BAA_2019_Appendix_C_3_24_19.pdf

FRA BAA 2019 - March 2019

Federal Railroad Administration Office of Research, Development, and Technology

Broad Agency Announcement – BAA 2019

Appendix C – Research Topics

Note: Concept papers may be submitted at any time, through the closing date of the research topic.

Track Research

Topic Title Closing Date for Concept Papers

FRA-TR-001 Investigating the Use of Artificial Intelligence in Track-Related Defect Detection and Prediction

May 31, 2019

FRA-TR-002 Advancing Rail Flaw Detection Capability May 31, 2019

FRA-TR-003 Collision Detection for Bridges May 31, 2019

FRA-TR-004 Intelligent Track Systems Technology May 31, 2019

Rolling Stock and Equipment Topic Title Closing Date for Concept

Papers

FRA-RS-001 Topology-based Resilience of Freight Transportation Networks

May 31, 2019

FRA-RS-002

Feasibility of Improving Crash Energy Management

(CEM) of Existing Passenger and Critical Hazmat Equipment

May 31, 2019

Train Control Topic Title Closing Date for Concept

Papers

FRA-TC-001 Train Control Communication Security May 31, 2019

Human Factors Topic Title Closing Date for Concept

Papers

FRA-HF-001 Trespass Prevention and Suicide May 31, 2019

FRA-HF-002 Highway-Rail Grade Crossing Safety May 31, 2019

FRA-HF-003 Combating Fatigue in the Railroad Industry May 31, 2019

FRA-HF-004 Automation and the Human-Machine Interface May 31, 2019

FRA-HF-005 Roadway Worker and Railroad Employee Protection May 31, 2019

Track Research

Topic: FRA-TR-001

Title: Investigating the Use of Artificial Intelligence in Track-related Defect Detection & Prediction

In February 2019, the White House issued an Executive Order on Maintaining American Leadership in Artificial Intelligence (AI) in response to the growing rate of AI-related technological innovations in nearly every industry imaginable. Under this direction, the Federal Railroad Administration (FRA) is spearheading efforts to investigate the application of AI for advancing railway safety for our national rail transportation system.

Track infrastructure is the second leading contributor to the number of accidents/incidents on our nation’s rail network each year. Despite a notable downward trend in track-caused accidents/incidents over the last decade, the industry still sees more than 400 of these accidents/incidents each year. Even though these events are extremely rare, it is still possible to improve and see a future where there are zero high-consequence accidents and derailments.

The objective of this research is to provide new knowledge, insights, and implementation tools to assist FRA and the railroad industry in general in improving railway track inspection systems using innovative AI technologies for real-time (or near real-time) detection and/or prediction of track-related defects. Proposed research should provide a multi-phased approach that addresses the following goals:

• Understanding what has been done in the industry with respect to the development of AI applications that could be applied to track-related defect detection and prediction, and…

• Assisting North American railroads in developing AI-enabled, data-driven capabilities to detect and/or predict track-related defects in real-time or near real-time.

The offerors must demonstrate (1) an established experience in the development of AI algorithms and (2) a confirmed partnership with a railroad for relevant datasets necessary to progress the research.

Topic: FRA-TR-002

Title: Advancing Rail Flaw Detection Capability

Internal rail flaws can lead to train derailments that result in human fatalities and injuries, environment damage, and high costs. This topic seeks projects that address one or more of the following rail flaw inspection research objectives:

• Non-contact rail inspection at track speed (i.e. up to 45mph or greater).

• Full rail (i.e. not just rail head) inspection for internal and external defects.

• Automation of rail flaw detection through machine learning, AI or other means.

Offerors shall demonstrate knowledge and comprehension of the scientific and other technical challenges encountered in any similar past efforts. Offerors explain how their proposed research differs from prior work and how it advances the state of the art. Preferences shall be given to research projects and technologies that have a higher TRL (Technology Readiness Level) and/or are ready for field or application testing. Projects should be focused to obtain significant, measurable results.

Topic: FRA-TR-003

Title: Collision Detection for Bridges

Bridges are a critical link in railway infrastructure. Bridge damage can result from impact from passing train traffic above or highway traffic impact below. The impact of highway vehicles into railway bridges is not uncommon. While this type of impact does not usually limit the performance of the bridge, bridge strikes must be inspected to ensure safety. Technology to help categorize the type (train traffic, vehicle, maritime, etc) and magnitude of the impact is desired to quantify the nature of bridge strikes. The data is expected to be useful in documenting the occurrence of strikes, the nature of the strike, ratings for damage, impact identification, and the likelihood that the strike resulted in structural bridge damage.

Measurement techniques and/or analytical techniques that use available data or existing systems are also sought under this topic.

Topic: FRA-TR-004

Title: Intelligent Track Systems Technology

Traditional track inspection technologies rely on sophisticated technologies to measure track parameters that highlight conditions which pose a safety or maintenance concern for railroad operations. These measurement systems are almost always external to the system or component being measured. This topic seeks innovative approaches to imbed sensors and detection and communications technologies within the track structure to allow for a type of self-enunciation when conditions warrant remedial maintenance or pose a threat to safe rail operations. The long-range objective is to develop technology that permits railroad track to communicate its “state-of repair” directly, in a manner that is somewhat analogous to the way modern devices communicate via the internet of things (IoT).

Railroad track is a complex arrangement of structural elements designed to safely support dynamic train loads. This system of elements – subgrade, ballast, crossties, fasteners, and rail (including special track work) – is subject to deterioration due to wear and environment factors that can impact its ability to safely support train loads. Each element plays an important role in the system and overall rail safety would be enhanced if these elements could self-report their condition state.

The goal for this research topic is to complete a feasibility study of a connected, intelligent track system that will automatically report condition states. This study should include:

• an analysis of the type of conditions that can be measured or detected with modern sensor technologies, and their impact on railroad safety,

• an analysis of the methods by which the track can communicate condition information

• a discussion of the cost and benefits associate with this type of system, and

• a system development plan that can be used to continue research and begin field demonstration of the technology.

Rolling Stock and Equipment Research

Topic: FRA-RS-001

Title: Topology-based Resilience of Freight Transportation Networks

The draft 2019 National Freight Strategic Plan (https://www.transportation.gov/freight/NFSP), articulates the need to enhance the national freight system to address key challenges corresponding to several major trends affecting freight transportation including: (1) expected growth in freight tonnage, (2) underinvestment in the freight system, (3) difficulty in planning and implementing freight projects, (4) continued need to address safety, security, and resilience, and (5) increased global economic competition.

A fundamental consideration to these areas is the network topology defining the freight transportation system. Does the network have the topological structure to offer robustness, resiliency, efficiency and effectiveness? What are the nodal and linkage bottlenecks? What are the investment strategies to be examined to enhance the network to meet these challenges?

Topic: FRA-RS-002

Title: Feasibility of Improving Crash Energy Management (CEM) of Existing Passenger and Critical Hazmat Equipment

The first step will be to conduct a detailed Literature review to analyze/investigate the current and previous state-of-the-art methods in Crash Energy Management (CEM) Technology and Implementations (world-wide). Then, an accurate and reliable feasibility analysis should be provided to improve the CEM capabilities of existing (in-service) passenger and critical hazmat equipment, through cost-effective adaptations and retrofit technology.

https://www.transportation.gov/freight/NFSP

Train Control

Topic: FRA-TC-001

Title: Train Control Communication Security

Background: With the continuing rollout of Positive Train Control (PTC) systems, US railroads and government agencies are working to promote improved security and explore innovative approaches for maintaining confidentiality of rail communications. Large geographical operational areas and bandwidth constraints necessitate proposed solutions be highly bandwidth efficient and compatible with existing PTC radios and equipment.

Objectives: Engage with a technical advisory group of relevant railroads and rail industry suppliers, develop operational concepts for methods of enhancing rail communication confidentiality, produce a detailed cost/benefit analysis and implementation plan, and identify technology gaps needing additional research.

Description of Research Need: The US rail system is designated a critical national transportation infrastructure and needs to be adequately protected from cyber-attack. The expertise of the security research community is needed to develop an innovative rail communications security approach.

