Using Thermal Imaging and Other Modalities to Detect Drivers Alertness

Project Description

According to a survey run by the National Sleep Foundation (2005), 60% of US adult drivers said they drove while being fatigued, and as many as 37% admitted to have fallen asleep at the wheel. Moreover, distracted driving caused by engaging in a different activity can cause fatal accidents. The U.S. Department of Transportation estimated a total number of 421,000 injuries in vehicles crashes due to distracted driving.

The goal of this project is to construct holistic models of drivers, covering a multitude of channels in the physical world, including vision, physiology, thermal, and language, as well as background information (demographic and psychological) and affective information of the drivers. We will use these holistic representations to build effective personalized multimodal models of driver alertness, specifically aiming to identify patterns associated with two main driving states: alertness (alert vs. drowsy) and attention (attentive vs. distracted). Previous research has focused on the detection of either alertness or distraction, but not their joint co-existence. Yet, we expect that distractors would have a different impact on a driver in a drowsy (tired) state than on an alert driver, and therefore our goal is to build joint models that take into account this interdependency.

Note: This project is a UM Flint –UM Ann Arbor collaboration and is IRB-approved. Project is partially funded by Toyota Research Institute.

Work Schedule

This is a 2-year (2019-2020) project in collaboration with Toyota Research Institute. Schedule for 2019-2020 academic year is September 1, 2019 – May 1, 2020.

GSRA is expected to participate in a weekly research meeting. Most of the work is done in a laboratory in the UM Flint campus with the work schedule being largely flexible. There will also be a couple of check-in meetings in the Ann Arbor campus that the student is expected to attend (travel together with the faculty advisor).

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Job ID: 169720
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Job Detail
Job Opening ID
Fall 2019 and Winter 2020
Work could be done by someone not coming to campus (e.g., online or non-local student)
What majors can apply?
  • Mechanical Engineering (MSE)
Faculty Sponsor
Faculty Name
Mihai Burzo
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