H M Abdul Aziz
Husain M. Abdul Aziz is a research scientist in the computational sciences and engineering division at the Oak Ridge National Laboratory. He works with the geographic information science and technology group and part of the “sustainable mobility” group of the Urban Dynamic Institute. He earned his Ph.D. in Civil Engineering with a concentration in Transportation Infrastructure and Systems from Purdue University, West Lafayette. He is currently leading two EEMS (Energy Efficient Mobility Systems) projects sponsored by the Vehicle Technology Office of the Department of Energy. His primary areas of expertise include: (a) transportation modeling and simulation in the paradigm of Connected and Automated Vehicles — travel behavior, network modeling, and traffic control; (b) application of optimization techniques in road infrastructure operations and management under extreme events — assessing vulnerability, identifying critical components, and optimizing operations through analytical models and agent-based simulation; (c) applying data science for transportation — econometric and machine learning based models using open data including connected vehicle environment data, and data from transportation network companies such as Uber. His scientific outputs include peer-reviewed journal publications, numerous peer-reviewed conference presentations, and a book chapter. He is a member of the Institute of Transportation Engineers and an Associate member of the American Society of Civil Engineers. He is affiliated with several committees of the Transportation Research Board of the National Academies of Sciences, Engineering, and Medicine.
Aziz, H. M. A., Wang, H., Young, .S., Sperling, J. and Beck, J., (2017). Synthesis Study on Transitions in Signal Infrastructure and Control Algorithms for Connected and Automated Transportation (No. ORNL/TM-2017/280). Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States).
Aziz, H. A., Nagle, N. N., Morton, A. M., Hilliard, M. R., White, D. A., & Stewart, R. N. (2017). Exploring the impact of walk–bike infrastructure, safety perception, and built-environment on active transportation mode choice: a random parameter model using New York City commuter data. Transportation, 1-23.
Aziz, H. M. A., & Ukkusuri, S. V. (2016). Network Traffic Control in Cyber-Transportation Systems Accounting for User-Level Fairness. Journal of Intelligent Transportation Systems, 20(1), 4-16.
Zhu, F., Aziz, H. A., Qian, X., & Ukkusuri, S. V. (2015). A junction-tree based learning algorithm to optimize network wide traffic control: A coordinated multi-agent framework. Transportation Research Part C: Emerging Technologies, 58, 487-501.
Aziz, H. M. A., & Ukkusuri, S. V. (2012). Integration of environmental objectives in a system optimal dynamic traffic assignment model. Computer‐Aided Civil and Infrastructure Engineering, 27(7), 494-511.
Aziz, H. M. A., Ukkusuri, S. V., & Zhan, X. (2017). Determining the impact of personal mobility carbon allowance schemes in transportation networks. Networks and Spatial Economics, 17(2), 505-545.
Aziz, H. M. A., & Ukkusuri, S. V. (2014). Exploring the trade-off between greenhouse gas emissions and travel time in daily travel decisions: Route and departure time choices. Transportation Research Part D: Transport and Environment, 32, 334-353.
Aziz, H. M. A., Ukkusuri, S. V., & Hasan, S. (2013). Exploring the determinants of pedestrian–vehicle crash severity in New York City. Accident Analysis & Prevention, 50, 1298-1309.