35 results about "Basic safety message" patented technology

The invention discloses an Internet of Vehicles attack detection method based on attention and space-time convolution, and relates to the field of Internet of Vehicles communication data security, and the method comprises the steps: enabling a vehicle to access a network at a trusted mechanism, and obtaining an ID; the edge cloud collects a basic safety message data set containing an ID of the vehicle and preprocesses the basic safety message data set; obtaining a time sequence diagram comprising an edge set and a node set; edge cloud generation comprises a network model of a graph convolutional neural network, a recurrent neural network and an attention mechanism, a training set and a test set are divided, and an attention and space-time convolutional network model is trained; and testing the network model by using the test set to obtain category prediction, and evaluating the model performance according to related indexes. According to the method, the graph convolutional neural network is adopted to learn the topological structure of the vehicle in the road to capture the spatial dependence of the vehicle, the recurrent neural network is adopted to learn the dynamic change of the basic safety message BSMs to capture the time dependence, and the attention mechanism is adopted to enable the model to have good robustness.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a transmitter mobile station may transmit at least one platoon control message (PCM) having a flexible structure, the at least one PCM comprising a first part and a second part that is different from the first part, wherein the first part comprises non-platoon-specific data elements and the second part comprises platoon-specific data elements. The transmitter mobile station may transmit at least one basic safety message (BSM). Numerous other aspects are described.

A system is provided for implementing an upstream message selection system that dynamically changes a message type for a cooperative vehicle platoon such that traffic congestion is mitigated and the damping properties of the platoon tail are improved. The upstream message selection system analyzes the current traffic conditions in a real-real time driving scenario to determine when increasing a frequency of transmitting messages are failing to sufficiently mitigate a traffic disturbance. The upstream message selection system determines that increasing the transmission rate of basic safety messages (BSMs) is sufficiently attenuating a traffic disturbance in a real-real time driving scenario. In response to detecting that increasing the frequency of BSMs is failing to efficiently attenuate a traffic disturbance, the upstream message selection system dynamically changes the message type from BSM to an intent maneuver message for the upstream vehicles based on the downstream response to a disturbance within the platoon.

Methods, systems, and devices for wireless communications are described. A user equipment (UE) (e.g., a vehicle, low-power sensor) may identify that the UE satisfies a set of conditions for a stationary state. The stationary state may be associated with a configuration for transmitting a position message (e.g., a basic safety message (BSM)) while the UE satisfies the stationary state. The UE may identify a periodicity at which to transmit the position message based on the UE satisfying the set of conditions for the stationary state, where the periodicity associated with a stationary state may be larger than a periodicity associated with a non-stationary state. The UE may transmit (e.g., broadcast) the position message over a sidelink in accordance with the configuration and based on identifying that the UE satisfies the set of conditions for the stationary state.

This disclosure provides systems, methods, and devices for wireless communication that support enhanced Basic Safety Message (BSM) reporting. A method of wireless communication includes receiving, by a wireless communication device, a C-V2X message from another wireless communication device; and transmitting, by the wireless communication device, a safety message including certificate information responsive to determining a certificate information trigger condition is satisfied based on the C-V2X message. Other aspects and features are also claimed and described.

The present invention relates to a method for communication during a group ride, in which several vehicles (611, 612, 613, 621, 622, 623, 631, 632, 633) are each equipped with a GPS sensor and means for V2X communication and internet communication, in which, in a first step, a vehicle group with at least two vehicles located within a V2X transmit / receive range (602, 603) is formed as respective group participants by means of internet communication, by transmitting a respective ID data record from each group participant, which includes the name of a driver and a V2X sender ID of the respective vehicle, to a backend server, and from the backend server a group data record with all group participants is transmitted to each vehicle, and in which, in a second step, a group ride is carried out by means of V2X communication.by managing the V2X Basic Safety Messages containing status information from all vehicles in each vehicle, assigning the vehicle with the shortest distance to a destination as the lead vehicle, and continuously generating a map with the route and GPS positions of all group participants in each vehicle by a control unit of the respective vehicle, and displaying the map on a display unit for the respective driver.

