Quantifying the Resilience of Logistics Operations with Disaggregate Spatiotemporal Data for Transportation and Land Use Planning

Pennetti, Cody, Systems Engineering - School of Engineering and Applied Science, University of Virginia
Lambert, James, EN-Eng Sys and Environment, University of Virginia

There is worldwide interest to address the vulnerabilities of infrastructure systems that serve operations logistics. Risk to logistics operations from economic downturns, technologies, natural disasters, regulations, global pandemics, and other emergent and future conditions is a concern. Methods of assessing disruptions on various time scales are needed to inform planning and prioritization of improvements to infrastructure systems. In particular, the disruptions of transportation networks are often obfuscated by daily aggregation of performance data; however, recent advances in methods of data collection, dissemination and processing provide the disaggregated data to understand disruptions to operating conditions on the scale of minutes and hours. This dissertation develops methods of quantifying and monitoring disruptions of transportation systems from perceptions of scheduled operations logistics, which requires layers of disaggregate spatiotemporal data to assess sub-daily variations in system performance. Five methods are developed and demonstrated as follows: (i) new measures of quantifying disruption are introduced by methods of disaggregate data analysis for an arterial highway network system; (ii) perspectives of disruptions are extended with methods of kernel density estimation (KDE) to consider deviations from the most frequently observed conditions; (iii) changepoint detection is applied to identify performance thresholds occurring by system demand; (iv) a temporal corridor trace analysis (t-CTA) method is provided to assess regional performance by valuation across disparate time periods; and (v) the methods are demonstrated in a spatiotemporal agent simulation for evaluating site-specific land use initiatives. The methods will improve adaptation and resilience of the transportation systems to performance variability in topics including freight logistics, workforce commuters, public transit, emergency transports, event management, et al.

PHD (Doctor of Philosophy)
Transportation, Logistics, Land Planning, Risk Analysis
All rights reserved (no additional license for public reuse)
Issued Date: