Case Study

bikeSense

A street smart sign that alerts passing car drivers of nearby cyclists and improves city planning

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Context

At a Glance

Bikesense grew out of an ubiquitous computing assignment from CMU's Interaction Design Studio course. Our prompt called for an intelligent system that improves public safety that would meet the needs of target users at a specific location. We arrived at our final concept through contextual research, iterative research and prototyping.

Our final deliverable was a video which showed the challenges inherent with current static signs in the city and how dynamic signs could not only help drivers and cyclists but also the city as a whole. In this team project, I performed research throughout and helped facilitate the group design process of the final sign.

Research

In Search of Problems

How do bike accidents happen? Who's at fault? How can we improve cyclist safety?

To improve cyclist safety we took conducted site observations, interviews and secondary research. From observations, we noticed that bike rental stations didn't provide helmets. Poor weather conditions such as rain and steep inclines found in Pittsburgh posed problems. Cyclists told us that they felt guilty for riding on the sidewalk but saw no good alternative due to heavy traffic and poor road conditions.

Site Observations

We looked at three different bike rental locations in Pittsburgh. We noticed some cyclists ran red lights and rode on sidewalks.

Interviews

Occasional cyclists perceived biking as a convenient (albeit dangerous) mode of transportation.

Secondary Research

From the City of Pittsburgh data we learned that cyclists were found at fault for half the accidents. Most accidents occurred due to car drivers not noticing the cyclists.

Concept Testing

Solving the Wrong Problem

Cyclists blamed drivers. Drivers blamed cyclists.

We storyboarded and speeddated multiple concepts with drivers and cyclists around safety. However, the reactions to them were lukewarm. Cyclists thought drivers were careless. Drivers said cyclists ignored the rules of the road. In the end, both had strong reactions, saying that the other party should take action, not them.

Bodystorming Ideas

We used a method called bodystorming to generate 66 ideas in 9 categories as a starting point for storyboards.

Speeddating the Storyboards

We speeddated multiple storyboards around cyclist and driver safety. We conducted these in person and through online surveys.

To address these issues we shifted our approach towards building a smart sign that would notify drivers of nearby cyclists. Additionally, the city of Pittsburgh could benefit from this concept by capturing the data collected from the smart sign to further improve its bike infrastructure.

Iterative Design

Creating the Perfect Sign

We got out of the building, prototyped on the streets and iterated on the sign striking the right balance of info for drivers.

Onsite Testing

Through street observations we shifted our focus from a hanging sign to one that's stationary.

Balance of Information

We iterated on several design concepts that would communicate the right amount of information to drivers without overwhelming them.

Paper Prototypes

We went through multiple paper prototypes to approximate a physical prototype and inform our thinking.

How It Works

In our final version of the sign we incorporated two interactive elements. As soon as a bike would pass, a red triangle would emerge at the top of the sign indicating that a cyclist is nearby. Over time, this indicator would get lowered until it disappeared. Secondly, the amount of info on the sign itself would change from a verbose mode about the law to a general statement about sharing the road.

Presentation

Final Deliverable

For our final deliverable, we created a concept video showing the benefits of a smart sign to cyclists, drivers and the city of Pittsburgh.

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