United States Department of Transportation
i
Predicting Driver Takeover Performance in Conditional Automation (Level 3) Through Physiological Sensing [supporting dataset]
-
2024-01-03
-
-
[JSON-4.26 KB]
Details:
-
Creators:
-
Corporate Creators:
-
Corporate Contributors:
-
Subject/TRT Terms:
-
Publication/ Report Number:
-
DOI:
-
Resource Type:
-
Geographical Coverage:
-
Corporate Publisher:
-
Abstract:The National Highway Traffic Safety Administration (NHTSA) calls for fundamental research on “the driver performance profile over time in sustained and short-cycle automation … and driver-vehicle interface to allow safe operation and transition between automated and nonautomated vehicle operation.” The emerging level 3 autonomous vehicle (AV) has the potential to transform driving because it can perform all aspects of the driving task and allow for complete disengagement of drivers (e.g., sit back and relax) under certain driving scenarios. The vehicle can handle situations that require an immediate response, such as emergency braking. However, this is not fully autonomous, and still requires the driver to be prepared for takeover at all times with a few seconds of warning. Being able to measure and predict the takeover performance (TOP) ahead of time and issue adequate warnings is thus critical to ensure driver comfort, trust, and safety in the system and ultimately acceptance of the technology by different stakeholders. This has not been explored to the extent of establishing complete and irrefutable trust in the autonomous vehicle system and its ability to engage the driver in safe and effective takeover under certain driving scenarios. Therefore, the objective of this project is to perform fundamental research to understand drivers’ capabilities of taking over the vehicle safely and promptly at any time in level 3 automation. This project advances fundamental research in human factors in level 3 AVs. This is achieved through an integrated treatment of the drivers’ TOP measured and predicted through physiological features and driving environment data in level 3 AVs. Thus, the main objective of this research will be to investigate the feasibility of using multimodal physiological features collected from drivers in level 3 AVs under different driving and disengagement scenarios (secondary tasks) to develop a personalized and real-time prediction of TOP. The project will engage a diverse group of students and faculty and develop a research program in an unexplored area of level 3 AVs, leading to substantial advances in how human physiological sensing can be used to understand the driver’s TOP, especially in a personalized manner. Such an understanding can eventually lead to the design of adaptive and personalized alerts that can be integrated in level 3 AVs.
The total size of the zip file is 1.39 GB. The .txt file type is a common text file, which can be opened with a basic text editor. The most common software used to open .txt files are Microsoft Windows Notepad, Sublime Text, Atom, and TextEdit (for more information on .txt files and software, please visit https://www.file-extensions.org/txt-file-extension). The .docx file is a Microsoft Word file, which can be opened with Word and other free word processor programs, such as Kingsoft Writer, OpenOffice Writer, Apache OpenOffice, and ONLYOFFICE. The .csv, Comma Separated Value, file is a simple format that is designed for a database table and supported by many applications. The .csv file is often used for moving tabular data between two different computer programs, due to its open format. The most common software used to open .csv files are Microsoft Excel and RecordEditor, (for more information on .csv files and software, please visit https://www.file-extensions.org/csv-file-extension). File extension .json is associated to JavaScript Object Notation file format, a lightweight, text-based, language-independent data interchange format. JSON defines a small set of formatting rules for the portable representation of structured data. It is used by various applications as alternative option to XML file format. The data in a json file are stored in simple text file format and the content is viewable in any simple text editor (for more information on .json files and software, please visit https://www.file-extensions.org/json-file-extension).
-
Content Notes:National Transportation Library (NTL) Curation Note: As this dataset is preserved in a repository outside U.S. DOT control, as allowed by the U.S. DOT’s Public Access Plan (https://doi.org/10.21949/1503647) Section 7.4.2 Data, the NTL staff has performed NO additional curation actions on this dataset. The current level of dataset documentation is the responsibility of the dataset creator. NTL staff last accessed this dataset at its repository URL on 2024-01-16. If, in the future, you have trouble accessing this dataset at the host repository, please email NTLDataCurator@dot.gov describing your problem. NTL staff will do its best to assist you at that time.
-
Format:
-
Funding:
-
Collection(s):
-
Main Document Checksum:
-
Download URL:
-
File Type:
