Peter Foytik

Cyber risk to transportation, industrial control systems, and traffic signal controllers

This paper is a result of a cyber risk assessment with a goal of increasing awareness to operators of infrastructure, managers, and political leadership. Senior executives and political leaders have a very limited understanding of industrial control systems (ICS) and of the crucial role ICS provide to public/private infrastructure, industry, and military systems. Therefore, to accomplish our purpose, we conducted a cyber-risk study focusing on a bridge tunnel ICS and a cyber event that tampered with traffic light operation—two scenarios of concern for senior leaders. In this paper, we present the analytic approach, discuss our model and simulation, and analyze the results using a notational data and generic system description. As a result of this study, we were able to discuss the importance of controls systems with senior leaders. We were able to demystify what we mean by “cyber”, showing that it is possible through simulation to inject the effects of cyber scenarios of concern into simulations to assess impact. Most importantly, during a system audit, ICS operators with decades of engineering experience began to realize that the ICS is vulnerable to willful intrusion.

Generic Incident Model for Investigating Traffic Incident Impacts on Evacuation Times in Large-Scale Emergencies

Traffic incidents cause a ripple effect of reduced travel speeds, lane changes, and the pursuit of alternative routes that results in gridlock on the immediately affected and surrounding roadways. The disruptions caused by the secondary effects significantly degrade travel time reliability, which is of great concern to the emergency planners who manage evacuations. Outcomes forecast by a generic incident model embedded in a microscopic evacuation simulation, the Real-Time Evacuation Planning Model (RtePM), were examined to quantify the change in time required for an emergency evacuation that results from traffic incidents. The incident model considered vehicle miles traveled on each individual segment of the studied road network model. The two scenarios considered for this investigation were evacuations of (a) Washington, D.C., after a simulated terrorist attack and (b) Virginia Beach, Virginia, in response to a simulated hurricane. These results could help the emergency planning community understand and investigate the impact of traffic incidents during an evacuation.

Integrating Truck Emissions Cost in Traffic Assignment

The adverse impacts of greenhouse gasses (GHG) and the imperative for reducing the existing rate of GHG production are well established. In the United States, the largest source of GHG emissions from human activities is from burning fossil fuels, primarily for the generation of electricity and transportation. The transportation sector accounts for 28% of all U.S. GHG production. Heavy-duty vehicles, such as large freight trucks, account for nearly one-fifth of the U.S. total, and this fraction is expected to grow rapidly. Consequently, many efforts are being used to reduce the total emissions of freight trucks. Most efforts emphasize one of four areas: engineering improvements to improve fuel economy or reduce emissions, shifts to other transport modes, improved logistics to reduce the movement of partially full or empty containers, and reduced travel costs for individual trucks. A few studies have assessed modifications to route choice considerations as a means of improving the fuel economy of individual vehicles and show potential gains. In this study, the potential gains of emissions-based route choice were assessed by integrating the U.S. Environmental Protection Agency motor vehicle emission simulator with a macroscopic regional traffic demand model. For this integration, route choices included a simplified emissions calculation within the repeated model iteration runs of an algorithm of the Frank–Wolfe type. The analyses suggested that reductions of freight truck emissions were possible and showed an example in which the total systems truck emissions were reduced by up to 0.61% (88.8 tons).

Towards a Trusted and Privacy Preserving Membership Service in Distributed Ledger Using Intel Software Guard Extensions

Distributed Ledger Technology (DLT) provides decentralized services by removing the need of trust among distributed nodes and the trust of central authority in the distributed system. Transactions across the whole network are visible to all participating nodes. However, some transactions may contain sensitive information such as business contracts and financial reports, or even personal health records. To protect user privacy, the architecture of distributed ledger with membership service as a critical component can be adopted. We make a step towards such vision by proposing a membership service architecture that combines two promising technologies, distributed ledger and Intel Software Guard Extensions (SGX). With SGX remote attestation and isolated execution features, each distributed node can be enrolled as a trusted entity. We propose security properties for membership service in distributed ledger and illustrate how SGX capabilities help to achieve these properties in each phase of membership service, including member registration, enrollment, transaction signing and verifying and transacting auditing. The SGX enabled membership service could enhance the support of privacy preservation, and defense capabilities against adversarial attacks, with scalability and cost effectiveness.

Generic incident model for use in large-scale evacuation simulations

Incidents and accidents can have a negative impact on the travel-time of road travelers; this impact is especially important during an evacuation. Many factors influence the rate and impact of incidents on a road facility (e.g., rainy conditions, driver behavior, pot-holes in the road); this has caused many transportation models to steer clear of generic incidents models. However, evacuation models do not require the high-fidelity that many other transportation models require. This paper introduces a new generic incident/accidents model that determines incident probabilities based on the modeled Vehicle Miles Traveled (VMT) and determines the effects of the incident in terms of lane closes and road capacity reductions. It was implemented in the Real-time Evacuation Planning Model (RtePM) which is a tool used to help emergency planners determine the evacuation time required to clear user-defined regions in the USA.

Distribution Analysis of Freight Transportation with Gravity Model and Genetic Algorithm

The application of a gravity model in freight modeling work on both short-haul and long-haul trips is discussed. A commodity-based gravity model was developed to assess the distribution of freight by long-haul trucks in southeastern Virginia. Although gravity models have been used extensively in transportation studies, little work has been done to address the special characteristics of freight transportation, such as the definition of friction factors and the differences between long-haul and short-haul trips. Results of a recent study of these and similar problems provide valuable insight into freight distribution modeling. A new calibration method that used a genetic algorithm was applied, various commodities were modeled, and the impact of the commodities on the accuracy of the gravity model was studied. Both travel time and travel distance were tested to generate the impedance for friction factors; results showed that for commodity-based long-haul models, travel times were more appropriate for friction factor calculations. In addition, results showed that the gamma function was more suitable than the exponential function for friction factor calculations. Extensive analyses of the causes of variation between observed values and the gravity model outputs are provided. The analyses and conclusions may help modelers better understand characteristics specific to freight transportation and can promote model constructions with greater accuracy and efficiency.