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Secondary Research
Walkability in U.S. Cities
Our secondary research underscores the urgent need for primary research to further explore pedestrian safety in U.S. cities and we are eager to hear everyone's personal stories.
Primary Research
Quantitative Survey
Primary Research
Qualitative Interviews
So how might we enable individuals who commute using non-personal motor vehicles to better make informed decisions, thus enabling them to feel safe and confident through every point of their commute?
Our Solution
A GPS navigation app that provides pedestrians with turn-by-turn directions, real-time crime data map, and user-submitted reports on road conditions, accidents, and hazards. Amble utilizes these crowd-sourced data to help pedestrians find efficient routes while avoiding potential hazards.
Design Highlights

Highlight 1:

Toggle on types of the hazard users want to aviod

Highlight 2:

Report potential hazards to inform other users

Competitor Analysis

Next, we conducted an in-depth competitor analysis to evaluate how other navigation/safety services ensure safe experiences for commuters.

After Competitor Analysis, we realized that observation of individual users was imperative for our own product development.

Personas and Storyboards

Meet Alex and Michelle, embodying the dual essence of our app in urban and suburban settings respectively. Alex navigates through New York City's bustling streets, relying on the app for safe, efficient routes. Meanwhile, Michelle, an active suburban community member, enhances neighborhood safety by reporting hazards through the app.

The following storyboards, based on our personas, explore situations including non-direct routes that avoid undesirable obstacles (Alex, p1), sharable reports that alert other app users (Michelle, p2), and the idea of changing routes in real-time when a new crowdsourced report is received (bystander, p3).

Key Features and User Flow

After identifying needs through various scenario evaluations, we initiated the development of the app's user flow. Below is an overview of key features and user flow, encompassing features:

Log in, History Activity Page, Community (potentially incorporating gamification), Settings, Report, and High-Freedom Navigation, which empowers users to either disregard hazard alerts from others or opt for recommended routes to aviod hazards.

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Paper Prototype
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First Wireframing

Let's revisit the problem statement: How might we enable individuals who commute using non-personal motor vehicles, particularly in last-mile situations, to better make informed decisions, thus enabling them to feel safe and confident through every point of their commute?

We designed the following wireframes (part of) which helped us refine the features of the app and identify any changes that needed to be made.

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Initial Usability Heuristic Test

From our wireframe, we carried out our initial heuristic evaluation with 6 participants. Three out of ten heuristics fell below our desired standards. We proposed the following solutions:

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UI Kit
Gamification

How can we boost user stickiness while promoting referrals? By adding engaging gamification elements, we can enhance user enjoyment and motivation, encouraging continued use and sharing.

To incentivize hazard reporting, we've established a point system. Not only can users accumulate points by walking but also by reporting hazards and validating others' reports. These points can be redeemed for in-app virtual items or carpool gift cards.

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Usability Test & Iteration

We are almost there!

To avoid developer bias, we need more participants to test our hi-fi prototype. We assigned each participant five tasks to test the major functionality of Amble. After conducting 8 usability tests, we noticed 4 significant problems.

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Final Product & Flow

Final flow
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Next Steps

Originally designed as a walking navigation tool for commuters, Amble has expanded to serve a diverse user base like runners and dog walkers, ultimately aiming to improve the experience for wheelchair users.

While there might be occasional drawbacks from user-program interactions, most can be addressed using specific algorithms and mechanisms.

1.  Avoid Reporting Abuse

Amble uses a report function for user-generated data, but this can lead to system abuse with false hazard reports for trolling or points. To counter this, we'll introduce vetting processes, a peer review system for report confirmation, and restrict reporting to a defined range.


2. Avoid Attention Distraction

We want our users to concentrate on their journey, not our app. By blending voice and vibration feedback for navigation and allowing hazard reports upon arrival, we could reduce phone distractions, promoting awareness of users' environment.

3. Public Data Archive and Foster Pedestrian Community

We would like Amble to develop a database that allows the community to easily access information like infrastructure and crime data. Our ultimate goal is to promote a pedestrian-friendly community.

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