A traffic control system includes at least one traffic signal, an aircraft and a ground control station. The aircraft includes a position sensor and a wireless communication device. The ground control station includes an electronic controller and a wireless communication device. The electronic controller is configured to control the at least one traffic signal based on at least one of position data of the aircraft and direction data of the aircraft.

A system for assisting a maneuver of a moving object is provided. The system includes a plurality of unmanned aerial vehicles, and a computing device comprising a controller configured to: identify a maneuver location of the moving object based on location information associated with the moving object, determine one or more unmanned aerial vehicles among the plurality of unmanned aerial vehicles based on a proximity of the maneuver location and the plurality of unmanned aerial vehicles, dispatch the one or more unmanned aerial vehicles to the maneuver location, and transmit an instruction signal to the one or more unmanned aerial vehicles, wherein the instruction signal causes the one or more unmanned aerial vehicles to generate an indication configured to assist one or more vehicles approaching the maneuver location.

A vehicle includes: a vehicle sensor configured to sense surroundings; a communication device configured to communicate with a telematics service server; and a controller configured to carry an unmanned aerial apparatus which is a collaboration object transmitted from the telematics service server. In particular, the controller controls the vehicle to move in collaboration with the unmanned aerial apparatus.

A vehicle includes: a vehicle sensor configured to sense surroundings; a communication device configured to communicate with a telematics service server; and a controller configured to carry an unmanned aerial apparatus which is a collaboration object transmitted from the telematics service server. In particular, the controller controls the vehicle to move in collaboration with the unmanned aerial apparatus.

In one embodiment, a micromobility transit vehicle may include a steering assembly. The steering assembly may include a steer tube configured to rotate within a headtube of the micromobility transit vehicle, and a stiffening brace positioned about the headtube. A stem may be coupled to the steer tube and the stiffening brace and configured to rotationally lock the stem and the stiffening brace together. A preload assembly may be coupled to the steering assembly and the stem and configured to adjust a preload of the steering assembly.

A method and system for tracking the real-time positions of airport ground vehicles, and integrating the positional data into the Automatic Dependent Surveillance-Broadcast (ADS-B) network infrastructure. The system may include one or more ground receiver stations that receives positional telemetry data from one or more airport ground vehicles, and transmits the ground vehicle positional data to a centralized ground base station. A computer system connected to the ground base aggregates the ground vehicle telemetry data from one or more ground vehicles, converts the aggregate telemetry data into an ADS-B compatible data protocol, and integrates that data into the ADS-B network infrastructure for dissemination and reporting across the ADS-B network. The method enables the use of and dissemination of ADS-B information for ground vehicles without the need for ADS-B transponders on each ground vehicle.

A method and system for tracking the real-time positions of airport ground vehicles, and integrating the positional data into the Automatic Dependent Surveillance-Broadcast (ADS-B) network infrastructure. The system may include one or more ground receiver stations that receives positional telemetry data from one or more airport ground vehicles, and transmits the ground vehicle positional data to a centralized ground base station. A computer system connected to the ground base aggregates the ground vehicle telemetry data from one or more ground vehicles, converts the aggregate telemetry data into an ADS-B compatible data protocol, and integrates that data into the ADS-B network infrastructure for dissemination and reporting across the ADS-B network. The method enables the use of and dissemination of ADS-B information for ground vehicles without the need for ADS-B transponders on each ground vehicle.

Unmanned aerial vehicles and related methods and systems are disclosed. An example unmanned aerial vehicle, comprising: a body and a propulsion source to propel the unmanned aerial vehicle during flight; and a display carried by the unmanned aerial vehicle to display a message to coordinate traffic, the display actuatable between a deployed position to enable the message to be conveyed and a stowed position in which aerodynamics of the unmanned aerial vehicle are enhanced.

A congestion management apparatus includes a memory configured to store, on a per-action-option basis, upper limits on numbers of users allowed to be guided to action options, and a processor coupled to the memory and configured to: generate the action options by time slot for a user; calculate for each of the generated action options, choice probabilities of the action options with respect to the user, and store the calculated choice probabilities in the memory; and calculate for each of the action options, estimated numbers of previous users assumed to have selected the action options, based on choice probabilities of each of the action options with respect to the previous users, the choice probabilities being obtained from the memory, wherein the processor is configured to extract, based on the upper limits and the estimated numbers for the action options, action options to be presented to the user.

A congestion management apparatus includes a memory configured to store, on a per-action-option basis, upper limits on numbers of users allowed to be guided to action options, and a processor coupled to the memory and configured to: generate the action options by time slot for a user; calculate for each of the generated action options, choice probabilities of the action options with respect to the user, and store the calculated choice probabilities in the memory; and calculate for each of the action options, estimated numbers of previous users assumed to have selected the action options, based on choice probabilities of each of the action options with respect to the previous users, the choice probabilities being obtained from the memory, wherein the processor is configured to extract, based on the upper limits and the estimated numbers for the action options, action options to be presented to the user.