Publications

Predicting Locomotive Crew Performance in Rail Operations with Human and Automation Assistance

Published in IEEE Transactions on Human-Machine Systems, 2019

As new technologies are introduced into rail operations, models are needed to represent the task load of operators to identify periods of extreme workload that could be mitigated through technological interventions. To this end, a computational model is described to quantitatively simulate freight rail operator workload to understand the impacts of inserting intelligent automation on different crew configurations. Read more

Recommended citation: Nneji, V. C., Cummings, M. L., & Stimpson, A. (2019). Predicting Locomotive Crew Performance in Rail Operations with Human and Automation Assistance. In IEEE Transactions on Human-Machine Systems. http://victorianneji.github.io/files/ieee_predictinglocomotivecrewperformance.pdf

Preliminary Analysis and Simulation of Railroad Dispatcher Workload

Published in Human Factors & Ergonomics Society, 2018

This paper discusses railroad dispatchers’ work analysis based on a large dispatch center. Read more

Recommended citation: Huang, L., Cummings, M., & Nneji, V. "Preliminary Analysis and Simulation of Railroad Dispatcher Workload." Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 62, 1: pp. 691-695. First Published September 27, 2018. *Best Paper Award in Human Performance Modeling* http://victorianneji.github.io/files/hfes-2018.pdf

Functional Requirements for Remotely Managing Fleets of On-Demand Passenger Aircraft

Published in AIAA SciTech Forum, 2018

Through the development of concepts of operations for remote management of vehicles with differing levels of autonomy, this paper presents preliminary requirements for on-demand air operations control centers. Read more

Recommended citation: Victoria C. Nneji, Mary L. Cummings, Alexander J. Stimpson, and Kenneth H. Goodrich. "Functional Requirements for Remotely Managing Fleets of On-Demand Passenger Aircraft", 2018 AIAA Aerospace Sciences Meeting, AIAA SciTech Forum, (AIAA 2018-2007) https://doi.org/10.2514/6.2018-2007 http://victorianneji.github.io/files/AIAA_SciTech2018_ROC_20171123.pdf

Exploring Concepts of Operations for On-Demand Passenger Air Transportation

Published in AIAA AVIATION Forum, 2017

This paper provides analyses of on-demand passenger air transportation, the stakeholders involved, their proposed operational concepts, and the hazards and regulations that must be addressed. Read more

Recommended citation: Victoria C. Nneji, Alexander Stimpson, Mary (Missy) Cummings, and Kenneth H. Goodrich. "Exploring Concepts of Operations for On-Demand Passenger Air Transportation," 17th AIAA Aviation Technology, Integration, and Operations Conference, AIAA AVIATION Forum, (AIAA 2017-3085) https://doi.org/10.2514/6.2017-3085 http://victorianneji.github.io/files/AIAA_Paper_10May2017.pdf

Tell Me More: Designing HRI to Encourage More Trust, Disclosure, and Companionship

Published in ACM/IEEE International Conference on Human Robot Interaction, 2016

Previous HRI research has established that trust, disclosure, and a sense of companionship lead to positive outcomes. In this study, we extend existing work by exploring behavioral approaches to increasing these three aspects of HRI. We engaged (N = 61) high school aged students in a 2 (vulnerability of robot: high vs. low) x 2 (expressivity of robot: high vs. low) between-subjects study where participants engaged in a short electronics learning activity with a robotic tutor. Our results show that students had more trust and feelings of companionship with a vulnerable robot, and reported disclosing more with an expressive robot. These findings suggest that vulnerability and expressivity may improve peoples’ relationships with robots. Read more

Recommended citation: Martelaro, N., Nneji, V. C., Ju, W., & Hinds, P. (2016, March). Tell me more: Designing hri to encourage more trust, disclosure, and companionship. In The Eleventh ACM/IEEE International Conference on Human Robot Interaction (pp. 181-188). IEEE Press. http://victorianneji.github.io/files/ieee_tellmemore.pdf