Video Editing Software
Project Inception - Research - Design and Testing
Hyundai - Tesla Mobile App - WayRay/Navion - Bouncie - OnStar - Maven - FordPass
To start the project we looked into how manufacturers and software providers are communicating with the operators of their vehicles. With the development of electric cars, the dashboard has finally, after many years, started evolving. However, many of the platforms we researched were taking new approaches to the same level of communication.
We followed the competitive analysis with generative interviews. Six drivers were interviewed to better understand the real problems associated with operator interactions inside and outside their vehicle.
A summary of our primary findings includes:
- Vehicle owners prioritize problems and their responses to them.
- Vehicle owners want to verify their prioritization of the problem with a more "objective" truth.
- Vehicle owners desire advance notice of the required service as well as potential accident-causing situations.
I then conducted a contextual inquiry with a local repair shop to fully understand the process associated with resolving mechanical issues. Often times, the owner/operator of the vehicle is primary source for troubleshooting information. This causes problems when their misinterpretation of the vehicles communication leads to delays in repair or significant and costly issues with their vehicle.
We then developed prototype Heads Up Display (HUD) graphics in Figma and had them printed on transparencies that we used for multiple rounds of RITE Testing. We conducted iterative interviews on a weekly basis and revised our script and prototypes based on the synthesis of the prior weeks interviews. Interviews consisted of three to four personalized scenarios that would prompt the user to address a potential problem successfully:
- Oil Change Light
- Oil Change Light (Under Stress)
- Recall Warning
- Fuel Light
- Service Light
- Tire Pressure
- Coolant Temperature
Primarily, our participants required strong language and color to correctly determine the severity of their issues. Tires with low tire pressure lights displayed in yellow or orange were interpreted as indicating a non-dangerous issue while red indicated the need to stop and disable the vehicle until the problem was addressed. This is problematic as the majority of vehicles today don't provide escalation and instead focus on more granular data (tire pressure PSI over time for example).
Testing was conducted by placing the interviewee inside of their vehicle, prompting them with the test situation. We then placed transparency mockups on the outside of the windshield to simulate the heads up display. As the situation escalated the transparency could be moved/shifted/switched so as to present a novel experience for the participant. This allowed us to test how the participant responded to specific situations and how their reaction may differ based on the visualization of the issue.
Below is a sample of one of our mockups and our warning prompts: