A communication structure including a first track system and a second track system including a first and second microprocessor and first and second control circuitry is provided. The control circuitry is configured to determine an inbound train on one of the track systems. The first and second control circuitry may be configured to communicate the inbound train on the corresponding track to the other control circuitry. The first and second microprocessor may be configured to communicate with one another. At least one of the first microprocessor and the second microprocessor may be configured to determine whether a first activation of warning devices is needed at a grade crossing and communicate the first activation to the other microprocessor. At least one of the first microprocessor and the second microprocessor may be configured to determine a second sustained activation of the warning devices and communicate the first activation to the other microprocessor.

A crossing gate mechanism includes an electric motor with one or more sensor(s), a crossing gate arm operated via the electric motor, and a controller configured to control the electric motor to raise or lower the crossing gate arm in response to a gate control signal. The controller is further configured to sense a motion of the crossing gate arm and detect an obstruction that prevents the crossing gate arm to execute the motion. Further, an associated method and non-transitory computer readable medium are described.

A method monitors a railroad-crossing. A track system area of which, which can be traveled by rail vehicles, and can be traversed by objects along a passing direction. Accordingly, provision is made for a first protection area located in front of the track system area along the passing direction to be monitored for passing events, for a second protection area located behind the track system area along the passing direction to be monitored for passing events, and for at least one warning signal to be generated if the identified passing events are implausible according to at least one predetermined plausibility check.

A system and method can include determining a location of a locating device disposed onboard a vehicle system, identify a size of the vehicle system, calculate a duration that the vehicle system has been blocking or will be blocking an intersection between at least two intersecting routes based at least in part on the location of the locating device and on the size of the multi-vehicle system, and implement one or more responsive actions to clear the intersection responsive to the calculation of the duration. Optionally, the system and method can predict or forecast whether a vehicle system approaching or moving through the intersection will come to a stop in a locking that blocks the intersection, and implement one or more responsive actions.

In one embodiment, a method includes capturing, by a machine vision device, an image of an object in a railway environment. The machine vision device is attached to a first train car that is moving in a first direction along a first railroad track of the railway environment. The method also includes analyzing, by the machine vision device, the image of the object using one or more machine vision algorithms to determine a value associated with the object. The method further includes determining, by the machine vision device, that the value associated with the object indicates a potential deficiency of the object and communicating, by the machine vision device, an alert to a component external to the first train car. The alert comprises an indication of the potential deficiency of the object.

Provided are a surveillance system, an information processing device, a fall detection method, and a non-transitory computer readable medium capable of improving the accuracy of detecting a person who has fallen down in a railroad crossing. A surveillance system according to the present disclosure includes a LiDAR sensor (10) that emits a plurality of laser beams with different ranges to a surveillance area, and outputs a detection signal indicating a detection status of an object by each of the laser beams, and an information processing device (20) that determines that the object has fallen down when the detection status by a laser beam with a shorter range than a predetermined range indicates that the object is detected and the number of laser beams detecting the object decreases.

Disclosed herein is a motorized railway safety cart, comprising a) a chassis adapted with rail-guided carriages configured to travel along rails, and interconnected by a base frame, b) a driving unit for driving wheels attached to at least one of said rail-guided carriages, c) a control module for controlling the operation of said motorized railway safety cart, and d) a communication module, said cart is configured to automatically travel along a railway track to a designated location thereof and is further configured with one or more safety measures for performing safety tasks thereat, such as alerting or triggering preventive measures that can restrict passage into a predefined track work zone. Also disclosed herein is a deployment system that facilitates a remotely controlled deployment of said motorized railway safety cart.

Provided are a surveillance system, an information processing device, a fall detection method, and a non-transitory computer readable medium capable of improving the accuracy of detecting a person who has fallen down in a railroad crossing. A surveillance system according to the present disclosure includes a LiDAR sensor (10) that emits a plurality of laser beams with different ranges to a surveillance area, and outputs a detection signal indicating a detection status of an object by each of the laser beams, and an information processing device (20) that determines that the object has fallen down when the detection status by a laser beam with a shorter range than a predetermined range indicates that the object is detected and the number of laser beams detecting the object decreases.

In one embodiment, a method includes capturing, by a machine vision device, an image of an object in a railway environment. The machine vision device is attached to a first train car that is moving in a first direction along a first railroad track of the railway environment. The method also includes analyzing, by the machine vision device, the image of the object using one or more machine vision algorithms to determine a value associated with the object. The method further includes determining, by the machine vision device, that the value associated with the object indicates a potential deficiency of the object and communicating, by the machine vision device, an alert to a component external to the first train car. The alert comprises an indication of the potential deficiency of the object.