Authors:

Bao Quoc Phan

Date Created:

Not specified

Course Title:

Professor:

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About Paper:

Worldwide, automotive companies are investing in the development of automated and autonomous vehicle technologies. While most research has been devoted to developing self-driving technology itself, there has been far less research on the interactions between human drivers and self-driving agents. Ultimately, we aim to improve such human-machine interaction by modeling and analyzing the driver's trust, self-confidence, mental workload, and perceived risk (which are the cognitive states that have been known to affect human- machine interactions). However, modeling the driver's cognitive states in real life scenarios can be expensive, dangerous, and complicated. Instead, Unreal Engine (UE) 5.1 is used as a platform for developing a dedicated SAE Level II driving simulator as a research testbed. Given the interest in human cognition during interactions with the autonomous vehicle, the simulator must not only include realistic driving scenarios, but additional sensing modalities, including psychophysiological and self-report data collection, must be integrated with the UE5 environment. In this research effort, an approach for integration and coordination of multiple sensing platforms with the UE5 environment is proposed and demonstrated. Python and UE5's UDP (User Datagram Protocol) message plugin are used to design a communication system between the simulator and iMotions, a software that integrates and synchronizes psychophysiological and behavioral sensors. The proposed system facilitates data post processing and analysis by enabling the simulator to send real time event markers to iMotions.

Source:

Purdue University / 2023

Topics:

No topics listed

Co-authors:

Bao Quoc Phan