Earl E. Lee

Restoration of Services in Interdependent Infrastructure Systems: A Network Flows Approach

Modern society depends on the operations of civil infrastructure systems, such as transportation, energy, telecommunications, and water. These systems have become so interconnected, one relying on another, that disruption of one may lead to disruptions in all. The approach taken in this research is to model these systems by explicitly identifying these interconnections or interdependencies. Definitions of five types of infrastructure inter-dependencies are presented and incorporated into a network flows mathematical representation, i.e., an interdependent layer network model. Using the lower Manhattan region of New York, for illustrative purposes, the implementation of the model is shown. First, the data requirements are presented with realistic data on the interdependent infrastructure systems of power, telecommunications, and subways. Next, a scenario is given that causes major disruption in the services provided by these infrastructures and demonstrates the use of the model in guiding restoration of services. The paper concludes with a discussion of accomplishments and opportunities for future work.

Near-Term Travel Speed Prediction Utilizing Hilbert-Huang Transform

: Accurate short-term prediction of travel speed as a proxy for time is central to many Intelligent Transportation Systems, especially for Advanced Traveler Information Systems and Advanced Traffic Management Systems. In this study, we propose an innovative methodology for such prediction. Because of the inherently direct derivation of travel time from speed data, the study was limited to the use of speed only as a single predictor. The proposed method is a hybrid one that combines the use of the empirical mode decomposition (EMD) and a multilayer feedforward neural network with backpropagation. The EMD is the key part of the Hilbert–Huang transform, which is a newly developed method at NASA for the analysis of nonstationary, nonlinear time series. The rationale for using the EMD is that because of the highly nonlinear and nonstationary nature of link speed series, by decomposing the time series into its basic components, more accurate forecasts would be obtained. We demonstrated the effectiveness of the proposed method by applying it to real-life loop detector data obtained from I-66 in Fairfax, Virginia. The prediction performance of the proposed method was found to be superior to previous forecasting techniques. Rigorous testing of the distribution of prediction errors revealed that the model produced unbiased predictions of speeds. The superiority of the proposed model was also verified during peak periods, midday, and night. In general, the method was accurate, computationally efficient, easy to implement in a field environment, and applicable to forecasting other traffic parameters.

Assessing vulnerability of proposed designs for interdependent infrastructure systems

Recent events have heightened our awareness of the vulnerability of civil infrastructure systems. Most of the research on this topic has focused on individual systems, while more recent efforts have recognized the interconnectedness of systems. Infrastructure systems have become so highly interconnected that a failure in one system can propagate through many systems and affect large geographic areas. The focus of this research is on reducing vulnerability by adding redundancy while taking into account the interdependencies of infrastructure systems. The paper first presents background and definitions related to interdependent infrastructure systems. An algorithm is then presented that identifies vulnerabilities in the current and proposed designs due to interdependencies with other infrastructure systems. An illustrative case, the reliance of telecommunications on power, is used to demonstrate the practicality of the proposed procedure. The paper concludes with a discussion of further research, both theoretical and operational.

Probes as Path Seekers: A New Paradigm

In a recent field experiment, a fleet of Global Positioning System—equipped vehicles shared real-time data about network travel times over a wireless network and had their path choices automatically updated accordingly. This paper describes the behavior of these 200 vehicles during the 3-month experiment and illustrates the kind of information that can be derived from the data archive that the vehicles created. Much can be learned about real-time traffic-responsive path choice, travel times, compliance, and more. Planners, designers, and system operators can learn much about the way a system behaves and can sharpen their ability to create systems that work effectively and efficiently under all ranges of use. True path seeking by probe-equipped vehicles will arise when such vehicles become a common part of the vehicle fleet.

Logic-based MultiObjective Optimization for Restoration Planning

After a disruption in an interconnected set of systems, it is necessary to restore service. This requires the determination of the tasks that need to be undertaken to restore service, and then scheduling those tasks using the available resources. This chapter discusses combining mathematical programming and constraint programming into multiple objective restoration planning in order to schedule the tasks that need to be performed. There are three classic objectives involved in scheduling problems: the cost, the tardiness, and the make span. Efficient solutions for the multiple objective function problem are determined using convex combinations of the classic objectives. For each combination, a mixed integer program is solved using a Benders decomposition approach. The master problem assigns tasks to work groups, and then subproblems schedule the tasks assigned to each work group. Hooker has proposed using integer programming to solve the master problem and constraint programming to solve the subproblems when using one of the classic objective functions. We show that this approach can be successfully generalized to the multiple objective problem. The speed at which a useful set of points on the efficient frontier can be determined should allow the integration of the determination of the tasks to be performed with the evaluation of the various costs of performing those tasks.

Impact of the 2001 World Trade Center attack on critical interdependent infrastructures

This work investigates the impact of the 2001 World Trade Center attack on critical infrastructure systems in the New York City metropolitan area. Of particular interest are the physical or logical connections - also known as interdependencies - among these systems, and the results of disruptions associated with the attack on them. Prior research on infrastructure interdependence has concentrated on modeling the consequences of interdependencies among impacted infrastructure systems. This work catalogues and analyzes reports of impacts to interdependent infrastructure systems associated with the 2001 World Trade Center attack. The results suggest that there were impacts to various types of interdependencies among nearly all critical infrastructure systems. Moreover, impacts continued to be reported throughout the one hundred day period following the attack. The paper concludes with a discussion of possible strategies for improving understanding of infrastructure interdependencies and for managing them during an emergency response.

Marine Vessels as Substitutes for Heavy-Duty Trucks in Great Lakes Freight Transportation

Abstract This paper applies a geospatial network optimization model to explore environmental, economic, and time-of-delivery tradeoffs associated with the application of marine vessels as substitutes for heavy-duty trucks operating in the Great Lakes region. The geospatial model integrates U.S. and Canadian highway, rail, and waterway networks to create an intermodal network and characterizes this network using temporal, economic, and environmental attributes (including emissions of carbon dioxide, particulate matter, carbon monoxide, sulfur oxides, volatile organic compounds, and nitrogen oxides). A case study evaluates tradeoffs associated with containerized traffic flow in the Great Lakes region, demonstrating how choice of freight mode affects the environmental performance of movement of goods. These results suggest opportunities to improve the environmental performance of freight transport through infrastructure development, technology implementation, and economic incentives.

Experimenting with Real-Time ATIS: Stepping Forward from ADVANCE

In the early 1990’s an in-vehicle navigation and route guidance project called ADVANCE was conducted in the northeastern suburbs of Chicago. It proved that travel time data could be updated on in-vehicle devices (albeit not in real-time) to assist drivers in choosing faster routes to their destinations. This past spring, about a decade later, a more progressive but similar 3-moonth field experiment was conducted in upstate New York. Nearly 200 participants used state-of-the-art, in-vehicle navigation and route guidance technology in conjunction with GPS tracking and broadband wireless to share travel time data and pick the shortest paths through a congested network. The route guidance devices observed travel times, uploaded them to a central server that updated a travel time database, and then downloaded every minute to each of the probe vehicles to ensure the latest travel time information was being used while enroute. The experiment resulted in a total of 4,111,210 latitude-longitude position/speed/time points. The largest number of location points per user was 98,018 while the smallest was 117; the average per user was just over 26,000 location points, or 325.5 points per trip. There were 12,629 probe trips for a traveled distance of 147,316 miles over a duration of 3,945.8 hours. This paper presents a discussion of the Capital District ATIS project including the parallels and differences with the ADVANCE effort. Areas covered are: travel time data, project background, description of the study data, participant statistics, experimental design, sample results, and a summary with future research directions.

A systems view of data integration for emergency response

In the wake of the terrorist attacks of 11 September 2001 and Hurricane Katrina, emergency response has acquired a new level of importance. Emergency managers must be prepared to respond to conscious acts of terror, caused by individuals wanting to inflict harm, as well as the more traditional natural calamities and human errors. Response must be faster, more integrated, and more intelligent in responding to these events in order to reduce the human, environmental and economic losses. One key element of improved response is improving the ability of the first responders (fire, EMS, police, etc.) to share data in time to support decision-making. This paper will discuss methods for improving data sharing, including how communications and computing technologies can facilitate the integration. Finally, a description of ongoing research in improving traffic incident management in the Capital District region of New York State will be presented.