An Autonomous Moped Experience
I explored semi-autonomous mobility through a moped experience focused on improving safety and rider interaction.
A semi-autonomous moped designed to reduce accidents on the road and make mobility more accessible for riders with cognitive and physical disabilities. For our Interaction Design course, we explored how new controls and interaction paradigms could make the moped intuitive, safe, and inclusive.
My Role
I explored ways to make mopeds more accessible and user-friendly for diverse riders. I conducted research on rider needs, created wireframes and prototypes for key interactions, and tested designs with potential users. Insights informed an accessible, intuitive navigation and control system, ensuring the product was usable for everyone.
IMPACT HIGHLIGHTS
Improved road safety
Integrates semi-autonomous technology to assists riders in avoiding hazards and making safer driving decisions.
Accessibility
Accessible to everyone by including capabilities that accommodate individuals with cognitive and physical disabilities.
Enjoyable Experience
A moped that’s not only safe and accessible but also enjoyable to ride, creating a stress-free commute.
Product Designer
2 UX Researchers
2 Product Designers
Visual Design
Interaction Design
Prototyping
6 weeks (October to November 2023)
The Problem
To understand the problem space and the potential pain points that already existed surrounding mopeds, we conducted a guerrilla research session through user interviews and user feedback.
Through this process, we identified key issues with mopeds that informed our design decisions. These were the main pain points we learned:
Inconsistent road regulations
Road regulations vary significantly across states and countries. This inconsistency can confuse users and create barriers, making mopeds less accessible for riders from diverse regions.
Limited suitability for all roads
While mopeds perform well on shorter trips and simpler routes, they are not the preferred choice for longer distances or more complex journeys. Their design and capabilities often restrict their versatility with certain road types.
Learning curve for new drivers
Driving a moped can feel intimidating to new users. However with time and practice, riders can become more comfortable navigating them.
Information overload on small digital interfaces
Small digital interfaces on mopeds limits the amount of visible information. However, these interfaces must still provide essential details like current speed, battery levels, and navigation to ensure driver safety.Ideation
Vision Boards and Sketches
Low Fidelity Paper Prototypes
Usability Testing
We tested our low-fidelity and physical prototype with 10 individuals of varying moped knowledge and skill levels, using the same user group with whom we conducted initial user research. Test participants were instructed to drive the vehicle, and given a scenario to lead them to their next destination. As we conducted the user test, we asked participants to make sense of what they were seeing and what they might expect to do next.
Key Insights from Usability Testing
During user testing, we identified areas where the experience could be improved, alongside positive feedback that highlighted what worked well.
Confusing Information Architecture
Users had difficulty navigating the moped interface and understanding the hierarchy of information.Unclear Visual Hierarchy
Important elements didn’t stand out, causing hesitation and errors.Uncertain Interactivity
Users struggled to identify which elements were interactive and how to engage with them.Solution
Introducing the AI Cover Letter Generator
The AI Cover Letter Generator analyzes a healthcare job seeker’s previous experiences and extract relevant skills and qualifications to generate tailored content that aligns with the job seeker's resume and the specific job posting.
Scope of Project:
Scope of Project:
- Streamline the cover letter writing process
- Save time for busy HCPs
- Help users stand out during their job search
- Strengthen Health eCareers’ market competitiveness and value by integrating AI-driven tools into the job search experience
Design Explorations
What problems does the generator solve?
Collaboration over automation
Enter job specific details to tailor the cover letter for a particular job posting. The generator incorporates AI to analyze job descriptions and suggest tailored content for users to refine, making a more collaborative experience collaborative rather than a fully automated one.
Customization
Users can customize the cover letter's length, tone of voice, and writing style to better reflect their personality, making each letter feel natural.
Personalization
The generator also incorporates information from the user’s resume into the cover letter. The system automatically extracts details such as relevant work experience, education, and skills to create more personalized and unique cover letters.
User Testing
Participants were initially hesitant but open to using AI to generate and evaluate cover letters.
I collaborated with the UX Lead to conduct an unmoderated user test on my high-fidelity prototype with 10 participants who were Physician Assistants, Registered Nurses, Obstetrician, and Nurse Practitioners, with up to 20 years of experience.
What I intended to discover:
Insight: Most participants have experimented with AI tools, often out of curiosity, but lacked real confidence in using them effectively. Despite this, they expressed very strong interest in using AI generators in the future.
Insight: Participants like the ability to customize cover letter because they can adjust tone and style to reflect personality and with different employers.
Insight: While participants praised their generated letters, they wanted more flexibility to compare multiple versions with different tones of voice.
Usability Testing Result
Usability testing showed us that HCPs found the generator useful in reducing time and effort spent on job applications, while also uncovering key usability issues
Data from the 1st round of usability testing informed design iteration #2, which addressed user needs identified in round one: enabling HCPs to regenerate new versions of their cover letter faster.
Post Project Reflections
I strengthened UX research skills through facilitating and interpreting user test results.
- Conducted unmoderated usability tests and analyzed participant interviews on UserTesting.com.
- Synthesized findings to support design changes and recommendations for stakeholders.
I leveraged design systems and designed responsively.
- Designed and optimized mobile versions of the AI Cover Letter Generator, ensuring usability across different screen sizes.
- Adjusted layout and visual hierarchy to make interactions clear and intuitive on smaller devices.
I improved communication by presenting my design process.
- Refined ability to articulate design rationale and advocate for user needs within a cross-functional team.
- Presented project progress at a company-wide UX working group meeting, which was created to bring UX teams together across the various subsidiaries at Everyday Health Group.
Try the generator today!