Overview

DriverSense aims to prevent accidents caused by driver drowsiness through real-time detection and timely interventions, which include alarms, rest stop guidance, and safety alerts. Using advanced optical sensing technology, it monitors eye movements and blink patterns to identify fatigue indicators such as prolonged eye closure, reduced blink rate, and slow eye movements. DriverSense also keeps families connected by providing live updates and encouraging communication with the driver, promoting safer long-distance travel.

This project was completed as a part of the course deliverable for the class SI 612: Pervasive Interaction Design. The goal was to design an innovative product that uses an IoT (Internet of Things) network to interact with its users. This included processes such as scoping the problem, conducting research, designing an interactive physical prototype which works in tandem with the IoT system.

Problem Statement

Drowsy driving is a fatal problem in the United States…

“How might we help truck drivers stay alert and engaged during long-distance trips, promote safer driving and reduce the risk of accidents?”

Cinematic Product Demo

Here’s a product demo of the DriverSense: Drowsy Driver Detection and Intervention System. This video showcases a scenario where a driver repeatedly shows signs of drowsiness and how the DriverSense System intervenes and keeps him alert and safe.

User Research

Diary Studies

To explore factors contributing to drowsy driving among truck drivers, we conducted a week-long diary study where participants documented daily activities, fatigue levels, and consumption habits. Structured entries at the start of the day, during rest stops, and at the day’s end enabled qualitative and quantitative analysis of behaviors and trends over time.

Survey

We conducted a survey to gain self-reported insights on fatigue-prevention strategies among truck drivers. The survey focused on understanding demographics, consumption habits, work routines, sleep quality, causes of fatigue, and attitudes toward autonomous driving features.

The survey revealed self-reported input on effective fatigue-prevention strategies and technology preferences while driving that helped shape our solution.

Research Summary

Combining these two studies allowed us to draw key takeaways about user demographics, behaviors, and attitudes. We used these findings to inform the rest of our design decisions.

Prototyping

User Enactments

For our user enactment study, we leveraged insights from the diary study and survey to identify four key features to address drowsy driving: an alarm system, rest stop suggestions, AI podcast interactions, and emergency phone calls from close contacts. We brainstormed and evaluated potential solutions, merging the most promising concepts into a cohesive experience prototype. This prototype was then tested to assess its effectiveness in mitigating driver fatigue.

Key Findings

Prototype Components

To detect fatigue, we explored open-source optical sensing solutions from Google Labs
With optical sensing as the primary sensor, we also identified other IOT components as necessary outputs: vibration, sound, voice, and Bluetooth.

Behind the scenes

Here’s a system architecture that shows how the IoT components interact with the steering wheel and display.
For this demo, due to time constraints and course requirements, we utilized the **‘Wizard of Oz’** method where one of our team members would trigger the vibrating motors when the user shows signs of drowsiness and initiate the display prompts.

Solution: A 3-Stage Intervention

User Enactments help guide the team in devising a fatigue detection system that intervenes in 3 progressively more intense measures to assist the driver in overcoming fatigue.

Driversense prototype with the My Safety Net-work application being displayed

Stage 1: Audio and Vibration Alert

Alarm sound and steering wheel vibration triggered as first stage measure.
The user has to dismiss the alarm on-screen through slide interaction.
The alarm is triggered twice before the sensor moves on to the next phase (rest stop).

Stage 2: Rest Stop Suggestion

If the driver is still drowsy after the alarm sounds, the system will ask if they would like to take the next rest stop.
The system provides direction to the next rest stop via GPS.
The system provides information on rest stops: Food, bathrooms, etc.

Stage 3: Phone Call Push Notification

If the driver is still drowsy, the system sends a notification to a trusted contact of the driver.
The driver adds a contact on the My Safety Net-work app.
Options to share location to contact or send push notifications when drowsy driving is detected.

Reflections

Diary studies and Surveys are excellent methods to get access to raw data and a glimpse into your users’ habits. We uncovered a bunch of insights about the daily life of a truck driver and based our solution on it.
User Enactments helped in validating our ideas and weeding out unproductive ones. It also made us realize and acknowledge all the variables that the user would need in the given scenarios, which covered things that we probably missed during ideation.
This project unlike most UX projects, required physical prototyping and basic circuitry knowledge. By designating members as leads in various sectors of the project, each member took ownership of leading a certain aspect of the project which improved their confidence and team morale.

My Role

Type

Tools

Timeline