Technology Focus Areas: Train Control, Communications Systems, Cyber Security

Project Details: Up to 1 award, $800k available budget, 6-18 month acceptable duration.

Human Factors

Topic: FRA-HF-001

Title: Trespass Prevention and Suicide

The U.S Department of Transportation’s (USDOT) Federal Railroad Administration (FRA) issued to Congress the first National Strategy to Prevent Trespassing on Railroad Property in 2019 (https://www.fra.dot.gov/eLib/Details/L19817). The report examines the causal factors that contribute to trespassing incidents on railroad property.

FRA seeks to support research that is aligned with the National Strategy to Prevent Trespassing on Railroad Property. For instance, a trespasser close call (or sometimes referred to as a near-hit) is a situation in which a trespasser is almost struck by a train, but escapes without injury and the incident is captured by a locomotive camera or reported by a train crew. Close call data would enable FRA to better identify trespasser hot spots and could be particularly beneficial in deploying law enforcement and railroad police more efficiently and determining what, if any, human factors engineering solutions may be feasible in particular circumstances.

Research proposals related to trespass may address, but are not limited to:

• Research that addresses trespasser mitigation through human factors engineering solutions and technology

• Identification and development, through independent analysis and collaboration with railroads and other stakeholders, known and new data sources and technology that could better identify trespasser hot spots or risk factors that lead to trespassing

• Identification and development of new analytical tools to effectively analyze trespasser data

In addition, the FRA is interested in objectively understanding the potential benefit of various forms of surveillance on railroad suicide prevention. Surveillance, be it through rail personnel trained to identify individuals at risk for suicide or through advanced technology, has the potential to identify suicide risks and intervene, but little is known about how effective these methods are for this purpose.

Research proposals related to suicide may address, but are not limited to:

• Research and development of technology to identify suicide risks and behaviors, including detection and intervention.

https://www.fra.dot.gov/eLib/Details/L19817

Topic: HF-002

Title: Highway-Rail Grade Crossing Safety

This research seeks to develop interventions or solutions that increase motorist, pedestrian, and/or bicyclist compliance at active and passive highway-rail grade crossings through human factors engineering. The overall purpose is to reduce significant safety risks and improve safety by incorporating human factors engineering into grade crossing design and operation. The FRA is interested in research ideas and pilot projects that address variables such as human perception, decision making, distraction and fatigue.

Topic: HF-003

Title: Combating Fatigue in the Railroad Industry

The FRA is interested in research and pilot projects that address the railroad industry’s susceptibility to the risk of injury and property damage caused by human fatigue and loss of attentiveness. This susceptibility is the result of several inevitable factors surrounding the around-the-clock operations faced by railroaders, including irregular hours of work, long shifts, and the unpredictability of on-duty times. FRA seeks to develop interventions and effective technological solutions to mitigate safety risks associated with these factors.

Research proposals may address, but are not limited to:

• Scheduling/calling systems

• Shiftwork

• Calling assignments

• Sleep disorder screening and treatment

• Fail-safe technologies

Topic: HF-004

Title: Automation and the Human-Machine Interface

The FRA seeks to explore the application and feasibility of electronic tools and automation to address rail operational safety, efficiency, and human performance issues.

Research proposals may address, but are not limited to:

• the application of artificial intelligence and machine learning in railroad operations

• the integration of system functionality and system displays into a common operating interface (human interface) in railroad operations

• the development of locomotive cab head-up display requirements, rail symbols, and messaging

• risks of deskilling with the use of automation

• potential human performance issues related to training and operations with the introduction of automated systems

• development of electronic tools and automated systems to improve situational awareness (in dispatch, locomotive, other)

Topic: HF-005

Title: Roadway Worker and Railroad Employee Protection

This research seeks solutions to mitigate risks to roadway workers, train crews, and railroad employees due to human factors errors by developing technologies to mitigate/eliminate risk.

A thorough assessment of employee protection procedures and the associated human factors risks is necessary prior to developing countermeasures to these risks.

Research proposals may address, but are not limited to:

• Methods of protection outlined in CFR 214 Subpart C, such as Train Approach Warning

• Adjacent track safety

• Worker safety at highway-rail grade crossings

• Railroad switching environment