The Federal Railroad Administration (FRA) should permit railroads that have utilized expanded ATI inspections in conjunction with a reduced level of visual inspections to continue and expand their programs. FRA should modernize its regulations to account for ATI and other future technologies that are proving to enhance safety. It is unconscionable for a safety regulator to impede safety gains.

Sustained railroad infrastructure investment and ongoing efforts to advance track safety via the adoption of inspection technologies such as automated track inspections (ATI), the development of better track components, and advancements in track inspection and maintenance practices, among other efforts, have resulted in substantial track safety gains. The freight rail industry is among the safest industries in the nation.

Technological solutions are imperative to railroads’ goal of an accident-free future. While not mutually exclusive, ATI technologies that track geometry conditions outperform mandated manual inspections done with the human eye and handheld tools required by outdated regulations. Data show that the blended use of ATI with visual track inspections increases rail safety.

In 1971 (before the Staggers Act of 1980 reduced railroad economic regulation), FRA set the frequency visual track inspections must occur. These inspections involve a track inspector visually looking at railroad tracks and using handheld measuring tools either on foot or while traveling in a truck specially designed to drive on railroad tracks (known as a hi-rail vehicle).

Today, trucks drive themselves, drones deliver food and virtual assistants help run our everyday lives. But still, freight railroads are forced to operate under the same visual track inspection regulations from 1971 — a time when the 8-track tape player was considered cutting-edge technology.

ATI enables railroads to measure how the track structure performs under the load of a train. ATI systems use lasers and cameras mounted onto locomotives or rail cars and inspect track as the train travels across the network. The system tests each foot of track under the same force as exerted by a loaded train. The data from the inspection devices transmits to a centralized location where employees schedule maintenance as necessary.

Railroads can inspect hundreds of thousands of miles per year by placing the automated equipment on a locomotive or in a boxcar. Railroads are looking to apply to expand testing along mainline routes, which covers most Class I trackage. At the same time, visual inspections will still be done at a reduced level.

Speeding up safety inspections: ATI systems have proven an extremely valuable railroad safety tool to reduce track-caused derailments. Not only have freight railroads invested millions of dollars in ATI, but so has the FRA. Experience has shown that ATI detects track geometry defects with more accuracy, consistency and frequency than do visual inspections, leading to quicker repair or elimination of those defects.

The ATI technology also allows railroads to collect huge amounts of safety data to better understand and evaluate the safety of their track infrastructure and to develop improved preventative track maintenance practices. This technology also allows railroads to better develop short-term and long-term capital expenditures and where to best allocate resources.

Safeguarding employees: Another safety benefit flowing from the use of ATI technology is a reduction in employee — usually track inspectors — risk exposure along the railroad right of way. FRA safety data indicates reportable accidents involving hi-rail vehicles occur regularly, specifically at highway-rail grade crossings with motor vehicles.

The use of ATI to partially fulfill track inspection mandates via the use of already occurring train movements (oftentimes along higher speed main tracks) eliminates unnecessary potential risk exposures. Risk is reduced via the decreased need for inspectors to physically occupy track solely to fulfill outdated visual inspection frequencies.

Improving efficiency, network capacity and supply chain flow: The blended use of ATI with visual inspections reduces the need for track inspectors to halt or slow down train traffic to fulfill a visual inspection frequency. This aspect of ATI improves network capacity and reduces the number of opportunities for blocked crossing occurrences. FRA has been using automated track inspection geometry vehicles to improve track safety for over 30 years.

In 2018, the Class I railroads began requesting to conduct autonomous ATI test programs to collect safety data that would help inform FRA rulemaking and ultimately make railroads even safer. BNSF received FRA approval to conduct an autonomous ATI test program on certain routes in September 2018, and FRA successfully defended that approval in federal court after it was challenged by a labor organization. Thereafter, Norfolk Southern (NS), CSX, Union Pacific, Canadian Pacific (now CPKC) and Canadian National received similar FRA approvals to conduct test programs.

Test programs have been successful. The ATI test programs are phased and involve a blended approach of performing some of the required visual inspections in concert with added ATI inspections. This approach allows for the continued detection of certain track defects not detected by current ATI technology (e.g., overgrown vegetation) while embracing ATI’s superior safety outcomes for identifying and remedying unprotected track geometry defects.

The data railroads have submitted to FRA as a condition of the test programs show positive track safety developments during the test programs, namely the reduction in FRA geometry defects present on main track. In some instances, there have been over 90% fewer unprotected defects that require remedial actions under FRA regulations.

Railroads want to expand the use of ATI. In January 2021, BNSF obtained approval from FRA for a waiver of compliance for a period of five years from the required visual inspection frequencies on two subdivisions of its rail lines. BNSF’s waiver accommodates the blended use of ATI in conjunction with visual inspections.

FRA granted BNSF’s waiver after what the agency recently described to Congress as the “successful results of the [BNSF] test program”, and due to cited improvements under the “BNSF track geometry measurement test program based on the established defect metric, FRA monitoring procedures, and consistency of number of defects located by visual track inspection.”

Given the ongoing success BNSF has seen under its existing waiver, on June 15, 2021, BNSF applied to expand the waiver to additional subdivisions on its network.

Similarly, on March 22, 2021, NS also applied for a waiver, requesting relief to allow for the blended use of existing visual inspections in concert with ATI inspections. The NS waiver petition also was premised on the positive results from its test program.

