The present disclosure is directed to a traffic signal apparatus communication system and methods of communicating traffic information to vehicles using same. The traffic signal apparatus communication system includes a traffic signal apparatus for providing a message to a vehicle. The apparatus includes at least one spatially encoded marker, and the vehicle is configured to receive returns of a radar signal from the spatially-encoded marker. At least one controller of the vehicle is configured to determine the message encoded by the spatially-encoded marker based on the returns and to control the vehicle based on the message. The message may include a value indicating a time to a transition of a new state of the traffic signal apparatus, where the new state includes emission of light from one of a first light source, a second light source, or a third light source of the traffic signal apparatus.

Disclosed herein is a black ice detection system, and more particularly, a system for detecting black ice on roads, which is capable of using a reflector and beamforming array radar installed along a road so as to measure a change in permittivity depending on the change of state of water and ice on the road and to warn of and take an appropriate action with regard to freezing conditions by detecting the same.

A detection system includes a first-sensor, a second-sensor, and a controller. The first-sensor is mounted on a host-vehicle. The first-sensor detects objects in a first-field-of-view. The second-sensor is positioned at a second-location different than the first-location. The second-sensor detects objects in a second-field-of-view that at least partially overlaps the first-field of view. The controller is in communication with the first-sensor and the second-sensor. The controller selects the second-sensor to detect an object-of-interest in accordance with a determination that an obstruction blocks a first-line-of-sight between the first-sensor and the object-of-interest.

A method for monitoring the traffic flow with the aid of a stationary radar sensor, which operates in the frequency band of 76 GHz to 77 GHz and is operated in such a way that it meets a radiation protection criterion according to which, in a sequence of consecutive time intervals which all have the same length T, each of these time intervals includes an uninterrupted radiation-free time period of at least 0.9 T. An arbitrary stationary point in the surroundings of the radar sensor within each of these time intervals is exposed to the radar radiation of this radar sensor for no more than a radiation duration of L≤T/100. The radar sensor is static during the measuring operation, and the radiation protection criterion is met by the temporally clocked operation of the radar sensor.

The present invention is a system and method to monitor, localize, and control objects in an implicitly defined geofenced area and to determine object position and orientation (vehicle only) by capturing the object's image, 3D data, or position using camera, LiDAR, and/or RADAR sensors that are installed on structures mounted on the ground. The sensors capture image, 3D data points, and distance of the surface points that are processed to ultimately obtain 3D data of the surface points of the object. The 3D data points from different sensors are then combined or fused by a controller to obtain a single set of 3D points, called fusion data, under one coordinate system such as the GPS coordinate system. The single set of 3D points is then processed by the controller using deep neural network and/or other algorithms to obtain position and orientation of the object. Additionally, the controller or sensors can send current and desired future object positions and orientations to controllable objects. Controller and/or sensors can send site image data to scene marking device and receive marked image data for geofenced monitoring of objects. Controller or sensors send alert to devices if objects are detected or abnormal behavior of objects are detected within the geofenced area.

The present invention is a system and method to monitor, localize, and control objects in an implicitly defined geofenced area and to determine object position and orientation (vehicle only) by capturing the object's image, 3D data, or position using camera, LiDAR, and/or RADAR sensors that are installed on structures mounted on the ground. The sensors capture image, 3D data points, and distance of the surface points that are processed to ultimately obtain 3D data of the surface points of the object. The 3D data points from different sensors are then combined or fused by a controller to obtain a single set of 3D points, called fusion data, under one coordinate system such as the GPS coordinate system. The single set of 3D points is then processed by the controller using deep neural network and/or other algorithms to obtain position and orientation of the object. Additionally, the controller or sensors can send current and desired future object positions and orientations to controllable objects. Controller and/or sensors can send site image data to scene marking device and receive marked image data for geofenced monitoring of objects. Controller or sensors send alert to devices if objects are detected or abnormal behavior of objects are detected within the geofenced area.

A detection system and a detection method are provided. The detection method includes configuring a processing circuit to perform an initialization phase, which includes: executing a detection process to respectively accumulate numbers of times that objects are detected to be present in sub-areas, so as to generate initial count values; and configuring the processing circuit to perform a normal operation phase, which includes: executing the detection process to respectively accumulate numbers of times that the objects are detected to be present in the sub-areas, so as to generate current count values corresponding to the sub-areas; and comparing the current count value with the initial count value in a current sub-area of the sub-areas. In response to the current count value being greater than the initial count value plus a first count threshold, a new stationary object is determined to be present in the current sub-area.

A density of Mode S interrogations and responses in the environment covered by a secondary radar is characterized according to the following steps: a first step wherein the radar: detects and locates Mode S targets by way of their synchronous responses to the interrogations emitted by the radar; detects asynchronous responses emitted by the Mode S targets, and not elicited by the radar; for each target, associates its asynchronous responses with its synchronous response to the radar; a second step wherein the radar: based on the association, determines the response rate of each target by counting the number of synchronous and asynchronous responses received from the target per given time period; with the environment being divided into elementary space cells, determines the response rate per cell by counting the number of synchronous and asynchronous responses received by each target in each cell, the rate characterizing the density of Mode S interrogations per cell.

A method for monitoring the take-off and/or landing procedure of an aircraft (1), in particular for an electrical, vertical take-off and landing aircraft (1), in which a monitoring region of a take-off and landing site (2) is monitored by at least one microphone (4, 5) of a monitoring station to detect sound emission data of an aircraft (1) taking off or landing as it approaches or departs and the detected sound emission data are transmitted from the monitoring station to an evaluation unit. The detected sound emission data are evaluated by the evaluation unit by comparing the detected sound emission data to characteristic sound emission data.

A method for monitoring a data fusion function of an infrastructure system for the infrastructure-supported assistance of motor vehicles during an at least semi-automated driving task within an infrastructure, the infrastructure including multiple infrastructure surroundings sensors for detecting an area of the infrastructure. The method includes: receiving multiple input data sets intended for the data fusion function, each of which includes surroundings data based on the respective detection of the area, which represent the detected area; receiving output data based on a data fusion of the input data sets, output by the data fusion function; checking the input data sets and/or the output data for consistency; outputting a check result of the check. A device, a computer program, and a machine-readable memory medium are also provided.