40results about "Traffic control systems" patented technology

The invention discloses a low-altitude meteorological early warning method and system based on the Internet of Things, and relates to the technical field of low-altitude flight traffic control, and the low-altitude meteorological early warning method comprises the steps: arranging a plurality of Internet of Things sensor devices in a low-altitude flight region, and collecting meteorological data in real time, including temperature, humidity, wind speed, air pressure and the like; uploading the collected meteorological data to a cloud server by using a data transmission network; performing real-time analysis and prediction on a low-altitude meteorological condition in combination with a meteorological prediction model and historical big data; and when abnormal or potential dangerous meteorological conditions are detected, early warning information is sent to related users through multiple communication modes. According to the invention, the accuracy and timeliness of low-altitude meteorological early warning are improved, and the safety of air traffic in low-altitude flight is effectively guaranteed.

The invention relates to air route quantitative evaluation, in particular to an unmanned aerial vehicle air route dynamic quantitative evaluation method based on comprehensive risk avoidance, and the method comprises the steps: constructing a multi-dimensional air route risk quantitative evaluation system, and enabling each dimension to comprise a plurality of specific and quantifiable risk evaluation factors; mapping the observation value of each risk assessment factor into a standardized risk score; determining the weight of each risk assessment factor according to a dynamic weight adjustment strategy, and calculating a route comprehensive risk score by combining the standardized risk score of each risk assessment factor; executing the evaluation process on all the candidate paths, calculating an air route comprehensive risk score for each candidate path, preferentially recommending the candidate path with the highest air route comprehensive risk score, and generating an air route risk evaluation report at the same time; according to the technical scheme provided by the invention, the defect that accurate dynamic quantitative evaluation of the route of the unmanned aerial vehicle is difficult in the prior art can be effectively overcome.

An electronic message indicates that a materials handling vehicle is approaching an access-controlled travel path. The materials handling vehicle has a travel system that includes a normal travel mode, a limp travel mode, and a restricted travel mode. An electronic permission request is generated to enter the access-controlled travel path. Additionally, an electronic command is issued to set the travel system to the limp travel mode as the materials handling vehicle engages an entry threshold of the access-controlled travel path. A transceiver receives an electronic permission response that includes a determination of whether the access-controlled travel path is in an open state or a closed state. An electronic command then sets the travel system to the restricted travel mode when the access-controlled travel path is in the closed state, and the normal travel mode when the access-controlled travel path is in the open state.

The present invention relates to a system and method for use in navigating a vehicle within an environment, and in one particular example, to a system and method for navigation planning in an unstructured environment including unobservable features, such as negative obstacles and / or occluded regions.

Method for detecting track anomaly and associated device This method (100) comprises, in configuration, the steps of: training a neural network (110) on training tracks to predict a log-likelihood value of a track data; calculating (120) an average log-likelihood value for validation tracks and calculating (125) a median; calculating (130) a score on the average log-likelihood value of test tracks with respect to the median and calculating (135) a statistical coefficient; defining (140) an abnormality threshold from the median and the statistical coefficient.The method comprising, in inference, the steps of: acquiring (150) at least one track of interest; processing (160) the track of interest by: calculating an average log-likelihood value of the track of interest, calculating a score of the average log-likelihood value of the track of interest relative to the median; and comparing the score of the average log-likelihood value of the track of interest to the abnormality threshold, the track of interest being “abnormal” when the score of the average log-likelihood value of the track of interest is greater than the abnormality threshold, and “normal” otherwise. Figure for abstract: Figure 3.

The present invention maintains the independence of transportation service providers, and efficiently coordinates transportation services. This transportation service cooperation assistance system 1 comprises: a plurality of transportation service planning devices that manage transportation service planning information including passenger transport plans between points where passengers get on and off; and a transportation service cooperation assistance device 100, wherein the transportation service cooperation assistance device 100 executes a process for calculating passenger transport service evaluation values at a transfer point, on the basis of items of transportation service planning information received from respective transportation service planning devices and passenger movement information from each transportation service, and, if the evaluation values do not satisfy a predetermined condition, executes a process for outputting, to the transportation service planning devices of the transportation services that passengers get on and off at the transfer point, a transport service target value of the transport means of the transportation services at the transfer point, and the transportation service planning devices control the transport means on the basis of transportation service planning information generated on the basis of the target values.

