Method for encoding/decoding a signal at a first and second communication node (N1; N2) in a road vehicle. A signal (1) from an on-board sensor (10) is encoded using a first encoding scheme (a), encoding the formed single encoded sensor signal (1a) using a second encoding scheme (b), decoding this double encoded sensor signal (1ab) in the second communication node (N2) based on the second encoding scheme (b), forming a decoded single encoded sensor signal (1a′). In the first communication node (N2), performing a comparison analysis, comprising at least one of the following: comparing the decoded single encoded sensor signal (1a′) with a stored single encoded sensor signal (1a), or after encoding the decoded single encoded sensor signal (1a′) with the second encoding scheme (b) comparing (110) the thus formed double encoded sensor signal (1a′b) with a stored double encoded sensor signal (1ab). If the compared sensor signals (1a′,1a; 1 ab,1a′b) match, then sending (111) a signal to the second communication node (N2) validating the sensor signal (1), and if they do not match, then initiating (112) a corrective action.

Methods and systems are provided for indicating a driving situation including at least one vehicle. The system includes a first processor, a second processor and an external device. A first processor obtains driving information, encodes the driving information and communicates the encoded driving information to the second processor. The second processor receives and decodes the encoded driving information. The second processor further allocates a predefined indication pattern to the decoded driving information, wherein the predefined indication pattern includes a graphical representation of an upcoming driving event involving the vehicle. An external device visualizes a current driving situation including the vehicle together with the predefined indication pattern.

The present disclosure is related to Intelligent Transport Systems (ITS), and in particular, to Vulnerable Road User (VRU) basic services (VBS) of a VRU ITS Station (ITS-S). Different arrangements and configurations of the VBS within the facilities layer of an ITS-S are described. Also described are different rules and/or conditions for VRU Awareness Message (VAM) formats, VAM generation and coding, and VAM dissemination.

Autonomous vehicles, and user-driven vehicles with an emergency intervention capability, can communicate to avoid collisions using 5G/6G technology, but this level of cooperation is possible only if the threatened vehicles have already determined the relative location and wireless address of the other vehicle. Disclosed is a method for wireless vehicles in traffic to exchange distance and angular information of the other vehicles in view, from which a position map can be prepared indicating the relative locations of each participating and non-participating vehicle. In addition, the traffic map can be annotated with the wireless addresses of the participating vehicles, thereby enabling them to communicate instantly in an emergency. The traffic map may be prepared or updated by one of the vehicles in traffic, or by a roadside access point. Satellite data is not necessary for the relative localization, but may be included if available.

Vehicles in traffic cannot coordinate their actions properly in 5G and 6G without knowing the location and the wireless address of the other vehicle. GNSS signals are generally too slow and too imprecise to discern vehicles in, for example, adjacent lanes. Directional wireless beams are subject to reflections from conducting surfaces, producing chaotic signals and false locations if more than one vehicle is within the transmission beam. To provide precise localization in traffic, methods are disclosed for multiple vehicles (or other mobile devices) to acquire satellite signals simultaneously, and then analyze the data differentially, thereby canceling major uncertainties (such as propagation variations, ephemeris motion, and clock jitter), and thereby determining the relative positions precisely. Unlike prior-art “precision” positioning methods, the disclosed methods do not require averaging multiple acquisitions. On the contrary, examples show how high differential precision can be obtained without averaging, using measurements acquired at the predetermined time.

The embodiment relates to a method for calibrating a traffic management system which is configured for the automated guiding of a vehicle within a traffic region, which method is configured for the automated parking of a vehicle, and to such a traffic management system. The traffic management system comprises at least one monitoring sensor for monitoring the traffic region, a communication device for communication with a vehicle, in particular for sending driving directions to the vehicle, and a controller for processing the signals from the at least one monitoring sensor and for determining driving instructions for the vehicle. The method comprises the following steps: detecting at least one object in the traffic region with the at least one monitoring sensor and storing the information about the object, querying sensor information of at least one environmental sensor of the vehicle and checking whether the detected object is detected by the environmental sensor, if the object is detected by the environmental sensor, retrieving the information of the environmental sensor relating to that object, and calibrating the monitoring sensor taking account of the information about the object acquired by the monitoring sensor and the information about the object acquired by the environmental sensor of the vehicle.

Disclosed are systems and methods for vehicles in traffic to simultaneously measure local traffic parameters and communicate the data to a planning vehicle in 5G and 6G. Each participating vehicle can measure, at a predetermined time, the angles of the other vehicles in view, and also the distances to the other vehicles using radar or lidar, for example. They then communicate the data to a planning vehicle. The planning vehicle “merges” or interconnects the various angle measurements to form a self-consistent traffic map of all vehicles in view of any of the participating vehicles, including non-participating vehicles. The planning vehicle then broadcasts the traffic map, or a listing of positions and wireless addresses of the vehicles, for all to use. The vehicles can then identify each other, and communicate with each other, to avoid collisions and facilitate the flow of traffic.

Disclosed are systems and methods for vehicles in traffic to simultaneously measure local traffic parameters and communicate the data to a planning vehicle in 5G and 6G. Each participating vehicle can measure, at a predetermined time, the angles of the other vehicles in view, and also the distances to the other vehicles using radar or lidar, for example. They then communicate the data to a planning vehicle. The planning vehicle “merges” or interconnects the various angle measurements to form a self-consistent traffic map of all vehicles in view of any of the participating vehicles, including non-participating vehicles. The planning vehicle then broadcasts the traffic map, or a listing of positions and wireless addresses of the vehicles, for all to use. The vehicles can then identify each other, and communicate with each other, to avoid collisions and facilitate the flow of traffic.

Communication between autonomous vehicles, in 5G or 6G, is necessary for cooperative hazard avoidance and to coordinate the flow of traffic. However, before cooperative action, each vehicle must determine the wireless address of other vehicles in proximity, so that they can communicate directly with each other. Methods and systems disclosed herein include a computer-readable wireless “connectivity matrix”, an array of black and white squares showing a connectivity code. The connectivity code may be the vehicle's wireless address, an index code, or other information about the vehicle. The connectivity code may be an index in a tabulation of information that provides the wireless address, among other data. Other vehicles, or their cameras, may read the connectivity matrix, determine the code therein, and find the vehicle's wireless address. After determining the wireless address of the other vehicles, the vehicles can then communicate and cooperate to avoid accidents and facilitate the flow of traffic.

A visual localization support system is provided. The visual localization support system includes one or more guidance indicators place on a road surface of a roadway, wherein the one or more guidance indicators each include a matrix barcode that uniquely identifies a location by latitude, longitude, and altitude, and describes an affine shape of the guidance indicator.