A roadside unit (RSU) receives, from a first set of on-board units (OBUs) of a first set of vehicles, messages describing events triggered by the first set of OBUs in response to basic safety messages (BSMs). Each BSM is received by a vehicle from the RSU or another vehicle over a PC5 interface. Each vehicle is operating at less than a threshold distance from the RSU. A timestamp is assigned to each event. A feature vector is extracted from the timestamped events. A machine learning model generates an update to functionality of the RSU based on the feature vector. The machine learning model is trained to update the functionality for vehicular management. The RSU is operated using the updated functionality to communicate with a second set of OBUs of a second set of vehicles for preventing vehicular collisions among the second set of vehicles.

Embodiments include systems and methods for automatically populating safety messages (such as basic safety messages (BSMs)) with the positions and combined lengths of the vehicle and the towed object. Some embodiments include determining the distance from one or more antennas coupled to a receiver in the vehicle to the remote sensor on the towed object by processing short-range wireless signals received from a remote sensor. Some embodiments include populating the safety message with the positions of the vehicle and the towed object based on the determined distances from the one or more antennas to the remote sensor.

The invention relates to the technical field of vehicle control, in particular to a vehicle forward collision early warning method, a computer program product, electronic equipment and a storage medium. The vehicle forward collision early warning method comprises the following steps: acquiring an Internet of Vehicles basic safety message sent by a remote vehicle, wherein the basic safety message comprises a remote vehicle position and a remote vehicle speed; determining a rectangular area in front of the driving direction of the vehicle according to the position, the direction angle and the speed of the vehicle; if the position of the far vehicle is located in the rectangular area, determining a safe distance between the two vehicles according to the speed of the far vehicle and the speed of the vehicle; according to the size relation between the longitudinal distance and the safety distance between the two vehicles, forward collision early warning is conducted on the vehicle. According to the invention, the accuracy and real-time performance of forward collision early warning can be improved.

The present invention relates to an operation method of a V2X device when a plurality of V2X devices are present within a vehicle, and the operation method of the V2X device may comprise the operations of: determining whether or not the V2X device is present within the vehicle; if the V2X device is present within the vehicle, determining whether the V2X device needs to act as a driver or a passenger; when it is determined that the V2X device acts as the driver, transmitting a vehicle basic safety message in which the user type is set as the driver; and when it is determined that the V2X device acts as the passenger, transmitting a vehicle basic safety message in which the user type is set as the passenger.

The application discloses a V2X trust management system based on Mamba and a block chain, which utilizes a deep neural network Mamba deployed at a base station to detect whether a basic safety message broadcast by a vehicle is abnormal in an unsupervised sequence reconstruction manner. A detection result is converted into a 'positive interaction' or 'negative interaction' record representing a vehicle behavior and stored in a block chain module jointly maintained by the base station. When it is necessary to evaluate vehicle trust, the base station inquires all interaction histories of the vehicle from the block chain module and calculates a dynamic trust value of the vehicle based on a Beta distribution expectation. The application innovatively combines a powerful abnormal detection capability of deep learning and decentralized and tamper-proof characteristics of a block chain, realizes effective identification of attacks in a vehicle network and distributed trust management, and solves a single-point failure problem of a centralized scheme.

A method performed by a communication apparatus according to an aspect of the present disclosure includes calculating (400, 530) a generation interval and transmit power of a basic safety message used for Vehicle-to-Vehicle, V2V, safety communication, based on a channel busy ratio which is a ratio of time during which a channel is busy and on vehicle density within a predetermined range, and transmitting (500), based on the generation interval and the transmit power, the basic safety message over a PC5 reference point specified in a technical specification of the 3rd Generation Partnership Project, 3GPP.

A communication device mounted on a vehicle, e.g., On-Board Unit (OBU), communicates collision related information to other road entities, e.g., other vehicles or roadside units (RSUs) or a server, after a collision is detected. The OBU may temporarily store basic safety messages (BSMs) (and optionally sensor data) for a predesignated number of seconds before discarding the BSMs (and optionally sensor data) on a continuing basis. When a collision is detected, the OBU sends a report, e.g., to a server, with the stored BSMs (and optionally sensor data) to a server. After a collision detection, the OBU may send a request to other vehicles to upload relevant collision related information. Additionally, if a first vehicle detects the collision of a second vehicle, the first vehicle may communicate collision related information to other entities and a server.

