"Building a better learner driver"
How I solo-designed and develop a product to try and improve learner driver attention rates by 50%
Project Overview
My master’s project explored the critical observation skills of learner drivers using advanced eye-tracking camera technology. This innovative idea delved into the real-time visual, audio and tactile response of novice drivers, providing measurable insights into their attention patterns, hazard detection capabilities, and overall situational awareness.
Understanding
As an open-ended masters project, we could propose a solution to any market we wished. As a close friend was going through their driving lessons at the time and had a lot of opinions on the process, this inspired me to try a new take on the system through product development.
The seed for the process started with questions:
The seed for the process started with questions:
- What is the market most open to improvement?
- What are the primary pain points in the learner driver process?
- Are there non invasive solutions to mitigate one of them?
Research
Qualitative
- Talking to a driving instructor with 10+ years experience gave his opinion on the highest failure points in the test: Safety checks, and car-road positioning.
- Surveying and interviewing student drivers uncovered other worries new drivers faced, such as inexperience in how other drivers react, and how to address unexpected situations not covered in lessons such as breakdowns and nighttime driving.
Quantitative
- RSA statistics showed young and new male drivers had an accident rate 5 to 10 times higher than that of the next highest group.
- 77% of drivers now use GPS navigation regularly, showing a steady trend of information offload to external devices.
Design
By analysing eye movement, observational data, and pre- and post-activity surveys, I aimed to identify common deficiencies and strengths in learners’ observational techniques, ultimately contributing to the development of more effective driver education programs.
I constructed a basic driver simulation rig. My idea was to use an eye-tracking camera to measure mirror responsiveness, introduce separate small sensory reminders (touch, sight and sound), and check if they improved mirror response rates.
This required some programming experience to ensure smooth communication between XML, Python and arduino C++.
I constructed a basic driver simulation rig. My idea was to use an eye-tracking camera to measure mirror responsiveness, introduce separate small sensory reminders (touch, sight and sound), and check if they improved mirror response rates.
This required some programming experience to ensure smooth communication between XML, Python and arduino C++.
Feedback
Overall, the simulation worked passably, but without proper in-car testing, would always feel more like a game with no consequences. The users felt the sensory feedback was simultaneously too intrusive, and then became completely ignored as the brain became able to filter out any noise or vibration deemed “unnecessary”. The users also felt the form factor of the devices were unappealing and bulky, considering the small size of the components used, and the protectiveness users felt when they entered their car as a "safe space".
A suggested solution would be to use a more innocuous device to track body responsiveness in the background before returning the results once a car trip had finished, to encourage more active effort on part of the user, and gather more reliable real-world data.
A suggested solution would be to use a more innocuous device to track body responsiveness in the background before returning the results once a car trip had finished, to encourage more active effort on part of the user, and gather more reliable real-world data.
Next Steps
This research not only enhanced my understanding of product development cycles, but also how to approach surveys and data gathering techniques for quickly building actionable insights for a more effective product.
The user testing sessions proved infinitely enlightening, where many of my own biases became clear once taken out of my hands and given to someone with fresh eyes.
My supervisors gave the project a high grade for working execution, losing points mainly on only having one proper round of development and testing due to time constraints.
I still believe the concept has legs, though, with still-rising wait times on re-tests. This is absolutely a market with potential for growth using a small, self-contained learner driver smart-education product.
The user testing sessions proved infinitely enlightening, where many of my own biases became clear once taken out of my hands and given to someone with fresh eyes.
My supervisors gave the project a high grade for working execution, losing points mainly on only having one proper round of development and testing due to time constraints.
I still believe the concept has legs, though, with still-rising wait times on re-tests. This is absolutely a market with potential for growth using a small, self-contained learner driver smart-education product.
