The Impacts of Driver Monitoring Systems on Mitigating Drowsiness Due to Conditional Automation

Driving automation is becoming increasingly available with the advancement in sensors and computational power. The next generation, i.e., conditional automation, allows drivers to engage in other activities like sleeping. If the system cannot operate in certain conditions due to limitations, the driver is required to takeover vehicle control. However, sleepy drivers might not be fit for taking over. Driver monitoring systems (DMS) can use driver physiological and behavioural data (e.g., heart rate, eye-tracking), vehicle kinematics (e.g., lane position), subjective measures, or their combination to detect unsafe driver states. DMS can be used to inform the vehicle and initiate interventions (e.g., warning systems, adaptive interfaces) to alert the driver. There is a vital need to understand how conditional automation can lead to drowsiness and whether and how the vehicle can intervene using a DMS to prepare the driver for a takeover request (TOR).

The objective of this study is to understand how drowsy drivers interact with a TOR in conditionally automated vehicles. The second goal of the study is to evaluate DMS-based drowsiness interventions to prepare the drowsy driver for an upcoming TOR. For this purpose, a driving simulator study will be conducted at the Driver-Vehicle Interaction Lab, Ulm University.

Faculty Supervisor:

Birsen Donmez

Student:

Partner:

Ulm University

Discipline:

Engineering

Sector:

Automotive; Transportation (excluding aerospace)

University:

University of Toronto

Program: