Safe Path is a mobile app for pedestrians to feel physically safe to travel to their destination by reducing and avoiding street harassment. It focuses on building a safe community for its users to provide recovery support and nearby help to potential encounters.
After conducting multiple user tests with different sets of users for each round, I found that the overall usability of the app improved dramatically. I computed the average task success rate, average time on task, and average recommendation rate.
In Emergency Mode, you can click "Call for Help" button at any point you feel you are in an uncomfortable situation. This will send a signal and notify all nearby Safe Path community members on your help request. Your coordinates and the Safe Path helper will be exchanged and you will be connected through a video call. This gives you the assurance that help is around the corner.
“My circle” consists of people that you want to keep track of their real-time location to ensure their safety and wellbeing.
Reporting an incident helps alert other users of any situation that happens on the streets. It also helps improve the recommendations of safer routes for other users.
Dealing with the aftermath can be challenging. To some people, sharing your experience can be difficult. Safe Path includes a moderated forum for post-trauma support and encouragement. You have the option to remain anonymous.
84 participants, based in Toronto
50% Females, 48% Male, 2% Trans
50% of the participants were between the age of 25-34, 29% between the age of 18-24.
I interviewed 5 women between the age of 20-and 35, focusing on asking neutral and open-ended questions for qualitative responses. A few of the interview questions that were asked:
The survey provided quantitative data on the extent and reach of the problem. Before conducting the survey, it was important to recognize and avoid any biases that can affect the results. Street safety can vary depending on the location that the participant is from, to keep consistency I focused on Toronto. Despite being regarded as one of the safest cities in the world, it was interesting to see that the majority of the female participants and members of the LGBT communities did not feel safe traveling at night. A majority of the participants had experienced some form of street harassment. A surprisingly 24% of those participants experienced life-threatening harassment.
Using the information gained from the research, I was able to create personas that represent the key target segment that I'm designing for.
Now that I had a better mental model of the user's goals and pain points, I looked into currently existing solutions available to the users. An audit of a few direct and indirect competitor’s products provided direction on gaps and opportunities that the Safe Path App can address.
Most safety apps available in the market were focused on sexual harassments. While sexual harassment is a large component of street harassment, it neglected other forms of harassment such as attacks motivated by racism, hate, homophobia, transphobia and etc. In addition, most safety apps had a feature of sending SOS/emergency to trusted friends or families. However, for this feature to be effective; it requires the contacted individual to be available to pick up the SOS request and be nearby to provide help.
Based on my research findings, I knew I had to come up with a convenient solution that provided peace of mind and comfort while traveling. In addition, I wanted to provide additional value in reducing stress or anxiety for those who have experienced an unfortunate encounter.
This diagram depicts an overview of each stage and path that the users can take to accomplish the core of getting home safe.
I drew a storyboard to visualize a scenario of how the Safe Path app could be used by the users.
Amanda is heading home after she finished her last evening class. She is new to the city and she is worried about traveling at night.
She remembers an app named Safe Path, which suggests a safer route for her.
Despite taking a safer route, she still ends up encountering a drunk person.
Amanda notices the drunk person is following her.
Taking precautious, she activates Emergency mode to notify her dad and clicks on the “Call for Help” button.
The app sends the help request to verified community members near her location. A helper, Tom, accepts her request. Tom and Sarah connect through a video call and map coordinate exchange.
Amanda and Tom are within short proximity so they agree to meet. The presence of another individual scare off the drunk individual away.
Now safe, she continues her route and gets home.
She reports the incidents to warn other community members about the incident and location.
Still shaken up by what happened, she goes to the Safe Path forum to share her experience and receive support.
With an idea selected, I started with paper and pencil to quickly draw out the wireframes for the app.
After drafting some paper wireframes, I transferred the initial designs into digital wireframes. These designs focused on creating a personalized safer path to users to travel to their destination.
I conducted 5 sets of usability studies on the low-fi prototype. Testing on the low-fi prototype allowed me to focus on functionality of the design while avoiding any distractions such as color and design elements. The usability studies were conducted remotely and were unmoderated.
I extracted all the data from the usability studies into an affinity diagram to allow me to find common themes and patterns from the participants. Turning these observations into insights allowed to discover some key findings:
I created Safe Path design system to keep consistency in the usage of the company’s branding, colors, typography, grid usage, UI components, and elements.
One crucial lesson I learned was the importance of doing user testing on diverse users with different devices. In my original low-fi prototype, I designed for Iphone X mini and tested it out multiple times. However, upon doing the actual user test, one of the participants had an older android screen and discovered a technical error in the low-fi prototype.
I learned that even though the problem I was trying to solve was a big one, diligently going through each step of the design process and aligning with specific user needs helped me come up with solutions that were both feasible and useful.