An object of the invention is to maintain autonomy of each traffic service provider and enables efficient cooperation between traffic services. A traffic service cooperation support system 1 includes a plurality of traffic service planning devices that manage traffic service plan information including transportation plan information between boarding and alighting points of a passenger, and a traffic service cooperation support device 100. The traffic service cooperation support device 100 executes processing of calculating a transportation service evaluation value for a passenger at a transfer point based on the traffic service plan information received from each traffic service planning device and travel information of a passenger by each traffic service, and processing of transmitting a target value of a transportation service of a transportation mode of a traffic service at the transfer point to the traffic service planning device of a traffic service through which a passenger gets on and off at the transfer point when the evaluation value does not satisfy a predetermined condition. The traffic service planning device controls the transportation mode based on the traffic service plan information generated based on the target value.

The invention discloses a space target long-time-sequence intelligent collision early warning method, and belongs to the technical field of space. The implementation method comprises the steps of constructing a double-branch multi-scale time convolution network long-time-sequence orbit forecasting model, and on the basis of a traditional time convolution network, establishing a relation between the model and perturbation of different time scales by establishing two branch expansion convolution structures and setting different expansion coefficients, so that the forecasting precision of the model is improved. On the basis, a voxel hash mapping rapid screening method is established, a Gaussian negative logarithm likelihood loss function is introduced, statistical characteristics of forecast errors are utilized, a voxel cube is constructed, only voxels where satellites are located and the distance between targets in neighborhoods of the voxels and the satellites need to be calculated during screening, the screening calculation scale is greatly reduced, and the screening speed is increased. The method does not depend on a high-precision dynamic model, can sense and extract the features of different time scales, improves the track forecasting precision and the collision risk screening efficiency, and accelerates the collision early warning speed.

An anomaly management system includes one or more processors. The one or more processors are configured to execute: video acquisition processing of acquiring a video captured by a camera mounted on a moving body; anomaly event recognition processing of automatically recognizing an anomaly event shown in the video and content of the anomaly event by using a machine learning model; notification destination determination processing of automatically determining a notification destination according to the content of the anomaly event; and notification processing of automatically transmitting to the notification destination, anomaly event information including at least information indicating the content of the anomaly event and position information indicating a position of the anomaly event.

A system includes a vehicle system provided with an autonomous vehicle.The vehicle system includes one or more computing devices configured to define a shared virtual secret key with an infrastructure server using a public server key obtained from the infrastructure server, generate a light code pattern to identify the autonomous vehicle using the shared virtual secret key and a code length, transmit a vehicle public key and flashing characteristics of the light code pattern, control one or more selected lighting devices of the autonomous vehicle to perform a flashing sequence indicative of the light code pattern, and transition to a maneuvering mode of operation to have the autonomous vehicle controlled by the infrastructure server in response to the autonomous vehicle being identified based on the flashing sequence.

A method for preventing a collision between a first object and a second object using a camera. The method includes capturing images of the first object and the second object using the camera, accessing a database of point clouds, and identify a first point cloud corresponding to the first object and a second point cloud corresponding to the second object within the database of point clouds, where the first point cloud corresponds to the first object being a person. The method further includes calculating a distance between the first object and the second object and comparing the distance to a threshold. The method further includes generating a notification when the distance is below the threshold.

