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RailBot Extention of Railroad Positve Train Control Capabilites Disclosure Number: IPCOM000250013D
Publication Date: 2017-May-16
Document File: 5 page(s) / 100K

Publishing Venue

The Prior Art Database

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RailBot Extension of Railroad Positive Train Control Capabilities

Disclosed is a system and method for preventing train accidents utilizing an autonomous rail

droid (RailBot).

Disclosed is a system and method for preventing train accidents utilizing an autonomous rail

droid (RailBot). Railroad accidents can be extremely disruptive, expensive, and even deadly.

Railroad safety technology has improved over the years. Some of the latest advancements

include technology innovations such as Positive Train Control (PTC) that can automatically take

action independent of the engineer to prevent accidents. A key objective of PTC regulation was

to unify a disparate group of safety technologies under a common set of standards. The second

was a set of core objectives defining the functionality of a PTC system that must prevent:

• Train-to-train collisions

• Over-speed derailments

• Incursions into established work zone limits

• Movement of a train through an improperly aligned wayside switch

PTC and other approaches will improve safety when implemented, help prevent accidents, and

save lives. Nevertheless, close scrutiny of the primary causes of rail accidents reveals the current

strategy will be ineffective at preventing accidents associated with the most prevalent problems.

PTC is intended as a back-up system that will alert and then take action independent of the

engineer when necessary. If, for example, the operating speed is too high for the track

configuration that the train is approaching, it can automatically and proactively decelerate the

train. The PTC system will first warn the engineer, but if no action is taken to address the issue,

the PTC system will initiate a braking event. Implementation of PTC involves instrumenting

trains and tracks with sensors, communication systems, and computer systems that prevent

accidents. On-board train sensors can effectively detect issues with the train components such as

wheels and bearing problems. Unfortunately, on-board train sensors do not detect all issues such

as track obstruction or damaged rails which are the more prevalent types of problems that cause

accidents. For example; “Broken rails or welds”, which account for the largest percentage of the

train accidents, cannot be detected in advance by on-board train sensors. Wayside track sensors

used with PTC have proven problematic too. These types of sensors cannot directly detect issues

like broken rails so they instead attempt to indirectly detect problems by measuring second-order

effects such as unusual vibration or temperature changes as an indicator of a potential problem

(e.g., a broken rail). However, this approach tends to produce a good number of false positives

resulting in unnecessary main train braking when there is no real problem. Another significant

challenge to PTC implementation is sheer magnitude of the track sensor data that needs to be

communicated back to processing centers for analysis for more than 100,000 miles of Class-1