Gaia

Team

Yuehui Du (Designer)

Iris Cai (Designer)

Angela Nam (Designer)

Aishwarya Rane (Designer)

Contribution

Value Creation

UI/UX Design

User Research

Motion Design

Prototyping

Timeline

5 Weeks

Sep. - Nov. 2022

Tools

Vioce Flow

Figma

Illustrator

After Effects

Premier Pro

Project Type

Studio project collaborated with Pittsburgh Regional Transit (PRT)

Overview

"Hey Ollie!" to meet your companion on bus.

Ollie is a conversational AI that keeps passengers informed during their ride on the public transportation, ensures their safety, provides accessibility assistance, and adds enjoyment to your ride, making every trip better for everyone.

"Hey Ollie!" to meet your companion on bus.

Ollie is a conversational AI that keeps passengers informed during their ride on the public transportation, ensures their safety, provides accessibility assistance, and adds enjoyment to your ride, making every trip better for everyone.

"Hey Ollie!" to meet your companion on bus.

Ollie is a conversational AI that keeps passengers informed during their ride on the public transportation, ensures their safety, provides accessibility assistance, and adds enjoyment to your ride, making every trip better for everyone.

Interaction through Mobile

We prioritize the mobile experience, recognizing it as the most accessible device during transportation rides. The interface boasts interactive and conversational elements, enabling passengers to seamlessly interact with Ollie for assistance. Features include shortcuts for primary functions, typing for searches, and natural language interaction for queries. Ollie consistently provides pertinent information and recommendations whenever needed.

Interaction through Kiosk

During our contextual inquiry, we identified a chance to repurpose the interactive screen already installed at the bus stop. We developed an interactive kiosk featuring Ollie's capabilities, enhancing the user experience beyond the mobile interface. This broadens access to Ollie's assistance, facilitating a more convenient transit experience for all users.

Concept Video with Key Scenarios

Challenge

Why leveraging conversational AI to an every-day experience of riding a bus?

Goal

How might we…

create an intuitive, inclusive, and reliable conversational AI that enhances the public transportation experience

Understand Client

Why Pittsburgh Regional Transit (PRT)?

As the most used local public transportation in Pittsburgh, designing for PRT includes an opportunity space that conversational AI can step in to ease the process and shape a richer user experience. The potential opportunities are listed below:

Prominent Public Transportation

PRT is the most used local public transportation in Pittsburgh, providing 60 million rides a year, and the majority of people that inside and outside the city would use its daily service.

Variety of Users & Multifaceted Requirements

PRT serves a wide array of passengers, each with unique needs, seeking various forms of support from the service. It's essential to provide detailed information that caters to every aspect of the journey.

Complex & Comprehensive Information

There are diverse types of users using PRT and request multiple support from the service. The comprehensive information related to every step during the ride is needed.

Understanding the Brand

We started by deep understanding the brand identity and visual system of PRT. We looked into client's brand identity and core values to align with their vision and goal to serve for the public: providing safe, reliable, and accessible public transportation throughout the community.

PRT Official Website

PRT Field Scenario

Auditing Existing PRT App

Ready2Ride, the mobile app developed by PRT, is designed to bring website information directly to users' smartphones, offering key features such as ticket purchasing, bus schedule checking, and accessibility support. However, the app is still under development and faces challenges with fragmented information, leading many passengers to opt for alternative solutions like the Transit app for their transportation tracking needs.

Secondary Touchpoint Opportunity

During our field research, we identified the bus stop as a significant secondary touchpoint for users. Although PRT initially aimed to install interactive screens, budget constraints have led to the use of posters with QR codes instead. We see this as a strategic opportunity to implement our client's vision.

User Research

Understand and Learn from the Everyday Users

Findings: Identify User's Painpoints from User Research

Through meticulous user research, we delved deeply into the experiences of our users, uncovering their core challenges and needs. By employing a variety of methods, including shadowing observation, interviews, and stakeholder synthesis, we gained valuable insights into the daily interactions passengers have with our services. Some pain points as key digests from interview are shown below:

Bus drivers arrive and depart on their own time. Don’t count on the set schedule...It’s hard to know when is correct to get to the bus stop.

