Pittsburgh
Smart Loading Zones

Reducing the fears and blockers that hinder the widespread adoption of Smart Loading Zones.

Project Duration

September - December 2023

Role

UX Researcher and Designer

the problem

In 2022, the city of Pittsburgh implemented Smart Loading Zones (SLZs) to effectively manage curb space, enhance delivery efficiency, and alleviate congestion and emissions. However, no effort was made to solicit feedback from nearby residents during the implementation process.

Our objective was to comprehensively assess the impact of SLZs on residents and to evaluate and develop potential future interactions for the program's expansion.

the solution

Revised signage

Real-time notifications

GoMobile integration

background research

  • Conducting a heuristic evaluation was an opportunity for us, as a team, to go through the system and compare these products with a list of predefined design principles. In this case we used Nielsen’s Ten Usability Heuristics.

The first step in our process was to conduct background research. To do this we interacted with the physical artifacts of the SLZS to include the curbs and signs. Additionally, we conducted a heuristic evaluation of the digital artifacts of the SLZs such as the online account page.

  • Curb view

  • Camera

  • Informational Sign

  • Curb Sign

  • Home Page

  • Registration Page

  • Payment Page

The key takeaways from our background research were that:

  1. The SLZ initiative was sponsored by the US Department of Energy with an underlying goal of minimizing emissions, in addition to the goal of minimizing congestion in Pittsburgh

  2. The SLZ initiative is centered around the rapid rise in commercial vehicle activity

  3. There has been significant pushback from local business owners who believe they are losing business as a result of the SLZs

  4. The online SLZ account page is designed to cater to dozens of different vehicle and driver types and requires the user to share extensive personal informational

With our background research behind us, it was time to narrow in on one specific need within the problem space, and define our research goals…

reframing

We started the narrowing process by first synthesizing all of our findings up until this point. We conducted a walk the wall session which allowed us to re-immerse ourselves in the data and analysis we had conducted thus far.

Following our walk the wall we were ready to conduct a reframing activity called reverse assumptions that would help us to dig deeper and possibly uncover the problem behind the problem.

  • Reverse assumptions is a great exercise to challenge what is assumed to be true. Why not think outside the box? Why restrict yourself?

Reversing these assumptions then prompted us to discuss the areas of opportunity in our problem space, and then select one area in which we wanted to focus our project on. 
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The common theme we found through this exercise was that there seemed to be a general user distrust of the SLZ initiative.
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From our background research it seemed that a lack of effective communication about the purpose of the SLZs, the pricing structure, and lack of feedback on user activity and billing may have caused this distrust.

With this we formed our how might we question and defined our project:

"How might we build trust by communicating effectively with delivery drivers, and increase awareness surrounding the SLZ initiative?"

  • I love "how might we's" because they are a way to turn a negative into a positive, and to see the user’s needs as an opportunity.

With our project focus narrowed, we needed to identify our research goals, what questions would allow us to accomplish those goals, and then align those questions with research methods.
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Our research goals became:

  1. Our biggest hurdle is user distrust. How can we make our users more aware of the purpose of the program in order to increase user trust?

  2. Another big hurdle is matching the public’s mental model of parking and loading zones to the SLZs. How can we align the public’s understanding of the current model of parking and loading zone usage with the model presented by the SLZs?

Examples of reverse assumptions

We found that many assumptions had been made by the City of Pittsburgh in their creation of the SLZs so we thought through the assumptions that had been made about the public’s thoughts, emotions, and behaviors surrounding the SLZs.

contextual research

Once we had completed our observations and interviews we joined together for an interpretation session in which we reviewed our findings. We then used affinity clustering to reveal broader themes. 

Our research clearly showed that there was:

  1. A lack of effective communication

  2. Fear of monetary consequences

  3. Lack of perceived efficiency

  4. Lack of intuitiveness

  • We had very little luck with speaking with delivery drivers because we were attempting to intercept them in the middle of their shifts. To counter this we attempted to speak with in-house restaurant delivery drivers but we were met with the same unsuccessful results. With the time and resource constraints we were under we had to pivot and pivot quickly. We therefore spoke with business owners and locals in the restaurant industry on streets that had received purple curbs. In the future, one way to take this project forward would be to focus it back on local delivery drivers.

To help us to express what we were learning and form a common understanding we generated empathy maps and user journey maps:

To best elicit the information we needed we knew we would need to conduct contextual research specifically in the form of interviews and observations. We wanted to understand the delivery driver’s needs, motivations, and behaviors. In teams of two we set out to the streets of Pittsburgh to conduct both observations and intercept interviews.

