Methods and systems for determining a status of retarder devices in a classification yard. In particular embodiments, a set of car event data associated with a retarder may be analyzed to determine the ability of the retarder to efficiently remove energy from cuts traveling over the retarder throughout the length of the retarder. A status of the retarder may be determined from analysis of the ability of the retarder to efficiently remove energy from cuts traveling over the retarder throughout the length of the retarder. In embodiments, the status of the retarder may be used to ensure corrective actions on the retarder (e.g., deploy maintenance personnel, report the status of the retarder, send a control signal to the retarder to deactivate, etc.).

Methods and systems for determining a status of hardware devices in a classification yard. In particular embodiments, a set of device event data associated with a hardware device may be analyzed to determine the performance of the hardware device during operations of each device event. A status of the hardware device may be determined from the analysis of the performance of the hardware device during operations of each device event. In embodiments, the analysis may include thresholding analysis that may be configured to determine a relationship between real-world measurements and expected (e.g., predicted or desired) results for each device event associated with the hardware device. In embodiments, the status of the hardware device may be used to ensure corrective actions on the hardware device (e.g., deploy maintenance personnel, report the status of the hardware device, send a control signal to the hardware device to deactivate, etc.).

Methods and systems for determining a status of switch devices in a classification yard. In particular embodiments, a set of switch event data associated with a switch may be analyzed to determine the performance of the switch during operations of each switch event. A status of the switch may be determined from the analysis of the performance of the switch during operations of each switch event. In embodiments, the analysis may include thresholding analysis that may be configured to determine a relationship (e.g., a deviation relationship) between real-world measurements during the switch events and expected measurements during the switch events for each switch event associated with the switch. In embodiments, the status of the switch may be used to ensure corrective action is taken on the switch (e.g., deploy maintenance personnel, report the status of the switch, send a control signal to the switch to deactivate, etc.).

Methods and systems for managing operations of a classification yard. In embodiments a release speed, coupling speed, and/or a predicted speed at one or more points of a route along which a cut is being routed is determined. A set of event messages of events that occurred during the traveling of the cut is generated. Real-world measurements associated with an actual speed of the cut at the one or more points of the route are obtained. Coefficients associated with the predicted speed of the cut at the one or more points are autotuned based on the real-world measurements, a status of one or more devices used to route the cut is determined based, at least in part, on thresholding analysis applied to the real-world measurements, and the set of event messages is stored in an event log for subsequent replaying in a graphical user interface (GUI).

Methods and systems providing predictive models for estimating tuning coefficients for automatically tuning operations of a classification yard. In embodiments, a set of predictions for car events at a segment or device may be generated using a current set of tuning coefficients for the segment or device. Real-world data related to the car events at the segment or device may be compiled, and a set of candidate tuning coefficients may be generated for the segment or device based on application of a predictive model to the real-world data. The segment or device may be automatically tuned based on a comparison of the set of candidate tuning coefficients and current set of tuning coefficients to the real-world data to determine which of the set of candidate tuning coefficients and the current set of tuning coefficients yields more accurate results for cuts passing the segment or device.

A method for controlling vehicle parking, includes: obtaining, by a processor, a current vehicle speed and a current vehicle control level of a vehicle; obtaining, by the processor, a target vehicle speed of the vehicle, and obtaining a target vehicle control level of the vehicle according to the current vehicle control level; obtaining, by the processor, a first vehicle control level according to the current vehicle speed, the target vehicle speed, the current vehicle control level, and the target vehicle control level; and controlling, by the processor, the vehicle to run according to the first vehicle control level.

Methods and systems for selection of a control speed for a remote-controlled vehicle based on rulesets applied to control nodes within a viewing window. In embodiments, a viewing window including control nodes, each having a having ruleset defining operating conditions associated therewith, may be determined. The ruleset for a control node may define operating limitations (e.g., speed limitations, orientation limitations, etc.) at the control node. In embodiments, a control speed plan for the viewing window may be generated based on the operating conditions for each control node within the current viewing window based on the limitations associated with each control node. The control speed plan may include an optimal control speed at each control node within the viewing window and a speed profile indicating an acceleration or deceleration curve to be followed through each of the optimal control speeds in the control speed plan when executing the control speed plan.

A computer-implemented method for allocating railcars in a rail yard based upon analysis of contents of the railcars is disclosed. The method includes generating, via a LiDAR sensor, images of the railcars. A network interface sends the images of the railcars to an analysis unit. The analysis unit analyzes the images of the railcars. Based on the analysis, the analysis unit determines a contents status for each of the railcars. A notification module transmits notifications to at least one of the mobile computing devices, where each of the notifications include at least one of: railcar contents statuses or images of the railcars. In response to the transmitting of the at least one notification, the railcars are sorted to different locations via at least one of the plurality of rail yard workers, where each of the different locations are based on a railcar contents status.

A computer-implemented method for allocating railcars in a rail yard based upon analysis of contents of the railcars is disclosed. The method includes generating, via a LiDAR sensor, images of the railcars. A network interface sends the images of the railcars to an analysis unit. The analysis unit analyzes the images of the railcars. Based on the analysis, the analysis unit determines a contents status for each of the railcars. A notification module transmits notifications to at least one of the mobile computing devices, where each of the notifications include at least one of: railcar contents statuses or images of the railcars. In response to the transmitting of the at least one notification, the railcars are sorted to different locations via at least one of the plurality of rail yard workers, where each of the different locations are based on a railcar contents status.

The train detection system comprises a wireless communication network further comprising train detection modules attached to catenary poles at the entrance and exit of the railyard. Each train detection module is equipped with a plurality of diverse sensors configured to detect trains and other on-track vehicles. The diverse sensors are simultaneously active and work together for detecting an approaching or leaving train. The train detection modules generate train alerts which are transmitted wirelessly over the wireless communication network. Each of the railyard workers wears a personal alert device capable of wirelessly connecting with the train detection modules and receiving the train alerts over the said wireless communication network. The train alert modules are capable of transmitting alerts wirelessly to personal alert devices and other train alert modules. Train alert modules are capable of generating audio visual warnings for any personnel which may not be equipped with personal alert module.