A system for enhancing personnel safety on a railroad track is presented. The system can receive data from sensors and/or a PTC system to determine positions of clients/worker and/or vehicles, and further utilize such data to determine if a vehicle is within a certain proximity of the client/worker location. The system can further generate geofences around clients/vehicles to and determine when such geofences intersect one another. Additionally, the present disclosure can assign severity levels and generate alerts with the assigned severity levels, and such severity levels can indicate how close a vehicle is to a particular location. It is an object of the invention to provide a system for generating alerts to notify personnel when they much retreat to a place of safety.

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.

A speed control and track change detection device for railways is characterised in that it comprises three high-frequency radar sensors located at the vertices of an imaginary triangle and a digital processing device for processing the signals detected by the radars, wherein in the case of the speed control system, both sensors are located at 1 m distance from each other along the axis of the path of the railway and inspect the ground of the infrastructure 2 cm away from the outside of each rail, and according to the temporal offset of the signals obtained the digital processing device estimates the exact speed of the train.

A system for the geolocation of vehicles traveling on a guideway comprises the vehicles and markers distributed episodically along the guideway. The vehicles are equipped with a sensor for detecting a physical characteristic of the markers, and a computer for supplying location information as a function of signals delivered by the sensor. The computer stores a database comprising a recording of the distribution of the markers on the guideway. The markers having a physical characteristic detectable by the sensors. The markers each belong to one and only one class among a plurality of classes of physical objects, and the physical characteristic of all the markers of a class have the same property during detection by one of the sensors. The markers are randomly distributed on the guideway, with an ordered recording of the class to which each of the markers arranged on the guideway is stored in the database. Each of the recordings is associated with location information relative to the physical position of the marker on the guideway.

A vehicle-position monitoring system includes liquid-capacitive inclinometer sensor, configured to provide a measurement of grade (θ.sub.grade) of a surface over which a vehicle travels, and an accelerometer to measure acceleration of the vehicle along a principal axis (a.sub.x) of the vehicle along the surface. Direct measurement of the grade (θ.sub.grade) provides a position-tracking system with accurate information to extract acceleration due to motoring and braking (a.sub.MB) from acceleration experienced along the principal axis and track vehicle position without regard to wheel diameter calibration.

A method is provided that may include obtaining image data from vision sensors disposed onboard a vehicle. The method may include determining a stopping distance of the vehicle based at least in part on the image data using an artificial intelligence (AI) neural network having artificial neurons arranged in layers and connected with each other by connections. A moving speed and a speed limit of the vehicle may be determined using the AI neural network. The method may control movement of the vehicle using the AI neural network by enforcing movement authorities preventing unwarranted movement of the vehicle based on a difference between the moving speed and the speed limit. The method may include receiving feedback regarding the stopping distance and the speed limit calculated by the artificial neurons and training the AI neural network by changing connections between the artificial neurons based on the feedback received.

The embodiments of the present application provide a method and apparatus for tracking and controlling virtual marshalling trains, an electronic device, and a readable storage medium, which is intended to balance the running safety and the utilization of the railway resources. In the present application, the running state data of the target train is obtained, the target control operation corresponding to the running state data is determined from the plurality of preset control operations based on the preset reinforcement learning model, and the control of the target train is implemented according to the target control operation. In addition, the reward value corresponding to the previous control operation of the target control operation is determined according to the distance contained in the running state data, and the reinforcement learning model is updated according to the reward value.

A measurement method includes: generating first measurement data based on observation data of an observation point of a structure; generating second measurement data by performing filter processing on the first measurement data; calculating a first deflection amount of the structure; calculating a second deflection amount by performing filter processing on the first deflection amount; approximating the second measurement data with a linear function of the second deflection amount to calculate a first-order coefficient and a zero-order coefficient; calculating a third deflection amount based on the first-order coefficient, the zero-order coefficient, and the second deflection amount; calculating an offset based on the zero-order coefficient, the second deflection amount, and the third deflection amount; and calculating a static response by adding the offset and a product of the first-order coefficient and the first deflection amount.

Systems and methods are provided for decentralized rail signaling and positive train control. A decentralized train control system may include a plurality of wayside units, configured for placement on or near tracks in a railway network, and one or more train-mounted units, each configured for use in a train operating in a railway network that support use of the decentralized train control system. Each train-mounted unit may configured to receive communicate with any wayside unit and/or train-mounted unit that comes within range, with the communicating including use of ultra-wideband (UWB) signals, and for generating control information based on the UWB signals, for use in controlling one or more functions associated with operation of the train.

A ride system includes a ride vehicle and an external sensor assembly disposed along a ride path and configured to measure external parameters. The ride vehicle includes an internal sensor assembly configured to measure internal parameters, a chassis, a cabin, and a motion base disposed between the chassis and the cabin, such that the motion base includes a turntable and a plurality of actuators. The ride vehicle also includes a controller that instructs (i) the turntable to rotate and (ii) the plurality of actuators to rotate, extend, or retract, to control six or more degree-of-freedom (DOF) motion of the cabin relative to the chassis, such that the controller is configured to instruct the turntable and the plurality of actuators based on the external parameters, the internal parameters, or both.