An embodiment relates to an operation method of a user equipment (UE) in a wireless communication system, the method comprising: receiving a crossing input from a pedestrian by the UE; configuring a predetermined area on a road on the basis of a position of the pedestrian; selecting a vehicle having a collision possibility when the pedestrian crosses, among vehicles within the predetermined area; transmitting, by the UE, a personal safety message (PSM) including information which relates to a crossing request of the pedestrian and is to be transmitted to one or more vehicles, on the basis of one or more selected vehicles; receiving a basic safety message (BSM) including a response to the crossing request and transmitted from each of the one or more vehicles; and displaying crossing request acceptance information on a display part by the UE, on the basis of the response.

The system is provided with a roadside unit (RSU) transceiver equipped with a sensor suite consisting of one or more electro-optic sensors, camera sensors, thermal imaging sensors, lidar sensors, ultrasonic sensors, and / or radar sensors, and capable of receiving authenticated participant Society of Automotive Engineers (SAE) standard J2735 basic safety messages, RTK-corrected GNSS positioning data, and SAE standard J3224 sensor data sharing messages. The system may include one or more processors programmed or configured to receive data from the system's own sensor suite, reporting transceiver, and other network-connected devices, and to construct high-reliability object actor detection, classification, and tracking perception messages representing object actors within the system's field of view for use in other internal system processes, and to transmit them to other external devices for use.

The present disclosure provides systems, methods, and devices for wireless communication supporting enhanced Basic Safety Message (BSM) reporting. In a first aspect, a method of wireless communication includes receiving, by a wireless communication device, a C-V2X message from another wireless communication device, and transmitting, by the wireless communication device, a safety message including route history information in response to determining, by the wireless communication device, that a route history information trigger condition is met based on the C-V2X message. In a second aspect, a method of wireless communication includes receiving, by the wireless communication device, a C-V2X message from another wireless communication device, and transmitting, by the wireless communication device, a safety message including certificate information in response to determining, by the wireless communication device, that a certificate information trigger condition is met based on the C-V2X message. Other aspects and features are also claimed and described.

The invention relates to the technical field of Internet of Vehicles security, in particular to an Internet of Vehicles false data injection attack detection method based on federated learning, which comprises the following steps: firstly, remodeling the original features of a vehicle basic security message through a time window, and processing spatial input features by a sliding alignment strategy; then, a BiLSTM is used for capturing a time sequence dependency relationship, and a lightweight Transform parallel modeling global space relationship is designed; and further dynamically calculating an attention score through a feature fusion weight matrix, realizing double-branch dimension-level dynamic weighting, performing dimension reduction in combination with a difference pooling strategy, and coupling a classifier. And the road side unit performs global aggregation based on a weighting strategy of node reputation and contribution degree, and distributes the global aggregation to node vehicles for a new round of incremental training. The method effectively solves the problem that traditional centralized learning cannot give consideration to privacy protection and lightweight calculation in the detection of the false data injection attack of the Internet of Vehicles, and remarkably improves the detection effect of the false data injection attack.

Various embodiments include methods and systems for vehicle-to-everything (V2X) system of a vehicle for managing processing of a basic safety message (BSM). Various embodiments may include calculating a relevancy value of a received BSM prior to conducting security processing of the BSM, determining whether the relevancy value of the BSM meets a relevancy threshold, and stopping processing of the BSM in response to determining that the relevancy value of the BSM does not meet the relevancy threshold.

An analysis server for analyzing factors of a dangerous road section by receiving a precise road map and a basic safety message (BSM) provided from an autonomous vehicle, according to the present invention, comprises a communication unit, a storage unit and a control unit, wherein the control unit controls the communication unit and the storage unit so as to accumulate the BSM or the precise road map in the storage unit for a specific period of time, configures a dataset by calculating an independent variable from the BSM and calculating a dependent variable from the precise road map, generates and trains a dangerous road section classification model by applying an XGBoost algorithm to the dataset, calculates importance for each factor of the dangerous road section, and performs factor analysis on the dangerous road section on the basis of the calculated importance for each factor.

Provided a Road Side Unit (RSU) transceiver enabled to receive authenticated participant Society of Automotive Engineers (SAE) standard J2735 Basic Safety Messages, RTK corrected GNSS positioning data, SAE standard J3224 Sensor Data Sharing Messages and equipped with a sensor suite consisting of one or more electro-optical sensors, camera sensors, thermal imaging sensors, lidar sensors, ultrasonic sensors, and or radar sensors; the system may include one or more processors programmed or configured to receive data from the system's own sensor suite, reporting transceivers and other network connected devices, to construct high confidence object-actor detection, classification, and tracking perception messages representing the object-actors in the system's field of view for use in other system internal processes and transmit to other external devices for use.

