Special Robotics Seminar: Victoria Chibuogu Nneji, "Heterogeneous Autonomous Transportation Networks
Wednesday, May 2, 2018
2168 AV Williams
301 405 4358
Special Robotics Seminar
Investigating Remote Operations Centers for Heterogeneous Autonomous Transportation Networks
Victoria Chibuogu Nneji
Robotics Ph.D. Candidate
The concept of On-Demand Mobility (ODM) in aviation has gained popularity in recent years, with several manufacturers proposing vehicles for high-speed intra-city air taxis. However, less attention has been placed on how these networked fleets would be operationally controlled and managed. Through the development of concepts of operations for remote management of fleets with heterogenous levels of vehicle and network autonomy, this research presents preliminary requirements for ODM operations centers. The centers would interface with traffic control and be responsible for ensuring safe, efficient, and effective operations of networks. This effort identified key functional requirements related to vehicle safety for these futuristic concepts. Further, using data gathered from airline companies and other transportation industry sources, this work introduces a predictive model of human-system performance in these operations control centers. With this tool, people making strategic, tactical, and operational decisions can rapidly prototype future concepts of operations to better plan for staffing and design of the remote operations centers.
Victoria Chibuogu Nneji studied Applied Mathematics at Columbia University in New York City and earned a Master of Engineering Management from Duke University in her hometown of Durham, North Carolina. In 2017, Victoria became the first Ph.D. candidate in Duke's robotics program. There, she works with Professor Missy Cummings and has led projects with NASA and the DOT on modeling remote operations centers for autonomous vehicle networks in rail, air, and surface transportation systems. Victoria hopes to make a positive difference in future mobility and logistics design decisions by strategizing with human factors-systems engineering considerations when integrating artificial intelligence into operations.