Techniques are described for enabling a device such as a user equipment or in vehicle system to receive permissions related to maneuvering and travel of a vehicle associated with the device. The vehicle may support travel by land, water, air or in space. A privilege-granting authority server may provide a signed document indicating the permissions to the device, where the permissions authorize the vehicle to perform actions related to maneuvering and travel of the vehicle, such as exceeding posted speed limits, using reserved lanes on a highway or receiving favorable traffic treatment. The device may wirelessly transmit messages comprising the signed document to additional devices separate from the vehicle, where the additional devices respond in accordance with the permissions, such as making way for the vehicle. The signed document may include a digital signature and digital certificates to authenticate the permissions.

The present invention discloses a low-altitude weather warning method and system based on the Internet of Things, which relates to the technical field of low-altitude flight traffic control. The low-altitude weather warning method collects meteorological data in real time, including temperature, humidity, wind speed, air pressure, etc., by deploying a variety of Internet of Things sensor devices in the low-altitude flight area; uploads the collected meteorological data to the cloud server by using a data transmission network; combines a meteorological prediction model and historical big data to conduct real-time analysis and prediction of the low-altitude weather conditions; and when detecting abnormal or potentially dangerous meteorological conditions, sends warning messages to relevant users through a variety of communication methods. The present invention improves the accuracy and timeliness of low-altitude weather warning and effectively guarantees the safety of low-altitude flight air traffic.

Systems and devices that will notify train system maintenance workers of an approaching vehicle and, conversely, will notify the operators and administrators of train systems of train system maintenance workers within the vicinity of an approaching section of track. Embodiments of the safety systems and methods disclosed herein may use proportional warnings based on the speed or proximity of approaching vehicles as well as the specific location of such approaching vehicles relative to worker positions to help avoid worker warning fatigue.

A method includes identifying a route for passengers seeking to enter a building. The route includes at least one section of road for automobiles to access a building; or at least one access point inside the building for pedestrians to pass through. The method includes receiving traffic flow information corresponding to the route. The method includes determining whether the received traffic flow information corresponds to a condition that impedes the route, from among a set of pre-trained conditions. The method includes identifying and displaying a list of user-selectable state alternatives related to the condition that impedes the route, based on a determination that the received traffic flow information corresponds to the condition.

A vehicle control system and method may receive state information from a vehicle group having one or more vehicles. The state information may indicate an operational parameter of one of the vehicles. The controller may direct a display device to present one or more statuses of the one or more vehicles based at least in part on the state information that is received by the controller. This state information may be used to notify an operator of a potential component fault before continued operation of the vehicle group further damages the component or a vehicle. In another example, the state information may be used to control or change operation of one vehicle based on the state or status of another vehicle, such as by changing movement of one or more drones in a swarm responsive to a lower state of charge of another drone in the same swarm.

This specification provides an embodiment of a smart city location recommendation method and system based on the Internet of Things (IoT), executed by a management platform of the smart city location recommendation IoT system. The method includes acquiring location information and pedestrian flow information for at least one location; wherein, the location information includes the number of locations, the distance between locations, and the control measures for entrances and exits and passageways in each location; the control measures include whether the entrances and exits and passageways in each location are closed; based on the location information and pedestrian flow information of at least one location, determining multiple candidate control schemes for at least one location; and based on the multiple candidate control schemes, determining a target control scheme for at least one location.

The ever increasing number of orbiting bodies in low Earth orbit has made it infeasible to calculate potential conjunctions between orbiting bodies more than a few days in advance, even with the aid of supercomputers. Disclosed embodiments utilize machine learning to predict potential conjunctions between orbiting bodies faster than state-of-the art systems by orders of magnitude. This enables potential conjunctions to be identified well in advance (e.g., 30 days or more), so that they may be prioritized (e.g., for fine calculations), visualized, and remediated (e.g., via control of the impacted satellites).

