| Methods |
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|---|---|---|---|---|---|---|---|---|---|
| Completed at | CMU | ||||||||
| Group | Chin Wei Wong, Nissa Nishiyama | ||||||||
| Final deliverable | App concept |
CMU provides a late-night escort shuttle service for students to ensure they get home safely. In a 30-minute shift, the driver takes up to 20 students home. Because the driver makes point-to-point stops like a taxi, he has to remember the stops and figure out an optimal route for efficiency.
Goals
- Identify human factors issues the drivers face
- Produce a redesign of an element of the current system
Challenges
- Realistically, a solution that is too costly to produce will not be considered
Research
First, we performed literature review to pinpoint factors that affects a bus driver’s performance. As it is not safe to overload the driver with questions while on the job, we quietly observed two drivers during their shifts. Asked passengers to fill out questionnaires about their past experience with the escort services. Followed up with a retrospective think aloud and interview session with each driver.
Synthesis & ideation
Analyzed driver’s behavior to identify breakdowns and decisions. Identified key features that needs to be addressed.
Final concept
We found the biggest challenge for drivers was remembering all the stops. Over the years, the drivers developed a cheat sheet that served as a memory aid. However this cheat sheet is not well-designed and caused problems. We opted to redesign this memory aid into a tablet application.
Our application reduces cognitive load by calculating the optimal route and tracking stops made. It also maximizes the driver’s time on the road by being legible, minimal and illuminated.
