Conceptualization of Human Factors in Automated Driving by Work Domain Analysis SAIC Motor Corporation Limited

Format:

Book

Conference/Event

Author/Creator:

Zhang, You, author.

Conference Name:

WCX SAE World Congress Experience (2020-04-21 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2020

Summary:

The increasing automation of driving functionalities is one of the most important trends in the automotive industry. The trend is moving towards systems which allow the driver to be absent from the active driving task. During the process, on one hand, the human driver more and more relies upon the driving automation to perform the dynamic driving tasks. Therefore the driver needs to trust the driving automation. On the other hand, even the high driving automation (e.g SAE Level 4) can only performs its functionality within the specific operational design domain and the driving automation relies upon the human driver to handle events when the vehicle operates outside the domain. What's more, for the lower level driving automation, the driver still needs to assume some fallback responsibility, and may be required to react promptly when the driving automation even inside the operational design domain is inadequate to operate the vehicle. From above, it is obvious that the interactions between human driver and driving automation are becoming complicated and less transparent. Hazardous events may occur due to the human factors in these interactions. However human beings are subject to the context in which they are working and their behaviors are not random. Thus to identify these factors in the early design phase may be a challenge. This contribution proposes to use Work Domain Analysis as formative approach to analyze the human factors in automated driving. As an overarching analytic framework for human behavior constraints, Work Domain Analysis can identify potential problems in driver automation interactions in a proactive manner and thus can benefit the system design of driving automation

Notes:

Vendor supplied data

Publisher Number:

2020-01-1202

Access Restriction:

Restricted for use by site license