Pattern Handler: Integrating Real World and Virtual Models of Human Systems Patterns to Regulate the Control Distribution in a Cooperative Automated Driving Task

To reach intuitive control of partially and highly automated machines, a smooth cooperation between both, human and machine, is necessary. A natural way to design cooperation is to use the structures of mental models already established in our minds by human-human or human-animal cooperation. These cooperation designs follow certain patterns to provide solutions in a variety of scenarios. By using interaction patterns, we form and trigger mental models in the human mind, which already uses patterns in a similar way. This paper provides a description of the structure of cooperation patterns. An exemplary pattern for the use case of control transition between a human and a driving automation is modelled based on data of an experiment of human drivers reacting to takeover requests. To use the patterns in human-machine cooperation systems, the novel concept of a pattern handler is introduced. The pattern handler can be instantiated in software and hardware, and matches the human behavior, automation actions, and environment data to cooperation patterns. Within the design phase, it helps with identifying and correcting flaws within the design.

Authors

Institutions

Publication Details

Published
2024-10-06
DOI
https://doi.org/10.1109/smc54092.2024.10831740
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Pattern Handler: Integrating Real World and Virtual Models of Human Systems Patterns to Regulate the Control Distribution in a Cooperative Automated Driving Task

Marcel Usai, Nils Mandischer, Frank Flemisch
Human-Automation Interaction and Safety
article

Pattern Handler: Integrating Real World and Virtual Models of Human Systems Patterns to Regulate the Control Distribution in a Cooperative Automated Driving Task

Marcel Usai, Nils Mandischer, Frank Flemisch
article en

Abstract

To reach intuitive control of partially and highly automated machines, a smooth cooperation between both, human and machine, is necessary. A natural way to design cooperation is to use the structures of mental models already established in our minds by human-human or human-animal cooperation. These cooperation designs follow certain patterns to provide solutions in a variety of scenarios. By using interaction patterns, we form and trigger mental models in the human mind, which already uses patterns in a similar way. This paper provides a description of the structure of cooperation patterns. An exemplary pattern for the use case of control transition between a human and a driving automation is modelled based on data of an experiment of human drivers reacting to takeover requests. To use the patterns in human-machine cooperation systems, the novel concept of a pattern handler is introduced. The pattern handler can be instantiated in software and hardware, and matches the human behavior, automation actions, and environment data to cooperation patterns. Within the design phase, it helps with identifying and correcting flaws within the design.

University of Augsburg (DE), Fraunhofer Institute for Communication, Information Processing and Ergonomics (DE)
Openalex Percentile: Top 66%
Human-Automation Interaction and Safety
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Pattern Handler: Integrating Real World and Virtual Models of Human Systems Patterns to Regulate the Control Distribution in a Cooperative Automated Driving Task — Marcel Usai, Nils Mandischer, et al. · (2024) | TGRS Research Map | TGRS