Publications and knowledge transfer

The complete list of publications is available on Google Scholar and ResearchGate.

Selected publications

  • Cao, S., Nandakumar, K., Babu, R., & Thompson, B. (2020). Game play in virtual reality driving simulation involving head-mounted display and comparison to desktop display. Virtual Reality, 24(3), 503-513.
  • Rehman, U., & Cao, S. (2019). Comparative evaluation of augmented reality-based assistance for procedural tasks: A simulated control room study. Behaviour and Information Technology, 39(11), 1225-1245.
  • Deng, C., Cao, S., Wu, C., & Lyu, N. (2019). Modeling driver take-over reaction time and emergency response time using an integrated cognitive architecture. Transportation Research Record, 2673(12), 380-390.
  • Cao, S., Ho, A., & He, J. (2018). Modeling and predicting mobile phone touchscreen transcription typing using an integrated cognitive architecture. International Journal of Human-Computer Interaction, 34(6), 544-556.
  • Rehman, U., & Cao, S. (2017). Augmented reality-based indoor navigation: A comparative analysis of handheld devices vs. Google Glass. IEEE Transactions on Human-Machine Systems, 47(1), 140-151.
  • Cao, S., & Liu, Y. (2015). Modelling workload in cognitive and concurrent tasks with time stress using an integrated cognitive architecture. International Journal of Human Factors Modelling and Simulation, 5(2), 113-135.
  • Cao, S., Qin, Y., Zhao, L., & Shen, M. (2015). Modeling the development of vehicle lateral control skills in a cognitive architecture. Transportation Research Part F: Traffic Psychology and Behaviour, 32, 1-10.
  • He, J., Chaparro, A., Nguyen, B., Burge, R., Crandall, J., Chaparro, B., Ni, R., & Cao, S. (2014). Texting while driving: Is speech-based text entry less risky than handheld text entry? Accident Analysis and Prevention, 72, 287–295.
  • Cao, S., & Liu, Y. (2013). Concurrent processing of vehicle lane keeping and speech comprehension tasks. Accident Analysis and Prevention, 59, 46-54.
  • Cao, S., & Liu, Y. (2013). Queueing network-adaptive control of thought rational (QN-ACTR): An integrated cognitive architecture for modelling complex cognitive and multi-task performance. International Journal of Human Factors Modelling and Simulation, 4(1), 63-86.
  • Rehman, U., Cao, S., & MacGregor, C. (2019). Using an integrated cognitive architecture to model the effect of environmental complexity on drivers’ situation awareness. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 63. 812-816.
  • Eisapour, M., Cao, S., & Boger, J. (2018). Game design for users with constraint: Exergame for older adults with cognitive impairment. The 31st Annual ACM Symposium on User Interface Software and Technology Adjunct Proceedings, 128-130.

PhD theses

Master of Applied Science (MASc) theses

Knowledge transfer

  • Queueing network-adaptive control of thought rational (QN-ACTR), an integrated cognitive architecture for the simulation and modelling of human performance, mental workload, and situation awareness. QN-ACTR can be used to simulate and predict human performance and other human factors constructs in a wide range of domains such as human-computer interaction, driving, and piloting. The method has been adopted as an important research tool by researchers worldwide. This open-source program is available on this GitHub website.
QN-ACTR
QN-ACTR Java
  • The Open Racing Car Simulator (TORCS) human experiment version, an open-source driving simulator adapted for human factors studies. It supports human driving studies with integrated car-following tasks and lane changing task. It also supports QN-ACTR simulation of driver performance, using user datagram protocol (UDP) data connection to link the driving simulator and the human model. It has been used as an education and research tool by teachers and researchers from many universities. Please contact us to request a copy.