientific Mission Report for COST Action CA16222 “Wider Impacts and Scenario Evaluation of Autonomous and
ConnectedTransport (WISE-ACT).
• Gruel,W. & Stanford, J. (2016). Assessing the Long-Term Effects of AutonomousVehicles: A Speculative Approach.Transportation Research Procedia, 13,
18-29.
• Grush, B. & Niles, J. (2017).Transit Leap: A Deployment Path for Shared-Use AutonomousVehicles that Supports Sustainability. Disrupting Mobility,
291-305.
• Hörl, S., Ciari, F., & Axhausen, K. (2016). Recent Perspectives on the Impact of AutonomousVehicles. Institute forTransportation Planning and System,
1-37.
• Litman,T. A. (2017B). AutonomousVehicle Implementation Predictions: Implications forTransport Planning.VictoriaTransport Policy Institute, 1-23.
• McNeil, N., Dill, J., MacArther, J., Broach, J., & Howland, S. (2017). Breaking Barriers to Bike Share: Insights on Equity.Transportation Research and
Education Center (TREC). 1-20..
• Brakewood, Candace, and George Kocur. "UnbankedTransit Riders and Open Payment Fare Collection."Transportation Research Record: Journal of the
Transportation Research Board 2351 (2013): 133-141.