Empathy map

user journey map

People are uncertain and fearful of SLZs because their use cases and target users are broad, not well-defined and not well-communicated, which places them in an ambiguous space between regular parking and loading

Finally, with this analysis and synthesis we generated six key insights:

SLZ users, who try to be parked for only a brief amount of time, will look for the path of least resistance in order to minimize their already brief time on task

People prefer using familiar and existing systems when conducting comparable tasks. When people do need to interact with new systems, they are more inclined to do so if they can draw parallels to existing systems

People’s understanding of the parking fees and their strict enforcement seem to be the most important factors impacting adoptability

People see momentary parking to pick up food as a transient activity; its not an essential step in their mental journey

People need obvious, low-tech, and well-located communications on curbs to decrease the fear of the unknown and increase the desirability of the SLZs

How might we identify and reduce fears and blockers that are leading to low SLZ adoptability by Pittsburgh drivers conducting curbside pickup activities?

Through the process of generating our insights and creating models we decided that we needed to reframe our how might we to be:

With these insights in mind we turned to speed dating with storyboards. We kicked this process off by playing crazy 8s with our new insights and how might we statement. The goal with this was to brainstorm a new set of ideas that met user needs.

From our insights it became clear to us that our key user needs were:

  1. I need to be able to interact with the SLZ, no matter my technical literacy

  2. I need to be able to quickly and efficiently pick up my food

  3. I need to be able to see if I am allowed to use the SLZ, and how I can do so

  4. I need to not be charged for short term parking

We then each generated three storyboards based on each user need with the goal of showing our storyboards to people and seeing how they reacted to each storyboard with each storyboard getting progressively riskier and more uncomfortable.

We tested our storyboards with four users and took away that

  1. Drivers generally don’t object to the concept of paying for parking, rather they find the process of paying for parking to be inconvenient

  2. Users are sympathetic to the need for camera-based enforcement

  3. Poor signage is the biggest deterrent of SLZ usage

  • Speed dating with storyboards is a method used to rapidly evaluate multiple concepts so that you can learn about how people react to ideas while taking into account contextual and social factors. The goal is to validate user needs and values, and identify conceptual risk factors.

Users need to be able to quickly and efficiently pick up their food

As a result, three of our four needs were validated:

Users need to be able to see if they are allowed to use the SLZ, and they need to know how

Users need to be able to interact with the SLZ, no matter their technical literacy

Integrating SLZ payment/parking with the Pittsburgh Go Mobile app

Speed dating

This then led us to think of new design opportunities:

New and improved signage

Option of multiple modes of payment

Lo-fidelity prototypeS

To begin, we used parallel prototyping to create four different loading zone sign designs, then consolidated them into one lo-fidelity prototype. We also developed a mobile application prototype to provide additional information to drivers.

We tested our prototypes with local Pittsburgh drivers and delivery drivers, focusing on five key assumptions:

  1. Clear signs will increase SLZ adoptability

  2. Renaming the zones to "Park and Load" will provide drivers with clarity

  3. Users are comfortable with camera enforcement if there's a 15-minute grace period

  4. Users will understand the per-minute rate despite differing mental models

  5. Users are familiar with downloading and using mobile apps, specifically PGH Go Mobile

Our team aimed to enhance the adoptability of Smart Loading Zones (SLZs) by creating clear and informative instructions for users.

So what did our testing reveal?

Following our testing we came up with a number of proposed changes:

  1. Introduce mailed billing

  2. Include camera enforcement and automatic timer steps on the sign

  3. Clarify that no action is needed to start the timer

  4. Relocate the camera icon for better visibility

  5. Use clearer icons to indicate the zone's use

  6. Display the GoMobile logo prominently

  7. Adjust the fee ladder colors to match users' mental models

  8. Move the payment section higher on the sign

High-fidelity prototype

‍We revamped the signage to ensure it spoke clearly to every driver

Armed with these findings, we embarked on designing a high-fidelity prototype that addressed these challenges head-on. Here’s how we transformed our design:

We also refined the GoMobile Park and Load feature

To then validate our designs, we conducted extensive usability testing. We engaged local Pittsburgh drivers in think-aloud sessions, gauging their initial impressions and comprehension from a distance. We then invited participants to interact closely with the signage and app prototypes, probing their understanding of payment processes and enforcement details. We solicited feedback on the clarity of information hierarchy, iconography, and overall user experience.

Our efforts yielded valuable insights:

  1. We found that users appreciated the transparency provided by notifications and the immediate visibility of the "15 minutes free" offer.

  2. Challenges included confusion over static timer dials and the clarity of icons.

  3. Recommendations for clearer fee representation and better visibility of alternative payment options were noted.

next steps

With these final insights in mind, we would be well-positioned to further refine our prototypes if given the opportunity.

A few of the elements we would focus in on would be:

  1. Exploring dynamic elements for timer dials to enhance user understanding.

  2. Iterating on iconography to better convey inclusivity and user permissions.

  3. Enhancing fee representation with clearer visual cues and strategic placement.