【Title】Recent Progress in Human performance Modeling using an Integrated Queueing Network Cognitive Architecture

【Speaker】Shi Cao, PhD, Assistant Professor, University of Waterloo

【Host】 Dr.Xiaolei Xie

【Date】Thursday March 19, 2015  14:00-15:00

【Venue】Room 510, Shunde Building

【Abstract】Human factors is an important research area in industrial engineering. Industrial designers need to evaluate operators/users‘ performance and workload while interacting with a system and compare different design options to determine the optimal design choice. Traditionally, such evaluation and tests mainly rely on empirical human studies, which add a heavy cost to the design process. In addition, it is difficult to conduct comprehensive user tests at early design stages when no physical interfaces have been implemented. To address these issues, I develop computational human performance modeling techniques that can simulate human-computer interaction (currently focusing on cognitive aspects). In this talk, I will introduce the recent progress on an integrated cognitive architecture that has the capability to model human performance and mental workload in complex cognitive multi-task scenarios. This QN-ACTR architecture integrates two previously isolated but complementary cognitive architectures – Queueing Network (QN) and Adaptive Control of Thought-Rational (ACT-R). It uses a general cognitive architecture to computationally represent human cognitive capabilities and constraints. Task-specific models can be built with the specifications of user knowledge, user strategies, and user group differences. The simulation results include performance measures such as task completion time and error rate as well as mental workload measures. Completed studies have modeled multitasking scenarios in a wide range of domains, including transportation, healthcare, and human-computer interaction. Software tools have been designed to simplify the model building process. I have also designed the connection protocol between QN-ACTR and an open-source driving simulation program so that models can drive simulated vehicles as a way to simulate and evaluate human driving performance. Implications and future research will be discussed.

【Bio】Shi Cao (曹石) is an Assistant Professor in the Department of Systems Design Engineering at University of Waterloo. He received his PhD in Industrial and Operations Engineering from University of Michigan, Ann Arbor in 2013. Dr. Cao studies human factors using both experiment and computational simulation methods. His current research focuses on modeling human performance and mental workload in complex human-machine interactions and developing cognitive engineering tools for quantitative human factors analyses.

https://uwaterloo.ca/systems-design-engineering/people-profiles/shi-cao-0 

https://www.linkedin.com/in/shicao 

http://scholar.google.com/citations?user=fQ1R4MEAAAAJ