A locomotive system is provided that includes a platform, plural wheel-axle sets operably coupled to the platform, a reservoir attached to the platform and configured to hold a fluid, and a resonant sensor probe assembly coupled to the reservoir. The sensor probe assembly includes a substrate formed from one or more dielectric materials and free-standing electrodes coupled with the substrate. The free-standing electrodes are configured to be placed into the fluid, to generate an electric field between the free-standing electrodes, and to measure an impedance response of the sensor to the fluid between the electrodes.

A train control system uses machine learning for implementing handovers between centralized and distributed train control models. A machine learning engine receives training data from a data acquisition hub, receives a centralized train control model from a centralized virtual system modeling engine, and receives an edge-based train control model from an edge-based virtual system modeling engine. The machine learning engine trains a learning system using the training data to enable the machine learning engine to predict when a locomotive of the train will enter a geo-fence where communication between the edge-based computer processing system and the centralized computer processing system will be inhibited.

A train control system controls the ramp rate at which a train accelerates after braking. A machine learning engine receives training data from a data acquisition hub, including a plurality of input conditions of the train and a plurality of outputs associated with the input conditions. A virtual system modeling engine simulates in-train forces and train operational characteristics using physics-based equations, kinematic or dynamic modeling of behavior of the train or components of the train during operation of the train when the train is accelerating after braking, and inputs derived from stored historical contextual data related to the train. The machine learning engine trains a learning system using the training data to generate an output based on an input using a learning function including at least one learning parameter. The learning parameter is modified as needed to improve the accuracy of the learning function in generating the output.

A train-to-train warning system and method for communicating an information notification, may include receiving or sensing, by a head of train computer of a listener train, an information notification originating from an end of train device associated with a first train in a geographic area, identifying the first train based on at least one of the position of the first train or the identifier associated with the first train, determining, one or more events or conditions of the first train in the track network based on the information notification, generating an updated operation of the listener train including one or more actions, the updated operation based on the one or more events or conditions associated with the first train, and controlling a movement of the listener train based on at least one of the one or more actions.

A signal aspect enforcement method for a rail vehicle includes determining if vehicle position is unknown. The system determines if rail vehicle speed is less than a line-of-sight threshold speed. The system determines the grade of the rail. A worst-case braking distance of rail vehicle is calculated. The signal aspect is determined using a camera system and a beacon system. The system determines if the signal aspect determined by camera system is same as signal aspect determined by beacon system and, if so, determines the route of rail vehicle and speed limit of rail vehicle.

A system for path control for a mobile unmanned vehicle in an environment is provided. The system includes: a sensor connected to the mobile unmanned vehicle; the mobile unmanned vehicle configured to initiate a first fail-safe routine responsive to detection of an object in a first sensor region adjacent to the sensor; and a processor connected to the mobile unmanned vehicle. The processor is configured to: generate a current path based on a map of the environment; based on the current path, issue velocity commands to cause the mobile unmanned vehicle to execute the current path; responsive to detection of an obstacle in a second sensor region, initiate a second fail-safe routine in the mobile unmanned vehicle to avoid entry of the obstacle into the first sensor region and initiation of the first fail-safe routine.

A method and a system for transmitting enforceable instructions in a vehicle control (VC) system includes receiving, by a cyclic redundancy check (CRC) calculator, at least one enforceable instruction from vehicle systems. The CRC calculator calculates at least one enforceable instruction CRC based at least partly on the at least one enforceable instruction and transmits the at least one enforceable instruction CRC to a back office server of the VC system and/or an on-board system of a vehicle. Methods for cyclic redundancy check (CRC) hazard mitigation in a vehicle control (VC) system and verifying enforceable instruction data on-board a vehicle are also disclosed.

A method for determining the position of a track-guided vehicle, in particular a rail vehicle, includes readjusting a distance measuring device on the vehicle for obtaining position-determining distance measurement values based on position marker information available at position markers on the track, wherein the position marker information is captured by a position marker information recorder connected to the distance measuring device. In order to be able to carry out an exact determination of the position of a track-guided vehicle in a comparatively simple way, the position marker information of the same position marker is detected again by a further position marker information recorder being offset relative to the first position marker information recorder in the longitudinal direction of the vehicle and a generation of further position-determining distance measurement values is initiated. A positioning device for determining the position of a track-guided vehicle is also provided.

A DC feeder voltage computing device includes a model information storing unit, a run history information storing unit, and a voltage setting value computing unit. The model information storing unit stores model information. The run history information storing unit stores, on a per train basis, run history information that indicates locations and power situations of a plurality of trains that run in a DC-electrified section on or before a preceding day. The voltage setting value computing unit computes, on the basis of the model information and the run history information, a voltage setting value for controlling a substation voltage to cause an amount of power consumption in the DC-electrified section to satisfy a preset condition.

An onboard system includes two control parts. Each of the two control parts has the function of performing a first process for controlling the travel of the transport vehicle. In a period during which a first control part being one control part out of the two control parts is performing the first process, a second control part being other control part out of the two control parts does not perform the first process. In the period during which the first control part is performing the first process, the second control part performs a maintenance process for performing maintenance of the transport vehicle.