A method for monitoring and diagnosing components of a rail vehicle, as a singular rail vehicle or as part of a rail vehicle train consisting of a plurality of rail vehicles, with regard to the necessary repair or maintenance, as appropriate, of at least one component, in which at least one measuring device captures at least one measurement variable, which is relevant to an assessment of a necessary repair or maintenance, as appropriate, of the component, is performed in which supplementation, extension, modification or adaptation of evaluation software implemented in an evaluation device is performed based on instructions, data and/or software modules sent from a control center to the evaluation device.

A method for monitoring and diagnosing components of a rail vehicle, as a singular rail vehicle or as part of a rail vehicle train consisting of a plurality of rail vehicles, with regard to the necessary repair or maintenance, as appropriate, of at least one component, in which at least one measuring device captures at least one measurement variable, which is relevant to an assessment of a necessary repair or maintenance, as appropriate, of the component, is performed in which supplementation, extension, modification or adaptation of evaluation software implemented in an evaluation device is performed based on instructions, data and/or software modules sent from a control center to the evaluation device.

A system for nondestructive evaluation of railroad rails, includes a carriage including a plurality of wheels movably supporting the carriage on the rails, a source of vibration mounted on the carriage and connected to transmit vibrations of a preselected frequency to test regions on the rails through the wheels to cause an increase in temperature of the rails at locations of flaws in the test regions, an infrared detector for recording thermal images of the test regions to detect the increase in temperature of the location of the flaws, a controller connected to actuate the infrared detector to record the thermal images of the vibrations impacting the test regions, and store the thermal images recorded by the infrared detector.

An engineer recertification assistant that utilizes a real-time data acquisition and recording system (DARS), a DARS viewer, and a video analytics system for mobile assets. DARS includes a data recorder, an onboard data manager, and at least one local memory module. The video analytics system processes video data from at least one camera and operational data from the data recorder for critical events and regulatory requirements based on a mobile asset operator's operational performance. The processed video data and operational data is display, along with episodes, exceptions, and user comments, on a display device featuring a web portal. The engineer recertification assistant can further determine an automated score-based recommendation for certification or decertification of the mobile asset operator or can directly certify or decertify the mobile asset operator for gross non-compliance.

Systems and methods according to one or more embodiments are provided for detecting an object in a field of view of an imaging device. An object may be detected by an imaging device when the object is present along a trajectory in a target scene. In one example, a system includes a memory component to store a plurality of images of the target scene and a processor. The processor is configured to define the trajectory between two locations within the target scene and extract a subset of pixel values from each of successive images corresponding to the trajectory. The extracted subsets of pixel values are processed to detect an object within the target scene. Additional systems and methods are also provided.

A method validates an obstacle identification system. In order to be able to demonstrate that obstacles are identified by an obstacle identification system at least as reliably as by a driver, it is provided that, in order to form driving scenarios, stochastic combinations of prespecified distributions of submodules are provided. The provided combinations are subjected first, for carrying out a simulation study, to simulation by a simulator and second to automatic processing by an obstacle identification algorithm of the obstacle identification system, and a result of a simulation study, which is carried out by the simulator, and a result of the automatic processing are automatically tested for agreement.

A track monitoring system (and a method thereof) for mounting to a vehicle on a track comprising at least one rail is provided. The track monitoring system comprises a position and attitude measurement unit configured to determine a geographical position and attitude of the system during at least one pass of the vehicle on the track, a storage medium for storing track geometry data, a laser imaging and/or scanning unit configured to determine a position of the at least one rail relative to the track monitoring system, and a position of the at least one rail and surroundings relative to the track monitoring system during the at least one pass, a processor configured to determine, in the at least one pass, a first geographically referenced rail position based on the geographical position and attitude of the rail monitoring system and the position of the at least one rail relative to the system, determine, in the at least one pass, a second geographically referenced rail position based on the geographical position and attitude of the rail monitoring system and the position of the at least one rail and surroundings relative to the rail monitoring system, determine a third geographically referenced rail position based on the first and the second geographically referenced rail positions, and corresponding geographically referenced track geometry data, acquire, in a further pass, track geometry data associated with each position of the rail relative to the rail monitoring system, and the output of the position and attitude measurement unit, update, based on the third geographically referenced position of the rail, the track geometry data acquired in the further pass, and store updated track geometry data to the storage medium.

The present disclosure relates to a railway collision protection and safety system having a vehicle device located on rail vehicles at a work zone, a personal protection unit located with rail workers at the work zone, and a dispatcher processor at a control center. An authority limit within the work zone may be determined by the dispatcher processor, and an authority exceeded signal is sent to the rail vehicle when the rail vehicle is determined to exceed the authority limit.

A method for determining a location of a vehicle driving on a track is provided, the method comprising the step of obtaining a real-time image from an imaging device (100) located on the vehicle and deriving information from the obtained real-time image. The derived information is compared with a database comprising derived information from a plurality of images, each of the plurality of images being associated with a specific track segment. The closest match is then determined between a sequence of the real-time images to a sequence of the plurality of images, and the location of the vehicle on a track segment is identified based on the specific track segment associated with the closest matched sequence of images. The track segments are associated with a specific track amongst a set of parallel or closely spaced tracks.

In an example, the autonomous vehicle (“AV”) can be configured among the other vehicles and railway to communicate with a rider on a peer to peer basis to pick up the rider on demand from a location on a track, like a railway, tram or other track, rather than the rider being held hostage to a fixed railway schedule. The rider can have an application on his/her cell phone, which tracks each of the AVs, and contact them using the application on the cell phone. In an example, the AV is configured for both on-track and off track operation with different operating parameters for on-track and off track, including speed, degree of autonomy, sensors used etc.