This invention discloses a large-scale space target collision early warning combination screening method, belonging to the field of space situational awareness. The implementation method is as follows: Preliminary screening of similar targets is performed based on the distance between intersection points on the orbital plane intersection line to quickly reduce the number of satellite combinations to be analyzed; by decomposing the analytical solution considering the minimum relative distance between satellites under J2 perturbation, it is divided into long-term terms and exact solutions; based on the evolution characteristics of the long-term terms, a second screening is performed using the trend characteristics of the long-term terms; a third screening is performed using the analytical exact solution considering the relative distance between satellites under J2 perturbation; based on the results of the third screening, satellite combinations with collision risk are determined, realizing large-scale space target collision early warning combination screening, thereby protecting the safety of space assets. This invention fully considers the long-term evolution characteristics of orbits under perturbation, significantly reducing the calculation time for early warning, and is suitable for rapid screening of long-term collision early warnings for large-scale space targets.

Techniques are described for enabling a device, such as a user terminal, or an in-vehicle system to receive permissions related to maneuvering and driving of a vehicle associated with the device. The vehicle can support land, water, air or space driving. The privilege grant authorization server may provide a signature document to the device indicating permissions that authorize the vehicle to perform actions related to manipulation and driving of the vehicle, such as exceeding signed driving speed limits, using reserved lanes on a highway, or receiving advantageous traffic processing. The device may wirelessly transmit a message including the signature document to an additional device separate from the vehicle, where the additional device responds upon permission, such as making way for the vehicle. The signature document may include a digital signature and a digital certificate to authenticate the permission.

The present invention relates to the field of unmanned aerial vehicle control. The present invention discloses an unmanned aerial vehicle control platform and a method for using the same, including a real-time monitoring module, an intelligent identification module, a route management module and a task management module. The route management module uses an ARA algorithm combined with an A algorithm to plan the route of the unmanned aerial vehicle, and the intelligent identification module performs target identification based on a recurrent neural network RNN. The unmanned aerial vehicle control platform combines a variety of advanced technologies, has better route planning, more accurate target identification, improves control efficiency and accuracy, enhances flight safety and task execution effects, and meets diverse unmanned aerial vehicle application requirements. The method for using the unmanned aerial vehicle control platform of the present invention simplifies the operation process, makes the control of unmanned aerial vehicles more efficient, and saves time and labor costs.

The present invention provides an approach and landing safety monitoring and warning device for an aircraft and its application, belonging to the field of aircraft safety. The device includes: a data receiving module, an aircraft motion prediction module, a decision-making module, and an acoustic and optical warning module that are connected in sequence; the data receiving module is used to receive the on-board signal emitted by the aircraft and send the received on-board signal to the aircraft motion prediction module; the aircraft motion prediction module is used to obtain the position of the landing point corresponding to the aircraft when it lands at this airport according to the on-board signal, and send the position of the landing point to the decision-making module; the decision-making module is used to obtain the predicted value of the landing risk of the aircraft according to the position of the landing point, and start the acoustic and optical warning module according to the predicted value of the landing risk; the acoustic and optical warning module is used to send acoustic and optical signals. By using the present invention, the landing risk of an approaching and landing aircraft can be monitored and warned in real time, assisting the controller's work and improving safety.

In a condition where a construction machine is in operation in an area where communication means for transmitting operation data to a server is not available, processing for accumulating operation data of the construction machine in the server is executed. A vehicle-side control unit (17) determines whether long distance communication means (W) is available or not, when determining that the long distance communication means (W) is available, controls a first vehicle-side communication unit (14) so as to transmit the operation data via the long distance communication means (W), and when determining that the long distance communication means (W) is not available, causes a vehicle-side storage unit (15) to store the operation data, and further determines whether a transmission start command is received from a tablet (3) or not, and when determining that the transmission start command is received, controls a second vehicle-side communication unit (16) so as to transmit the operation data stored in the vehicle-side storage unit (15) via short distance communication means (N).

