Description

This research project implements several software applications to enable algorithms to assess the dynamic (time varying) vulnerability of a transportation network. These assessment techniques will enable decision support tools for dynamic defense allocation and surveillance as well as promote the coordination of orderly evacuation and response.

Resources

Smartphone app git: Traffic Tracker Android

Map Extraction Tool: OSM Map Extractor

Publications

8. V. Shekar and L. Fiondella, Efficient Vulnerability Assessment of Large-scale Dynamic Transportation Networks, IEEE Transactions on Reliability (T-Rel). (in press)

7. V. Shekar and L. Fiondella, Transportation Network Disruptions: Quantitative Impacts on Congestion, Economics, and the Environment, In S. Chatterjee, R. Brigantic, and A. Waterworth (eds.), Applied Risk Analysis for Guiding Homeland Security Policy and Decisions, John Wiley & Sons Inc, 2021.

6. V. Basavaraj, V. Shekar, L. Fiondella, A. Rahman, N. Lownes (2017). An Algorithm to Prioritize the Restoration of a Multiple Facility, Multiple Hazard Road Network. Journal of Risk and Reliability. 

5. V. Shekar, L. Fiondella, S. Chatterjee, M. Halappanavar (2017). Quantifying Economic and Environmental Impacts of Transportation Network Disruptions with Dynamic Traffic Simulation. In Proc.IEEE International Symposium on Technologies for Homeland Security (HST2017), Waltham, MA.

4. V. Shekar, L. Fiondella, M. Halappanavar, S. Chatterjee (2017). Quantitative Assessment of Transportation Network Vulnerability with Dynamic Traffic Simulation Methods. In Proc.IEEE International Symposium on Technologies for Homeland Security (HST2017), Waltham, MA.
Best Paper Award, Disaster and Attack Preparedness, Mitigation, Recovery and Response Track.

3. L. Fiondella, A. Rahman, N. Lownes, V. Basavaraj (2016). Deployment of High Speed Rail: An Evolutionary Algorithm guided by Game Theory. IEEE Transactions on Reliability, 65(2), pp. 674-686.

2. V. Shekar, L. Fiondella (2016). Graph Extraction and Demand Profiling Applications for Transportation Network Research. In Proc. Humanitarian Technology: Science, Systems and Global Impact 2016 (HumTech2016).

1. V. Basavaraj, D. Noyes, N. Lownes, L. Fiondella (2015). Mitigating the Impact of Transportation Network Disruptions on Evacuation. In Proc. of the IEEE International Conference on Technologies for Homeland Security (HST), Waltham, MA.

Presentations and Tutorials

1. V. Shekar and L. Fiondella, Efficient Vulnerability Assessment of Large-scale Dynamic Transportation Networks, Presented to WG3 Infrastructure Analysis, Protection, and Recovery (IAP&R), 90th Military Operations Research Symposium (MORS 2022), Quantico, VA, June 2022.

2. V. Shekar, S. Chatterjee, M. Halappanavar, and L. Fiondella, Quantitative Transportation Network Vulnerability Assessment with Dynamic Traffic Simulation Methods, Presented to WG 3 Infrastructure Analysis, Protection and Recovery at the 85th Military Operations Research Symposium (MORS 2017), West Point, NY, June 2017.

3. V. Shekar and L. Fiondella, Graph Extraction and Demand Profiling Applications to support Transportation Network Vulnerability Research, Presented to WG 03 Infrastructure Analysis, Protection and Recovery at the 84rd Military Operations Research Symposium (MORS 2016), Quantico, VA, June 2016.

4. V. Shekar and L. Fiondella, Software Tools to Support Transportation Network Performance and Vulnerability Analysis, Presented at the MassDOT Innovation & Tech Transfer Exchange, Worcester, MA, Mar 2016.

5. V. Basavaraj, V. Shekar, L. Fiondella, Transportation Networks, Game Theory, and Vulnerability Mitigation, Presented to WG 2 Chemical, Biological, Radiological, Nuclear, and Advanced Explosives (CBRNE) Defense and WG 3 Infrastructure Analyses, Protection and Recovery at the 83rd Military Operations Research Symposium (MORS 2015), Alexandria, VA, June 2015.

6. Q. Wang, L. Fiondella, and N. Lownes, Quantifying the Vulnerability of Transportation Networks with Algorithmic Game Theory. In Proc. 2012 National Security Innovation Competition, Apr 2012.

7. S. Tolba, L. Fiondella, Q. Wang, R. Ammar, S. Rajasekaran, and N. Lownes, A Wireless Sensor Deployment Toolkit for Road Network and City-scale Protection. In Proc. 2012 National Security Innovation Competition, Apr 2012.

8. N. Lownes, R. Ammar, S. Rajasekaran, L. Fiondella, and Q. Wang. Securing America’s Future Transportation Infrastructure: Network Vulnerability and High-Speed Rail. HSI Journal of Homeland Security (JHS).

9. L. Fiondella, S. Tolba, A. Byrd, Q. Wang, S. Rajasekaran, R. Ammar, and N. Lownes. Optimal Deployment and Protection of High-Speed Rail. In Proc. 5th Annual Department of Homeland Security Student Day, Washington, DC, pp. 55-56, Mar 2011. Panel 3.

10. Q. Wang, L. Fiondella, A. Byrd, S. Tolba, S. Rajasekaran, R. Ammar, and N. Lownes A Many to Many Theory Approach to Measuring Transportation Network Vulnerability. In Proc. 5th Annual Department of Homeland Security Student Day, Washington, DC, pp. 87-88, Mar 2011. Panel 3.

Acknowledgments

This research was supported by the United States Department of Homeland Security (DHS) through the National Center for Risk and Economic Analysis of Terrorism Events (CREATE) at the University of Southern California (USC) under award number 2010-ST-061-RE0001. However, any opinions, findings, and conclusions or recommendations in this document are those of the authors and do not necessarily reflect views of the United States Department of Homeland Security, or the University of Southern California, or CREATE.