Authors:

Adam Cover

Date Created:

Not specified

Course Title:

Professor:

Not specified

About Paper:

As semi-autonomous vehicles become more prevalent on public roadways, it will become increasingly important to develop shared control strategies to ensure that drivers and vehicles collaborate effectively to achieve safe driving operations. One challenge in developing such strategies is accurately characterizing and predicting the behavior and actions of human drivers. Situation Awareness (SA) is a cognitive construct often used to assess the knowledge of human operators in dynamic environments. Recent investigations suggest that some eye-related measures can reflect SA, which may help to infer a person's planned actions. However, there still remains many unknowns regarding which particular eye metrics are best to use to infer SA. Therefore, the goal of this research is to analyze various eye tracking metrics, such as fixation sequence, saccade length, and concentrated gaze regions, to determine their associations with drivers' knowledge and actions. This research leverages data collected from an extensive driving study on obstacle avoidance using a medium-fidelity driving simulator and a remote eye tracking system. Insights from this work can be used to inform the development of control algorithms and adaptive automation to improve joint driver-vehicle interactions.

Source:

Purdue University / 2023

Topics:

No topics listed

Co-authors:

Adam Cover