Despite the success of the ATI programs, FRA is impeding the forward safety progress of the industry’s ATI programs and the accompanying long overdue regulatory reforms. In 2021, FRA let one of the ATI test programs expire, delayed action on Canadian National’s request to move to the next phase of its still-in effect test program and denied NS’ request to continue its expired test program.

In March 2022, FRA denied BNSF’s request to expand its existing waiver, as well as NS’ request to begin an ATI waiver that had been submitted a year earlier. BNSF has challenged FRA’s decision to deny its request to expand the existing waiver in a federal appeals court, while NS filed a petition for reconsideration with FRA of the agency’s decision to deny its initial waiver requests. Both matters remain pending.

The nation’s railroads put technology to work every day. Here are just six innovations railroads have deployed to maximize the safety and efficiency of the nearly 140,000-mile rail network.


Track geometry cars measure every inch of track

Freight railroads use track geometry cars to identify anomalies in train tracks. The cars travel along the tracks measuring every foot for rail-wear, track alignment, elevation in curves, gauge (distance between rails) and many other track geometry measurements.

After the initial survey is complete, railroads quickly respond to any issues, keeping small problems from becoming big ones. Asim Ghanchi, AVP of Enterprise Services s at BNSF, says that track geometry cars — including its autonomous fleet — allow BNSF to measure over 300,000 miles of track each year. “Inspecting that much track, that often, would be impossible without technology,” Ghanchi says.

BNSF also uses machine learning technology to analyze data collected by track geometry cars, which allows them to predict track problems that may occur over the next 30 days. This flexibility means the railroad can complete maintenance at an ideal time, which maximizes safety and network efficiency.


Sonar helps protect bridge piers.

Railroads use sonar to assess the stability of bridge piers. Sonar identifies increased erosion around the piers, which can compromise a bridge’s integrity.

The sonar technology railroads use is similar to the echolocation whales use to understand their surroundings. Sonar sends out sound waves, which bounce off the bridge piers and the ground surface below the water. Then, based on the nature of the echo, railroads determine whether there are any concerns with the stability of the bridge piers.

Railroads use sonar to assess bridges when significant water flow occurs following big storms or flooding events.  This is especially useful when the water is extremely murky, making it difficult for a human diver to evaluate — or even see — the piers.

“With sonar, we have a better sense of what’s going on underwater,” says Kevin Day, former General Manager of Field Technology and Data Analytics at Canadian National. “And divers don’t have to enter challenging and unsafe water conditions.”


Smart sensors keep wheels turning.

Smart sensors placed alongside track use a host of technologies — such as infrared and lasers — to assess the strength and health of wheels and bearings as they travel across the nation’s rail network.

Overheated wheel bearings can lead to train derailments, so railroads use hotbox detectors to measure the temperature of bearings. When a bearing gets too hot, it can only safely travel another five to 100 miles.

CPKC uses acoustic bearing detectors to predict when bearings will overheat three months in advance of them actually overheating. These sensors use acoustic signatures to evaluate the sound bearings make.

By combining this data with the data collected by hotbox detectors, CPKC can find patterns in the acoustic bearing detector data that indicate when bearings could overheat. “By paying attention to the acoustic bearing detectors, we can make sure our bearings never get too hot,” says Kyle Mulligan, an AVP of Operations Technology at CPKC. “Technology makes us safer and more efficient. It protects our infrastructure.”


Locomotive simulators safely train engineers.

As a supplement to required field training, CSX uses tabletop locomotive simulators to train engineers on Positive Train Control (PTC), a set of innovative technologies that automatically monitor the safe operation of a train and prevent certain kinds of human-factor incidents.

Engineers virtually learn train handling procedures on different parts of the track, seeing, for instance, how going down an incline will increase speed. They can also experience how the PTC system initiates by constantly assessing a large number of variables to guarantee the train has the necessary time and space to come to a stop safely where necessary to do so along the route.

To create the simulator, CSX used a helicopter equipped with advanced imaging technology to capture detail about routes, including curves, elevation, track speed and even the location of buildings and overpasses along the track. “It’s very realistic,” says Patrick Barnett, Technical Director of CSX. “Our engineers really feel like they’re in the train’s cab, on the route.”


Big Data makes railroads safer and more efficient.

Railroads use machine learning to predict a number of maintenance issues — such as track wear and tear — based on patterns and trends found in huge amounts of data.

“It’s a lot like when your phone guesses what word you’re going to use next in a text message,” says Mabby Amouie, Norfolk Southern’s AVP of Enterprise Data and Analytics. “By analyzing patterns, we can predict the rail’s wear and tear over time.”

Using models and algorithms powered by machine learning and artificial intelligence, Norfolk Southern can predict the wear and tear of track over a five-year period with a high degree of confidence. This five-year look-ahead window allows the railroad to proactively plan repairs and maintenance, helping make its network safer and more efficient.

Track wear is only one of several different use cases for which Norfolk Southern has developed models to proactively leverage big data. And with so much data at its disposal, Norfolk Southern foresees many more exciting big-data applications on the horizon.


Machine Visioning

With machine visioning technology, Union Pacific collects 40,000 images per second of trains passing on tracks. A series of algorithms then analyze the images to identify any anomalies, allowing Union Pacific to address issues faster than they could with manual inspections alone.

The technology helps railroads look at many elements all at once, providing a comprehensive view of locomotives, trains and their components. Union Pacific uses machine visioning in Nebraska, Iowa and Arkansas and is exploring where to deploy it next.