Human-cyber physical systems (CPS) are systems in which the functions of intelligent machines and human operators are well integrated. Such systems have become increasingly pervasive, from intelligent manufacturing systems to smart homes to automobiles. The existing intelligent technologies aim at reducing human workload and increasing system safety, yet they also bring new safety concerns. These concerns are particularly essential in emergency situations, in which the human operator may be required to make decisions under time pressure and high-level stress. The decisions made in these situations are often the most important ones that can cause severe safety issues. This CRII project investigates influential factors for human-CPS system safety in emergency situations, using the semi-autonomous driving system as a concrete domain. The project outcome will improve our understanding of the safety-critical factors for semi-autonomous driving, inform the future design of other human-CPS systems, and ultimately lead to a more efficient and safe world.

Specifically, the inclusion of human drivers in the semi-autonomous systems makes the control tasks of the system more difficult because the controller must allow for unanticipated input from the human driver. Most existing work on the safety of such systems assumes a priori models that are expected to fully characterize human behaviors. However, such assumptions may become invalid when the human operator has to make a decision in emergency situations, such as car crashes or malfunctions. The goal of this project is to investigate systematically how the human-CPS system as a whole reacts to such situations and examine influential factors of the human driver, the vehicle sub-system, and the interaction. The proposed assessment measures of system safety in emergency situations include human performance in response to unexpected hazardous events, and human decision making during vehicle malfunctions caused by cyber attacks.

Agency
National Science Foundation (NSF)
Institute
Division of Information and Intelligent Systems (IIS)
Application #
1760347
Program Officer
William Bainbridge
Project Start
Project End
Budget Start
2017-08-25
Budget End
2019-07-31
Support Year
Fiscal Year
2017
Total Cost
$97,786
Indirect Cost
Name
Old Dominion University Research Foundation
Department
Type
DUNS #
City
Norfolk
State
VA
Country
United States
Zip Code
23508