1045 results about "Vehicle networks" patented technology

The invention provides an Internet of Vehicles vulnerability management method, system, device and medium based on a block chain, and relates to the technical field of vehicle networks, the method can comprehensively identify potential safety risks of vehicles through a dynamic and static combined vulnerability detection mechanism, and generates a structured vulnerability report; hash abstract chaining evidence storage is performed on key data of reports and subsequent repair links by using a block chain, so that the whole process of vulnerability discovery, analysis and repair is ensured not to be tampered and traceable, and the authenticity and credibility of data are improved; the integrity of the report is verified at the cloud end, and an AI analysis engine is combined to associate a CVE database and threat intelligence, so that intelligent generation and decision support of a repair scheme are realized; the hash abstract on the chain of the OTA patch is verified at the vehicle end, so that the credibility of the patch source and the integrity of the content are guaranteed; and finally, through feedback of an installation result and secondary uplink archiving, complete closed-loop management from vulnerability discovery to repair verification is formed.

The invention discloses an Internet of Vehicles network selection and switching decision system supporting access of multiple operators. According to the method and the device, the timeliness and the continuity of network switching are remarkably improved through prediction and planning in advance. The module depends on a trajectory-network matching prediction sub-module, combines a vehicle navigation trajectory and a global digital twinborn model, identifies a base station coverage area in a future driving path and the network service quality of each operator in advance, and avoids the lag problem that switching is triggered only after signals are weakened in traditional passive switching. The pre-switching resource reservation sub-module further sends a resource request to a target operator base station and confirms reservation before the vehicle enters a new road section, ensures that resources such as bandwidth and time slot required during switching are in place, reduces switching failure or interruption caused by resource competition, avoids common communication interruption after signal sudden drop in traditional switching, and improves the switching efficiency. And continuous transmission of key businesses such as automatic driving control instructions and real-time road conditions is ensured.

The invention provides an Internet of Vehicles broadcast frame radio frequency fingerprint identification method based on LMMSE channel estimation. The method comprises the following steps: obtaining subcarrier data in a resource grid based on an obtained signal of a physical side link broadcast channel; performing root-mean-square delay expansion and channel autocorrelation matrix construction based on the subcarrier data, and combining priori signal-to-noise ratio regularization and time domain windowing operation to obtain a channel estimation value; initial radio frequency fingerprint features are obtained through the channel equalization and the channel estimation value, and the improved neural network and the initial radio frequency fingerprint features are utilized to carry out classification identification on the Internet of Vehicles equipment. Influences of noise and channels on fingerprints are effectively considered, and the purpose of extracting fingerprints of different devices in a complex environment more accurately is achieved.

The invention provides a large-scale ultrafast charging facility vehicle network interaction-oriented adaptive regulation and control system, and belongs to the technical field of charging pile load scheduling. During working, a multi-source data acquisition and vehicle network state sensing module acquires and fuses multiple types of data, and a vehicle network interaction strategy optimization module generates a strategy according to the data; the power dynamic distribution module distributes power according to a strategy, and the energy storage coordinated control module optimizes energy storage charging and discharging. The real-time response and feedback module quickly responds to a power grid instruction and corrects a strategy, and the security and protocol adaptation module guarantees security and docking. During use, after the terminal is started, fusion data is automatically collected, a regulation and control strategy is generated and executed, instructions are responded and corrected in real time, and safety and cross-platform adaptation are guaranteed in the whole process.

The invention relates to an Internet of Vehicles multi-agent cooperative sensing method and system. The method comprises the following steps: constructing a collaborative sensing network, wherein the collaborative sensing network comprises a self-agent and a plurality of collaborative agents; acquiring and processing sensing data through the collaborative sensing network; performing feature extraction to obtain intermediate features; self-adaptive sparsification is carried out to obtain sparse features, and the sparse features are compressed and transmitted to a self-agent; performing time sequence feature enhancement on the features of all the agents at the self-agent end; fusing the features to obtain fused features; and constructing an Internet of Vehicles perception model, and realizing perception by the detection model according to the fused features. According to the method, the calculation complexity of traditional global attention is reduced from the square level to the linear level through an adaptive sparsification mechanism, the calculation overhead is remarkably reduced while the multi-agent feature interaction precision is kept, and the method is more suitable for real-time operation on the vehicle-mounted edge equipment with limited resources.

The invention provides a vehicle-mounted network security threat sensing system and method based on edge and cloud collaboration, and belongs to the technical field of vehicle network security. Comprising the following steps: S1, collecting vehicle multi-modal data through an edge layer; s2, preprocessing the multi-modal data of the vehicle; s3, performing feature extraction on the preprocessed vehicle multi-modal data to obtain a high-dimensional feature vector; s4, calculating a threat confidence score based on the high-dimensional feature vector; s5, performing hierarchical response decision based on the threat confidence score and a predefined response strategy library, and generating hierarchical response data; s6, extracting threat metadata based on the hierarchical response data; s7, performing global association analysis based on the threat metadata, and upgrading a defense system; and S8, based on the global threat intelligence and the upgraded defense system, carrying out edge layer updating, and then skipping to S1. The method is beneficial to eliminating response delay, relieving network bandwidth pressure and optimizing cloud computing resource load.

The invention relates to the technical field of intelligent power grid and electric vehicle cooperative control, and discloses a plug-and-play and flexible power regulation and control integrated vehicle network interaction cooperative control system, which comprises a protocol adaptive conversion module, a multi-modal data alignment module, a flexible power regulation and control module, a vehicle pile identity authentication module and a power grid state sensing module, and realizing inter-generation vehicle millisecond-level identification and data unified modeling through the protocol middleware. According to the method, the problems of protocol compatibility and data alignment in a plug-and-play scene are solved, and deep coordination between the charging process and the power grid state is realized through flexible power regulation and control and a multi-stage safety mechanism. The system guarantees the non-inductive charging experience of a user, reduces the impact on a power grid to the maximum extent, prolongs the service life of a battery, and improves the energy utilization efficiency.

The invention discloses a heterogeneous Internet of Vehicles network selection method based on fuzzy logic and a related device. The method comprises the following steps: acquiring network attributes of candidate networks; inputting the network attribute of each candidate network into a membership function to obtain input membership of low, medium and high levels of the network attribute; performing fuzzy reasoning on the input membership degrees of the low, middle and high levels of the network attribute to obtain an aggregation membership degree of the output level of the network attribute; performing defuzzification on the aggregation membership degree of the output level of the network attribute to obtain a network evaluation value of each candidate network; according to the method and the related device, the network selection problem of a V2I communication scene can be solved, the optimal network can be selected, and efficient information transmission with road infrastructures is realized.

An embodiment method for managing at least one vehicle network including at least one electronic control unit (ECU) among a plurality of ECUs in a vehicle network management apparatus is provided, which may include, based on information of at least one default partial network cluster including at least one ECU among the plurality of ECUs according to at least one default partial network function provided by default in a mapping database, configuring a new partial network cluster by adding an ECU according to user customization to the at least one default partial network cluster, and storing information of the new partial network cluster in the mapping database.

The in-vehicle device for receiving time synchronization information transmitted from each of a plurality of reference devices and transmitting the received time synchronization information to another device, includes: a communication unit configured to communicate with the other device; and an information processing unit configured to, if the communication unit receives a frame in which the time synchronization information is stored, store the time synchronization information in a specific queue with priority over other information, wherein the communication unit transmits the time synchronization information stored in the specific queue to the other device.

The invention discloses a vehicle diagnosis service method and system based on dynamic protocol adaptation and context awareness, and the method comprises the steps: analyzing a diagnosis request, and determining a service range and a dependency relationship required by the diagnosis request; obtaining multi-dimensional context information, and based on the obtained information and the dependency relationship, executing a routing decision to select an optimal service instance and a protocol path; dynamically calling a protocol adapter through a protocol adaptation matrix based on the service instance and the protocol path, converting the diagnosis request into a protocol message, and sending the protocol message to a vehicle network; and receiving the original diagnosis data returned by the vehicle network to generate a complete diagnosis report. According to the method, flexible calling of the protocol adapter is realized through the dynamic protocol adaptation matrix, the service range and the dependency relationship are analyzed in combination with the service governance engine, and the routing decision is optimized by utilizing the multi-dimensional context information, so that the method has the advantages of dynamic and flexible protocol adaptation, accurate and intelligent service analysis and global optimization of the routing decision.

The described techniques address issues related to compatibility and cost-effectiveness of in-vehicle networks. The described techniques may utilize security Ethernet-based protocols, for example, without the need to exchange separate key agreement messages and, consequently, meet the stringent starting time requirements for real-time control systems. Additionally, a membership tracking solution may be implemented in which each node within a membership group may request, or “challenge” other nodes with the same group to verify their online status, and this online status may be maintained over time. Finally, a transmission queue management process is described that deletes queued messages only when it is determined that every intended recipient node received the message, thereby providing atomicity. Retained queued messages may then be re-transmitted in accordance with a transmission schedule.

The invention provides a surrounding vehicle track prediction method and system based on an attention mechanism in a network connection environment, and the method comprises the steps: constructing a vehicle network which comprises a road side unit and a vehicle; cooperative driving data of the target vehicle and surrounding vehicles are obtained through a road side unit and a sensor on the vehicle; the driving data is preprocessed; inputting the preprocessed driving data into the trained Transform trajectory prediction model based on the attention mechanism to obtain a trajectory prediction result of the surrounding vehicles; calculating a root-mean-square error between the trajectory prediction result and the actual running trajectory of the vehicle; constructing a vehicle collaborative decision according to the trajectory prediction result and the root-mean-square error, and controlling the operation of the vehicle based on the vehicle collaborative decision; according to the invention, an attention mechanism is adopted to effectively capture a complex dynamic interaction relationship between vehicles, and the precision of trajectory prediction is remarkably improved.

The invention discloses a photovoltaic-energy storage-electric vehicle collaborative V2G optimization scheduling method adaptive to a building scene, and relates to the technical field of building energy management and vehicle network interaction, and the method comprises the steps: training to obtain a data generator; outputting sample data of new energy output and building load scenes through a data generator, and generating a plurality of typical scenes by using a clustering algorithm and a Nash equilibrium model; in each typical scene, planning vehicle network interaction facility configuration, and carrying out cooperative scheduling on a source, a load, a storage and a vehicle; selecting participating automobiles, and scheduling the participating automobiles in combination with battery loss and a compensation mechanism; and comprehensive evaluation of economy and operation quality is carried out on the collaborative scheduling result of the source, the load, the storage and the vehicle, the planning result of vehicle network interaction facility configuration and the scheduling result of the participating vehicle. According to the method, the uncertainty scene serves as input, cost minimization is achieved through the two-stage model, and the economical efficiency and feasibility of the scheme are verified through evaluation.

The invention discloses a vehicle network interaction intelligent scheduling optimization method and system fused with elastic optimization. The method comprises the following steps: acquiring a power grid state, an electricity price, an electric vehicle state and user behavior information in real time; determining a plurality of scheduling targets and constraint conditions; constructing elastic energy functions with rigidity coefficients for the scheduling targets respectively, and coupling the elastic energy functions to construct a total elastic energy function; defining a state vector reflecting the real-time state of the current system, and dynamically adjusting a coupling structure and a rigidity coefficient of the coupling structure between the elastic energy functions based on the state vector; and finally, on the premise of meeting constraint conditions, solving an optimal scheduling strategy for minimizing the total elastic energy. Through the bionic elastic mechanical model, adaptive coordination and optimization of multiple conflict targets are realized, the flexibility and stability of the electric vehicle participating in power grid adjustment are improved, and the elasticity and reliability of the whole vehicle network interaction system are enhanced.

The AutoWrap Robotics Humanoid Service Center System is an innovative AI platform that autonomously manages vehicle service centers using a fleet of humanoid robots. It coordinates customer interaction, advanced diagnostics (including for EVs / SDVs) with Explainable AI, and autonomous vehicle repairs, alongside facility and outdoor maintenance. Integrating cutting-edge humanoid robots with sophisticated AI, machine learning, and multi-modal sensing, the platform provides semantic understanding of complex environments. It boosts service quality, reduces labor demands, and dramatically increases operational efficiency, transforming underperforming properties into highly productive autonomous centers. Key features include augmented reality interfaces, robust cybersecurity for in-vehicle networks and robot operations, predictive maintenance, and real-time, socially adaptive humanoid-mediated customer communication. Delivered as a scalable Software-as-a-Service (SaaS) solution, the system provides essential AI intelligence for fully autonomous, comprehensive, and sustainable vehicle servicing.

The invention provides a management method and system of a vehicle networking control unit. The method comprises the steps of obtaining various operation data of a vehicle-mounted T-BOX; the types of the operation data comprise hardware state data, software operation data and vehicle operation state data; extracting a plurality of operation feature representations from the plurality of operation data; inputting the plurality of operation feature representations into a pre-trained fault prediction set model to obtain a fault prediction result of the vehicle-mounted T-BOX; wherein the fault prediction set model comprises a fault prediction overall model and at least one fault prediction sub-model for a specific fault type of the vehicle-mounted T-BOX; inputting the various operation data into a pre-constructed health state evaluation model, and determining a health state evaluation result of the vehicle-mounted T-BOX; and integrating the fault prediction result and the health state evaluation result of the vehicle-mounted T-BOX, and executing a fault processing action. In this way, the accuracy of vehicle-mounted T-BOX fault prediction, the comprehensiveness of health assessment and the initiative of fault processing can be improved, and the fault occurrence rate is effectively reduced.

A method of communication in a vehicle network is provided. An example method includes transmitting a network allocation map in a TDMA cycle, indicating reservation of time slots in the TDMA cycle. The method further includes transmitting a synchronization signal in the TDMA cycle, to synchronize the timing of nodes in the vehicle network. Each of the reserved time slots is identified by at least a network ID of a transmitting node in the vehicle network, and a slot type comprising one of a low latency traffic slot, and a bulk traffic slot. Further, the low latency traffic slots are repeated in the TDMA cycle at least as frequently as a guaranteed QoS latency parameter. Further, the bulk traffic slots are at least as long as a guaranteed QoS throughput parameter.