To provide a group control system and a group control method that allow machine learning by taking acceleration and deceleration data into account and group controlling based on correct position information.SOLUTION: A group control system controls a plurality of moving objects 10 that are capable of traveling autonomously within a predetermined area. The group control system includes a position information estimation unit 101 that estimates position information of each moving object, a route planning unit 102 that creates a route plan for each moving object based on the estimated position information, an acceleration data acquisition unit that acquires acceleration data acquired from an acceleration sensor 11, and a moving object position acquisition unit that acquires an actual position of each moving object using a position sensor. A deep reinforcement learning model is trained so as to correct the amount of deviation between the actual position of the moving body obtained using the position sensor and the estimated position of the moving body based on the obtained acceleration data.SELECTED DRAWING: Figure 4

The invention relates to a method for characterizing the environment of a moving carrier, in which, for each iteration at a given time t, the following steps are implemented: S10) Acquisition of a plurality of distance measurements in the environment by at least one sensor; S20) Generation of a pair of occupancy grids at t and t, each grid merging the distance measurements into a discretized spatial representation of the environment; S30) Generation of a static space grid at t, or S40) Generation of a free space grid at t. Figure for the abstract: Fig. 7

An apparatus, method, and computer program product for: communicating with a first proximity detection sensor and a second proximity detection sensor; detecting the presence of a collision detection device of the moving object within a first proximity detection range based on first information received from the first proximity detection sensor; in response to detecting the presence of the collision detection device, determining a vehicle speed parameter corresponding to a second proximity detection range; controlling a speed of the autonomous mining vehicle based on the vehicle speed parameter; and in response to detecting the presence of the collision detection device within the second proximity detection range, controlling the autonomous mining vehicle to perform at least one collision avoidance operation based on second information received from a second proximity detection sensor.

The present invention relates to the field of unmanned aerial vehicle management technology, and in particular to a management platform for low-altitude unmanned aerial vehicles. In order to solve the problem that the effectiveness of terrain data monitoring and the flight safety of low-altitude unmanned aerial vehicles in the prior art are difficult to ensure; the present invention is provided with a route management module to optimize the flight route of low-altitude unmanned aerial vehicles, a terrain feature monitoring module to identify terrain features, a dynamic obstacle recognition module to identify and avoid dynamic obstacles in real time in the survey area, an environmental adaptation module to dynamically adjust the flight parameters of low-altitude unmanned aerial vehicles, a task switching module to manage and switch the terrain information of low-altitude unmanned aerial vehicles that is being executed or not yet executed, a data integration module to integrate terrain information, a resource scheduling module to coordinate the collaborative operation of multiple unmanned aerial vehicles, and a user interface to provide a visual operation interface. The present invention not only greatly improves the efficiency of terrain surveys and reduces manual input, but also improves the accuracy of data collection and provides more accurate terrain information support.

Method for detecting track anomalies and associated device This method (100) includes, in configuration, the steps of: training a neural network (110) on training tracks to predict a log-likelihood value of a data track; calculation (120) of an average log-likelihood value for validation tracks and calculation (125) of a median; calculation (130) of a score on the average log-likelihood value of test tracks with respect to the median and calculation (135) of a statistical coefficient; definition (140) of an anomaly threshold from the median and the statistical coefficient.The process includes, in inference, the steps of: acquiring (150) at least one lead of interest; processing (160) the lead of interest by: calculating a mean log-likelihood value of the lead of interest; calculating a score of the mean log-likelihood value of the lead of interest relative to the median; and comparing the score of the mean log-likelihood value of the lead of interest to the abnormality threshold, the lead of interest being "abnormal" when the score of the mean log-likelihood value of the lead of interest is greater than the abnormality threshold, and "normal" otherwise. Figure for the abstract: Figure 3.

Techniques are described for enabling a device such as a user equipment or in vehicle system to receive permissions related to maneuvering and travel of a vehicle associated with the device. The vehicle may support travel by land, water, air or in space. A privilege-granting authority server may provide a signed document indicating the permissions to the device, where the permissions authorize the vehicle to perform actions related to maneuvering and travel of the vehicle, such as exceeding posted speed limits, using reserved lanes on a highway or receiving favorable traffic treatment. The device may wirelessly transmit messages comprising the signed document to additional devices separate from the vehicle, where the additional devices respond in accordance with the permissions, such as making way for the vehicle. The signed document may include a digital signature and digital certificates to authenticate the permissions.