On the quantitative resilience assessment of complex engineered systems

Recent years have seen the increasing complexity of engineered systems. Complexity and uncertainty also exist in engineered systems’ interactions with human operators, managers, and the organization. Resilience, focusing on a system's ability to anticipate, absorb, adapt to, and recover from disruptive situations, can provide an umbrella concept...

Knowledge- and ambiguity-aware robot learning from corrective and evaluative feedback

In order to deploy robots that could be adapted by non-expert users, interactive imitation learning (IIL) methods must be flexible regarding the interaction preferences of the teacher and avoid assumptions of perfect teachers (oracles), while considering they make mistakes influenced by diverse human factors. In this work, we propose an IIL...

Decision making under deep uncertainty for pandemic policy planning

Policymakers around the world were generally unprepared for the global COVID-19 pandemic. As a result, the virus has led to millions of cases and hundreds of thousands of deaths. Theoretically, the number of cases and deaths did not have to happen (as demonstrated by the results in a few countries). In this pandemic, as in other great disasters,...

Capturing the uncertainty about a sudden change in the properties of time series with confidence curves

The representation of uncertainty in results is an important aspect of statistical techniques in hydrology and climatology. Hypothesis tests and point estimates are not well suited for this purpose. Other statistical tools, such as confidence curves, are better suited to represent uncertainty. Therefore three parametric methods to construct...

Modeling Pedestrian Tactical and Operational Decisions Under Risk and Uncertainty: A Two-Layer Model Framework

Pedestrian tactical choices and operational movement in evacuations essentially pertain to decision-making under risk and uncertainty. However, in microscopic evacuation models, this attribute has been greatly overlooked, even lacking a methodology to delineate the related decision characteristics (bounded rationality and risk attitudes), let...

Irrigation development under uncertainty: A call for adaptive investment pathways

There is an urgent need in sub-Saharan Africa (SSA) to enhance irrigation access to meet the challenges of growing population and climate risk. To achieve this, big investments are currently planned in large irrigation infrastructure. We believe there is danger in following this conventional approach, which requires big lumpsum investments,...

Real-time control of combined sewer systems: Risks associated with uncertainties

Model Predictive Control (MPC) of combined sewer systems can reduce environmental degradation caused by uncontrolled overflows. However, practical uncertainties are often neglected when assessing the potential of MPC strategies. This paper aims to understand the risks associated with using a non-perfect internal MPC-model, real precipitation...

Stochastic Stability of Discrete-time Phase-coupled Oscillators over Uncertain and Random Networks

This article studies stochastic relative phase stability, i.e., stochastic phase-cohesiveness, of discrete-time phase-coupled oscillators. Stochastic phase-cohesiveness in two types of networks is studied. First, we consider oscillators coupled with 2π -periodic odd functions over underlying undirected graphs subject to both multiplicative...

How can airports prepare for future public health disruptions? Experiences and lessons learned during the COVID-19 pandemic from a systemic perspective based on expert interviews

The COVID-19 pandemic proved to be an existential public health and economic crisis for the airport system. An interview study was conducted using Amsterdam Airport Schiphol as a use case to prepare for future public health disruptions. The study aimed to uncover key experiences and lessons learned by an airport system during the COVID-19...

A copula-based model to describe the uncertainty of overtopping variables on mound breakwaters

Rising sea levels caused by climate change are increasing the risk of overtopping on coastal structures. Moreover, there is a growing societal concern about the visual impact of these structures, which leads to the lowering of their crest freeboards. In previous studies, safety during overtopping events was assessed considering the...

Contingency Games for Multi-Agent Interaction

Contingency planning, wherein an agent generates a set of possible plans conditioned on the outcome of an uncertain event, is an increasingly popular way for robots to act under uncertainty. In this work we take a game-theoretic perspective on contingency planning, tailored to multi-agent scenarios in which a robot's actions impact the...

Distributed Adaptive Synchronization in Euler Lagrange Networks with Uncertain Interconnections

In this work we propose a new practical synchronization protocol for multiple Euler Lagrange (EL) systems without structural linear-in-the-parameters (LIP) knowledge of the uncertainty and where the agents can be interconnected before control design by unknown state-dependent interconnection terms. This setting is meant to overcome two...

High-Confidence Data-Driven Ambiguity Sets for Time-Varying Linear Systems

This paper builds Wasserstein ambiguity sets for the unknown probability distribution of dynamic random variables leveraging noisy partial-state observations. The constructed ambiguity sets contain the true distribution of the data with quantifiable probability and can be exploited to formulate robust stochastic optimization problems with out...

Uncertainty of thermosphere mass density observations derived from accelerometer and GNSS tracking data

Thermosphere mass density and crosswind can be derived from accelerometer and GNSS tracking data. However, present datasets are often provided without comprehensive uncertainty specifications. We present a newly developed method that propagates measurement noise and errors in the satellite specification, thermosphere models, and radiation flux...