LAUNCHED

Vehicle Autonomy and Intelligence Lab

Vehicle Autonomy and Intelligence Lab

Helping engineers make better decision with AI data from Self-Driving Racing Car

Helping engineers make better decision with AI data from Self-Driving Racing Car

MY ROLE
MY ROLE

As the Lead UI/UX Designer, I designed every part of the dashboard except the maps. I also guided a team of seven designers in conducting eight in-depth user interviews.

As the Lead UI/UX Designer, I designed every part of the dashboard except the maps. I also guided a team of seven designers in conducting eight in-depth user interviews.

TEAM
TEAM

1 UX/UI Designer, 2 Developers, 10 Engineers,
1 Product Manager

1 UX/UI Designer, 2 Developers, 10 Engineers,
1 Product Manager

IMPACT
IMPACT

Reduced interpretation time from 3.8s to 1.2 s through 6 iterations, and showcased it at the 2024 Indy Autonomous Challenge, where it was featured by CNBC.

Reduced interpretation time from 3.8s to 1.2 s through 6 iterations, and showcased it at the 2024 Indy Autonomous Challenge, where it was featured by CNBC.

TIMEFRAME
TIMEFRAME

Oct 2023 - Sep 2024

Oct 2023 - Sep 2024

Summary

Summary

The first internal dashboard that intuitively visualized complex AI data for autonomous race cars

The first internal dashboard that intuitively visualized complex AI data for autonomous race cars

3.16x

3.16x

faster data comprehension

faster data comprehension

CNBC

CNBC

featured by CNBC

featured by CNBC

Process

Context

For one of the world’s first autonomous races

No driver onboard—engineers monitored AI data in real time.

An internal tool designed for AI engineers

Tailored to the specific needs of internal engineers.

User Research

In-depth Interview

To understand the meaning, priority, and context of the data.

Comparable Analysis

Researched platforms used by engineers to view data.

Heuristic Evaluation

To evaluate the effectiveness of the design.

Problem Analysis

Text-heavy data slowed interpretation

Engineers new to the tool struggled to understand data

Data

3.6 secs

3.6 secs

To locate the needed data.

Reference

1 st

No existing design precedent.

Worst Case Scenario

Delayed responses could lead to a car crash

Goal

Simplify complex AI data to help engineers quickly understand and feel assured

Iteration Summary

Received Feedback on Initial Versions

" It looks fancy but messy "

" I can't immediately understand data from graphs "

Iterations

Simplified the visualization of complicated data types

Grouped data based on what each engineering team frequently monitors, so they can focus only on the relevant sections of the dashboard

Before

After

Final Design

Intuitive dashboard showing AI data effectively

Style Guideline

To support development, I documented variables, data values, and style guides.

User Testing

User evaluation for feedback

Accessibility check under direct sunlight

Impact

Reduced time for new engineers to locate and understand AI data

3.8 secs

3.8 secs

→➔➜

1.2 secs

1.2 secs

Successfully handed off to developers

Showcased in the Indy Autonomous Challenge 2024, broadcasted on CNBC

Takeaway

Takeaway

Building an internal tool requires a proactive attitude and friendly relationships with engineers

Building an internal tool requires a proactive attitude and friendly relationships with engineers

Empathy is essential when creating unprecedented AI products

Empathy is essential when creating unprecedented AI products

Got a UX dilemma, or just want to geek out about design? Let’s chat—I promise I’m more fun than a 404 page!

Got a UX dilemma, or just want to geek out about design? Let’s chat—I promise I’m more fun than a 404 page!