A travel condition network information generation system includes: a travel condition output unit provided on the transport, and outputting a piece of travel condition data responsive to a travel condition of the transport; and a controller generating, based on a plurality of pieces of travel condition data, a plurality of pieces of divided travel condition information responsive to divided travel paths obtained by dividing a plurality of travel paths, and generating, based on the plurality of pieces of divided travel condition information, the travel condition network information corresponding to the travel path network of the transport.

A method is provided that may include obtaining image data related to a route from a imaging device associated with a vehicle. The method may also include determining an environmental condition based on the image data, and operating the vehicle or communicating an alert signal based on the environmental condition that is determined.

Techniques for injecting a vehicle into a high speed transportation system are described. A travel request is received from a user. The user is determined to be authorized to travel using the high speed transportation system, based on a profile associated with the user. An injection portal for the user to enter the transportation system is identified. One or more instructions for the user are provided, relating to the injection portal. A vehicle associated with the user is identified at the injection portal. Characteristics of the vehicle are sensed at the injection portal, including a center of gravity of the vehicle. The characteristics are determined to satisfy threshold values, and the vehicle is authorized for travel in the transportation system. A vehicle profile is generated. The vehicle profile is transmitted to a second controller associated with the transportation system. The vehicle is injected into the transportation system.

A roadside unit 40 that controls a traffic safety apparatus provided at a railroad crossing 150 at which a general road 120 on which a vehicle 20 travels and a railroad track 110 on which a railroad vehicle 10 given priority over the vehicle 20 travels intersect receives a first message from the railroad vehicle 10. The first message includes an information element indicating a railroad vehicle as a type of a transmission source vehicle, and an information element indicating at least one of a position of the railroad vehicle 10 or speed of the railroad vehicle 10. In the roadside unit 40, a communicator transmits a second message to the vehicle 20. The second message includes an information element related to waiting time for passing of the railroad vehicle 10 through the railroad crossing 150.

The present disclosure relates to a train identification system and method, and a train safety inspection system and method. The train identification system includes: a remote detection component, configured to acquire overall feature information of an inspected train through remote monitoring; and an identification device, configured to determine at least one of a type and a traveling situation of the inspected train according to the acquired overall feature information.

A health early warning system for passengers on a train in an outdoor air polluted environment and a method thereof are provided. The system comprises an air quality monitoring station data acquisition module, a train data acquisition module, a train air pollution prediction module, and a train air environment early warning module; the air quality monitoring station data acquisition module acquires data of air quality monitoring stations and uploads the data to the train air pollution prediction module; the train data acquisition module acquires data of the train and uploads the data to the train air pollution prediction module; the train air pollution prediction module performs short-term prediction on air pollution of the train and uploads a result of the short-term prediction to the train air environment early warning module; and the train air environment early warning module performs early warning on the health of the passengers on the train.

Systems and methods for railway asset management. The methods comprise: using a virtual reality device to recognize and collect real world information about railway assets located in a railyard; and using the real world information to (i) associate a railway asset to a data collection unit, (ii) provide an individual with an augmented reality experience associated with the railyard and/or (iii) facilitate automated railyard management tasks.

Managing passenger flows is an important issue in modern buildings. Particularly in high buildings there will be a lot of people arriving and leaving typically through one access floor. When passenger flows are not managed and passengers are not instructed facilities of buildings are not in optimal use. People may be queuing for one elevator group when another elevator group is not used in full capacity. This can be improved by using an access gate arrangement where the controller of the access gate arrangement receives information from external systems in the building.

A machine learning system for maintaining distributed computer control systems for a train may include a data acquisition hub communicatively connected to a plurality of sensors configured to acquire real-time configuration data from one or more of the computer control systems. The machine learning system may also include an analytics server communicatively connected to the data acquisition hub. The analytics server may include a virtual system modeling engine configured to model an actual train control system comprising the distributed computer control systems, a virtual system model database configured to store one or more virtual system models of the distributed computer control systems, wherein each of the one or more virtual system models includes preset configuration settings for the distributed computer control systems, and a machine learning engine configured to monitor the real-time configuration data and the preset configuration settings. The machine learning engine may warn when there is a difference between the real-time configuration data and the preset configuration settings, the difference being indicative of at least two of the distributed computer control systems being out of synchronization by more than a threshold deviation.

A machine learning system for maintaining distributed computer control systems for a train may include a data acquisition hub communicatively connected to a plurality of sensors configured to acquire real-time configuration data from one or more of the computer control systems. The machine learning system may also include an analytics server communicatively connected to the data acquisition hub. The analytics server may include a virtual system modeling engine configured to model an actual train control system comprising the distributed computer control systems, a virtual system model database configured to store one or more virtual system models of the distributed computer control systems, wherein each of the one or more virtual system models includes preset configuration settings for the distributed computer control systems, and a machine learning engine configured to monitor the real-time configuration data and the preset configuration settings. The machine learning engine may warn when there is a difference between the real-time configuration data and the preset configuration settings, the difference being indicative of at least two of the distributed computer control systems being out of synchronization by more than a threshold deviation.