A system for detection and identification of objects and obstacles near, between or on railway comprise several forward-looking imagers adapted to cover each different range forward and preferably to be sensitive each to different wavelength of radiation, including visible light, LWIR, and SWIR. The substantially homogeneous temperature along the rail the image of which is included in an imager frame assists in identifying and distinguishing the rail from the background. Image processing is applied to define living creature in the image frame and to distinguish from a man-made object based on temperature of the body. Electro optic sensors (e.g. thermal infrared imaging sensor and visible band imaging sensor) are used to survey and monitor railway scenes in real time.

An emergency action system for use with a railcar or locomotive is described herein. The emergency action system may include a transmitter and a locomotive transceiver located within a cabin of the locomotive. The locomotive transceiver may receive a signal sent from the transmitter and may further send an emergency stop signal to a set of brakes on the locomotive to stop. The emergency stop signal may cause air to be released from the brake pipe, thereby applying the brakes and bringing the train to an immediate stop. The emergency action system enables crew members to stop a train or railcar without communication to the locomotive operator when a hazard is recognized.

A method and a system (30) for inspecting and/or mapping a railway track (18). The method comprises: acquiring geo-referenced rail geometry data associated with geometries of two rails (20) of the track along the section; acquiring geo-referenced 3D point cloud data, which includes point data corresponding to the two rails and surroundings of the track along the section; deriving track profiles of the track from the geo-referenced 3D point cloud data and the geo-referenced rail geometry data; and comparing the track profiles and generating enhanced geo-referenced rail geometry data and/or enhanced geo-referenced 3D point cloud data based on the comparison.

An object of the present invention is to provide an obstacle detection system and an obstacle detection method for a trajectory traveling vehicle, which are capable of detecting a front obstacle on a trajectory and around the trajectory with high accuracy. The system includes: a monitoring area setting processing unit that sets an obstacle monitoring area for detecting an obstacle; a front obstacle monitoring unit that monitors an obstacle in the obstacle monitoring area using a sensor that horizontally scans the front of the train; and an obstacle detection unit that detects an obstacle in the obstacle monitoring area based on a monitoring result by the front obstacle monitoring unit, in which the front obstacle monitoring unit complements a gap in a detection region of the sensor at a first position with a detection region of the sensor while the train moves from the first position to a second position.

A system and method for inspecting a railway track bed using a plurality of sensors that are synchronized for rapid interrogation of a railway track bed while the sensors are in motion at a high rate of speed.

A system and method for inspecting a railway track bed using a plurality of sensors that are synchronized for rapid interrogation of a railway track bed while the sensors are in motion at a high rate of speed.

A track data determination system including: a video camera device positioned on a vehicle to capture video data in at least one field-of-view; a geographic positioning unit associated with the vehicle to generate position data and time data; a recording device to store at least one of the following: at least a portion of the video data, at least a portion of the position data, at least a portion of the time data, or any combination thereof; and a controller to: (i) receive the video data, the position data, and/or the time data; and (ii) determine track data based at least in part upon the video data, the position data, and/or the time data. A computer-implemented track data determination method is also disclosed.

An article transport facility includes a transport vehicle and a controller, and the transport vehicle includes: a drive unit; a speed detector configured to detect a traveling speed; and a distance detector configured to detect an inter-vehicle distance, which is a distance to another transport vehicle. The controller is configured to (i) refer to at least one target speed that is set in advance according to the inter-vehicle distance, and (ii) perform an inter-vehicle adjustment control to control the drive unit in such a manner as to cause the traveling speed to approach the at least one target speed, based on the traveling speed and the inter-vehicle distance, the at least one target speed includes an accelerating target speed and a decelerating target speed, and the accelerating target speed is lower than the decelerating target speed for each inter-vehicle distance.

A method of monitoring a track using train cars includes collecting first sensor data corresponding to a track location by a first sensor network on a first train car. Based on the first sensor data, a potential track anomaly at the track location is identified by a diagnostics system on the first train car. A message describing the anomaly is transmitted to diagnostics systems located on other train cars. The message is received by a second diagnostics system on a second train car located behind the first train car. The second diagnostics system determines a time at which the second train car will be passing over track location and, at the determined time, collects second sensor data. If the track anomaly is present in both the first sensor data and the second sensor data at the track location, a train control system is notified of the track anomaly.

A positive train control may comprise a plurality of different sensors coupled to a processor that determines whether there is an anomaly of a track way, and if there is, provides an alert and/or a train control action. The plural sensors may include a visual imager, an infrared imager, a radar, a doppler radar, a laser sensor, a laser ranging device, an acoustic sensor, and/or an acoustic ranging device. Data from the plural sensors is geo-tagged and time tagged. Some embodiments of the train control employ track monitors, switch monitors and/or wayside monitors, and some employ locating devices such as GPS and inertial devices.