Category: Systems and Connectivity

North American freight railroads uniquely combine safety, speed and efficiency in transporting large amounts of freight long distances over land. Prompted by railroad commitments to reduce emissions, and looming stricter in-use locomotive emissions regulations, US freight railroads face the challenge of reducing or eliminating the roughly 3 billion gallons of diesel fuel consumed each year. To achieve this, North American freight railroads are exploring alternative technologies, including modern options for electrification that leverage traditional traction power supply via overhead contact (catenary) systems (OCS), along with rapidly advancing battery technology.

Previous research by the University of Texas at Austin has investigated the overall economics of pure OCS and Battery Electric Locomotive (BEL) options. The resulting Cost Uncertainty and Risk of Rail Electrification wit New Technologies (CURRENT) model is also capable of evaluating the concept of intermittent electrification that uses batteries onboard electric locomotives to reduce the amount of OCS construction required on a given corridor.

Currently, application of the CURRENT model is subject to two main limitations. First, the model assumes battery performance and efficiency as a function of state of charge is static over time and not influenced by environmental temperature. Second, intermittent electrification case studies have used engineering judgement to identify the locations of OCS segments along a corridor. However, it is likely that OCS placement could be further optimized to reduce infrastructure costs and maximize the battery range and corresponding lengths of gaps in the OCS.

This project will advance the CURRENT model to address both of these limitations. The project team will identify and implement an appropriate battery degradation model to accurately capture the change in battery efficiency and storage capacity as a function of discharge cycles over time. This change in efficiency will alter the long-term economics of batteries within the CURRENT model. The project team will also develop an algorithm to optimize OCS placement on a given corridor subject to traffic, topography and onboard battery size. It is anticipated that a genetic algorithm framework will be coupled with the CURRENT model to identify the combination of segments that maximizes economics.

Rail infrastructure is a critical component of the national economy, with track systems representing some of the most valuable assets in the railroad industry. Key datasets, including track layout data, condition monitoring data, repair and maintenance records, are frequently siloed across departments, limiting their combined utility in streamlining track asset management and safety analyses. This research addresses these challenges by developing an integrated informatics-enabled intelligent platform to unify disparate datasets into a centralized data warehouse. The platform leverages temporal-spatial data analysis to integrate and overlay track chart data with various types of condition monitoring data and other operational records, enabling advanced data analytics for track asset management. Statistical and machine learning techniques will be applied to analyze and predict track changes, identify degradation trends, and ultimately support proactive inspection and maintenance planning. The project will focus on building a digital intelligent platform in collaboration with NJ Transit that provides seamless access to their various types of enterprise and asset data, supporting complex data queries and condition monitoring data analysis. While developed in close collaboration with NJ Transit, the platform is adaptable for use by other railroads facing similar challenges. This research advances the state of infrastructure management by breaking down data silos and enabling data-driven decision-making. The outcomes will contribute to improved safety and operational reliability of rail systems.

Positive Train Control (PTC) is a combination of systems and protocols that provide wireless communication between railroad operations, locomotives, and wayside equipment. Its original purpose is to ensure that trains comply with track speed restrictions and signals by providing this information to a control system inside the locomotive that can take corrective action. Because the main PTC communication channel is 220 MHz radio, an attacker can observe and tamper with all PTC communications. To prevent an attacker from tampering with PTC messages, the current implementation authenticates them using Message Authentication Codes (MACs). MACs are a form of symmetric cryptography where all parties share a common secret key: if the key is compromised, an attacker can forge apparently authentic messages. This is particularly problematic in the rail setting, where the communicating parties include all locomotives operating on a section of track as well as all wayside equipment along the track. If any of these systems are compromised, an attacker can gain access to the secret key.
Modern cryptographic protocols, including the HTTPS protocol used to secure the Web, use asymmetric cryptography, which does not require a common secret key. The primary goal of this proposal is to develop a scheme for authenticating PTC communications using asymmetric cryptography, and to do so in line with current communication security best practices, including public key infrastructure and robust mechanisms to mitigate key compromise.
Today, the PTC communication channel is used more broadly, as a general-purpose communication link between the railroad, its locomotives, and its wayside equipment. The security implications of other applications using the PTC link are not well understood. Indeed, past experience with system security (and its painful lessons) have taught us that security problems occur when systems are pushed beyond their original design goals. The second aim of the project is to identify other uses of PTC communications and assess their security requirements, providing recommendations for additional security mechanisms or practices as needed.
In line with computer security community best practices, the project will make its proposed scheme and implementation open, in order to invite public scrutiny and vulnerability assessment.