Inefficient Communication

Why is it so difficult to find a place to buy a bus pass? I even don’t know when it was expired and it turned really chaotic when I got on bus to renew it.

Complicated Fare Purchase Process

Late night buses are really terrible. The app says they are coming but didn’t show up at all. It’s ruined my night...

Unreliable Service Reporting

Stakeholder Map

We created a stakeholder map to pinpoint the essential participants within the PRT service ecosystem. This visualization helped us understand the interactions and impacts among these groups, enabling us to assess how the AI assistant could offer advantages to each stakeholder, which we then clearly delineated.

Interview Synthesis

We analyzed user interviews to identify key challenges in current PRT experience. From these insights, we crafted hypotheses on how conversational AI could enhance user experiences, such as improving communication, simplifying fare purchases, ensuring service reliability, and boosting accessibility. These hypotheses will shape our design approach for Ollie.

Modeling: Current User Flow

To validate potential opportunities, we charted the comprehensive journey for both passengers and drivers, identifying prospective users of our digital service. Marked segments within these maps signify areas where a conversational AI agent could intervene to enhance the user experience.

Modeling: Target Users & User Journey

Following our stakeholder mapping and interview synthesis, we pinpointed three primary user groups for the conversational AI: general passengers, passengers needing accessibility support, and bus drivers. We crafted detailed personas for these groups and conducted a thorough analysis of their experiences to unearth potential design opportunities.

By employing user journey maps, we meticulously charted the experiences of these key users, identifying crucial pain points and areas ripe for improvement. This method allowed us to capture their emotional journey and explore how conversational AI could significantly enhance their overall experience.

Ideation

Prioritizing Target Users

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Proposing Design Directions from User Painpoints

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Storyboard Scenarios

To illustrate the diverse experiences of our users, we crafted storyboards that encapsulate the journeys of a daily commuter, a passenger with disabilities, and a bus driver, allowing us to examine the flow and gain insights into how each distinct experience could unfold, and enhancing our understanding and design approach for each group.

Define the Identity of Conversational AI

We explored defining Ollie's identity by considering the traits and tone that best align with the project's objectives and the client's core values. We concluded that the following characteristics would suit Ollie best:

Visualizing Ollie

After establishing Ollie's traits and personality, we iterated on its design, focusing on embodying public transportation attributes and PRT's mission in a singular visual form. This iterative process involved considerable refinement until we settled on Ollie's definitive visual representation.

Ollie's Motion Status

We identified essential statuses for conversational feedback and created motion designs to visualize these states, focusing on smooth transitions and infusing shapes with easy-understanding movements and transformations.

Explore

Developing Visual System

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Prototyping Mobile Interaction

Structure

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Scenario 1. Schedule Tomorrow's Trip

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Scenario 2. Renew Bus Pass

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Scenario 3. Driver Updates to the Passengers

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Scenario 4. Request Accessibility Supports

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Prototyping Mobile Interaction

Structure

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Scenario 5. The Tourist Plans Trip and Cross-platform Experience

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Scenario 6. Notification to Waiting Passengers

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Value Proposition

Structure

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Explore

Developing Visual System

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Prototyping Mobile Interaction

Structure

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Scenario 1. Schedule Tomorrow's Trip

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Scenario 2. Renew Bus Pass

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Scenario 3. Driver Updates to the Passengers

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Scenario 4. Request Accessibility Supports

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Prototyping Mobile Interaction

Structure

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Scenario 5. The Tourist Plans Trip and Cross-platform Experience

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Scenario 6. Notification to Waiting Passengers

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

Value Proposition

Structure

Before detailed design, we identified key user groups to focus our limited resources effectively. This strategic allocation allows us to deeply understand and address the specific needs of these prioritized users, enhancing the overall design impact.

© Yuehui Du 2024