@inproceedings{1c9677e278cb449bacee1c85871ad9a8,
title = "A study of how drivers' subjective workload and driving performance change under varying levels of automation and critical situations",
abstract = "Mixed control by driver and automated system is going to be implemented for decades until fully automated driving is achieved. Thus, the driver has to re-control the vehicle accurately and in a timely manner when an automated system sends a take-over request (TOR) at its limitation. Workload is the actual capacity required for a person to complete a specified task. While in driving task, excessively low and high workloads result in an insufficient capacity of drivers. Hence, a driving simulator experiment was performed in three levels of automated driving conditions, with 31 participants involved. The results showed that compared to manual driving conditions, a driver's subjective workload was significantly reduced in both partial and highly automated driving conditions. The results support the application of an automated driving system, as it reduces driving workload. The results also supported that participants reflected higher workload when encountering more critical situations, especially under higher levels of automation.",
keywords = "Driving performance, Driving workload, Levels of automation, Simulated driving",
author = "Junda Zhai and Guangquan Lu",
note = "Publisher Copyright: {\textcopyright} ASCE.; 19th COTA International Conference of Transportation Professionals: Transportation in China - Connecting the World, CICTP 2019 ; Conference date: 06-07-2019 Through 08-07-2019",
year = "2019",
doi = "10.1061/9780784482292.033",
language = "英语",
series = "CICTP 2019: Transportation in China - Connecting the World - Proceedings of the 19th COTA International Conference of Transportation Professionals",
publisher = "American Society of Civil Engineers (ASCE)",
pages = "344--355",
editor = "Lei Zhang and Jianming Ma and Pan Liu and Guangjun Zhang",
booktitle = "CICTP 2019",
address = "美国",
}