The invention discloses a segmentation learning vehicle networking anomaly detection method and system based on a large language model, relates to the technical field of vehicle networking security, and solves the problems of insufficient detection precision, large computing resource occupation and high privacy leakage risk in the prior art. The method comprises the following steps: generating a BSM sequence based on a sliding window, and mapping the BSM sequence into a high-dimensional Token representation; uploading the Tokens to a cloud end, extracting a context dependency relationship between the Tokens by using an LLM model of a bidirectional self-attention mechanism, and generating a message sequence representation matrix; and a vehicle-mounted classifier calculates an abnormal probability according to the representation matrix, and real-time detection is completed. According to the method, the computation-intensive tasks are unloaded to the cloud through segmentation learning, and a vehicle-mounted module only needs a 568KB storage space, so that the effects of low computation load and strong privacy protection are achieved.

The present invention discloses a vehicle-road cooperative data processing method and related equipment, which relate to the field of communication technology, in order to solve the problem in related technologies that the security and reliability of roadside perception data are poor, thereby affecting the security and reliability of vehicle-road cooperative information services. The method includes: obtaining N groups of roadside perception data of the target road section; obtaining M groups of basic safety message BSM data of the target road section; making a confidence judgment on the i-th group of roadside perception data based on the i-th group of roadside perception data and the M groups of BSM data, where i takes values from 1 to N in sequence; outputting K groups of roadside perception data whose confidence meets the requirements among the N groups of roadside perception data, where K is a positive integer less than or equal to N; providing vehicle-road cooperative information services to traffic objects on the target road section based on the traffic data on the target road section, where the traffic data includes K groups of roadside perception data. The embodiments of the present invention can improve the security and reliability of roadside perception data, thereby ensuring the security and reliability of vehicle-road cooperative information services.

A message hop-based communication method of guaranteeing real-time communication in a vehicle communication environment may comprise: receiving, by a first on-board unit (OBU) of a first vehicle, a first message including a message frame (MF) for probe vehicle data (PVD) from a road side unit (RSU); and transmitting a second message, including an MF for a basic safety message (BSM), to a second OBU of a second vehicle, the second message corresponding to the first message, wherein the PVD and the BSM each comprise a data frame for a hopping request.

This disclosure provides systems, methods, and devices for wireless communication that support enhanced Basic Safety Message (BSM) reporting. A method of wireless communication includes receiving, by a wireless communication device, a C-V2X message from another wireless communication device; and transmitting, by the wireless communication device, a safety message including certificate information responsive to determining a certificate information trigger condition is satisfied based on the C-V2X message. Other aspects and features are also claimed and described.

Embodiments of the present disclosure provide a collision early warning method, a vehicle-mounted terminal and a storage medium, related to the field of smart automobiles. The method comprises: acquiring a map message (MAP), state information of a host vehicle and basic security messages (BSM) of multiple remote vehicles; according to the MAP and the state information, determining whether the host vehicle is about to drive into an intersection; if the host vehicle is about to drive into an intersection, then, according to the MAP, the state information and the BSM of each of the distant vehicles, screening out a target remote vehicle having a risk of collision with the host vehicle in the intersection from among the multiple remote vehicles; and during the process from when the host vehicle enters the intersection to when the host vehicle exits the intersection, if it is predicted that the host vehicle will with one of the target remote vehicles, then outputting collision early warning information. The present disclosure greatly improves vehicle collision risk detection accuracy and early warning accuracy.

A roadside unit (RSU) receives, from a first set of on-board units (OBUs) of a first set of vehicles, messages describing events triggered by the first set of OBUs in response to basic safety messages (BSMs). Each BSM is received by a vehicle from the RSU or another vehicle over a PC5 interface. Each vehicle is operating at less than a threshold distance from the RSU. A timestamp is assigned to each event. A feature vector is extracted from the timestamped events. A machine learning model generates an update to functionality of the RSU based on the feature vector. The machine learning model is trained to update the functionality for vehicular management. The RSU is operated using the updated functionality to communicate with a second set of OBUs of a second set of vehicles for preventing vehicular collisions among the second set of vehicles.