Eyes on the Road: Detecting Phone Usage by Drivers Using On-Device Cameras
Using a phone while driving is distracting and dangerous. It increases the accident chances by 400%. Several techniques have been proposed in the past to detect driver distraction due to phone usage. However, such techniques usually require instrumenting the user or the car with custom hardware. While detecting phone usage in the car can be done by using the phone's GPS, it is harder to identify whether the phone is used by the driver or one of the passengers. In this paper, we present a lightweight, software-only solution that uses the phone's camera to observe the car's interior geometry to distinguish phone position and orientation. We then use this information to distinguish between driver and passenger phone use. We collected data in 16 different cars with 33 different users and achieved an overall accuracy of 94% when the phone is held in hand and 92.2% when the phone is docked (?1 sec. delay). With just a software upgrade, this work can enable smartphones to proactively adapt to the user's context in the car and and substantially reduce distracted driving incidents.
Research Questions / Practical Problems
Question signals indexed for this paper.
- 75%
Long-Term Evolution of Driver Visual Attention during Automated Driving in Real-Traffic: Investigating the Influence of Mental Model and Dynamic Learned Trust
AutoUI '25· Automated Driving Interface & Takeover Design +1
- 60%
Acceptability and Acceptance of Autonomous Mobility on Demand: the Impact of an Immersive Experience
CHI '18· Automated Driving Interface & Takeover Design +1
- 60%
Trust and Visual Focus in Automated Vehicles: A Comparative Study of Beginner and Experienced Drivers
CHI '25· Automated Driving Interface & Takeover Design +1
- 60%
P4 - Where Autonomous Buses Might and Might Not Bridge the Gaps in the 4 A’s of Public Transport Passenger Needs – a Review
AutoUI '18· Automated Driving Interface & Takeover Design +1
- 60%
What Makes a Good Team? - Towards the Assessment of Driver-Vehicle Cooperation.
AutoUI '21· Automated Driving Interface & Takeover Design +1
- 60%
Development of a Perceived Security Scale for Shared Automated Vehicles (PSSAVS) and its Validation in Colombia and Germany
AutoUI '23· Automated Driving Interface & Takeover Design +1
- 60%
I've Got the Power: Exploring the Impact of Cooperative Systems on Driver-initiated Takeovers and Trust in Automated Vehicles in Conflicting Situations
AutoUI '23· Automated Driving Interface & Takeover Design +1
- 60%
Text a Bit Longer or Drive Now? Resuming Driving after Texting in Conditionally Automated Cars
AutoUI '24· Automated Driving Interface & Takeover Design
Based on Jaccard similarity of research subtopics & professions (≥60%)