The invention provides a modular multi-shaft redundant braking system and a braking pressure distributed calculation and distribution method thereof. The system comprises an air storage tank, a battery and a plurality of redundant brake units arranged on all axles of the multi-axle vehicle respectively, and each axle of the multi-axle vehicle is independently provided with one redundant brake unit. The shaft redundant brake unit comprises a redundant brake module, and a shaft left wheel brake cylinder, a shaft right wheel brake cylinder, a shaft left wheel speed sensor and a shaft right wheel speed sensor which are respectively connected with the redundant brake module; the redundant braking module is connected with the air storage tank and the battery so as to obtain a braking air source and a working power source. The communication networks of all the redundant brake modules are mutually connected and are connected with a whole vehicle network; the problems that an existing redundant braking system is high in cost and low in redundancy are solved.

An anomaly detection device detects an anomaly in an in-vehicle network system including two or more electronic control units and one or more networks and includes: ECU attribute storage in which attributes of the two or more electronic control units each of which has been set for a corresponding one of the two or more electronic control units are stored; a communicator that transmits and receives a message on the one or more networks; and an anomaly detector that detects anomalous communication by using an attribute of a message source electronic control unit or an attribute of a message destination electronic control unit among the attributes stored in the ECU attribute storage. The attribute stored in the ECU attribute storage indicates the function of the electronic control unit including the attribute or the type of information that is handled by the electronic control unit including the attribute.

The invention discloses an Internet of Vehicles security certification and data encryption transmission system integrated with an IPv6 (Internet Protocol Version 6) technology. According to the invention, the key strategy can be automatically optimized according to the dynamic environment in the actual operation of the Internet of Vehicles, and the dynamic balance between the security protection and the communication efficiency is realized. The system can intelligently judge the cracking risk faced by a current key by combining real-time data such as a vehicle driving state and network environment characteristics, so as to flexibly adjust the key length and the updating frequency: when the network environment is safe and the vehicle is in a low-risk area, the key service cycle is properly prolonged, and the basic key length is maintained to reduce the communication overhead; when a potential threat is detected or a vehicle enters a complex road section, the secret key security level is automatically improved, and the rotation period is shortened to enhance the protection capability. The system burden cannot be increased due to excessive encryption, potential safety hazards cannot be left due to insufficient protection, and key management better meets the actual requirements of high-speed movement of vehicles and rapid change of scenes in the Internet of Vehicles.

The invention provides a vehicle remote upgrading method and device and a vehicle, which are applied to the technical field of automobile information security, and the method comprises the following steps: firstly encrypting an original upgrading package through a dynamic symmetric algorithm key to obtain an encrypted upgrading package, carrying out Hash algorithm operation on the original upgrading package to obtain a first Hash value, and then, carrying out Hash algorithm operation on the original upgrading package to obtain a second Hash value; performing asymmetric algorithm private key encryption on spliced data of the symmetric algorithm secret key and the first hash value to obtain a digital signature, encrypting the digital signature and the symmetric algorithm secret key by using a vehicle-side asymmetric algorithm public key to obtain a digital envelope, packaging the digital envelope and an encrypted upgrade package into a transmission data package, and finally, sending the transmission data package to the vehicle-side asymmetric algorithm public key. And the transmission data packet is transmitted to the vehicle-mounted networking terminal, so that the vehicle-mounted networking terminal performs asymmetric signature verification and symmetric decryption based on the transmission data packet, and software upgrading corresponding to the upgrading packet is realized. According to the method, the symmetric algorithm key and the hash value digital signature are jointly packaged into the digital envelope, so that the tampering risk of the upgrade package is reduced.

The invention relates to a decentralized federated learning method for vehicle-mounted CAN (Controller Area Network) bus intrusion detection, which belongs to the field of vehicle-mounted network security and comprises the following steps: S1, constructing a decentralized federated learning system; s2, the client initializes a local model, reconstructs and learns CAN signals, and achieves anomaly detection; s3, each client executes initial training, and local model parameters are updated; s4, establishing a dynamic communication topology between the clients by adopting a Gossip protocol, calculating cosine similarity of the two models, pairing according to similarity difference, and selecting a client pair with the maximum difference to perform model exchange and aggregation; s5, taking a weighted aggregation result of the paired clients as an intermediate model, and carrying out rollback learning on a data set of the opposite side to generate a temporary update model; s6, the paired clients exchange temporary updating models, cross-updating training is carried out on respective local data sets, and a round of local model updating is completed; and S7, repeatedly executing the steps S3-S6 until a preset condition is met.

A system and method in a building or vehicle for an actuator operation in response to a sensor according to a control logic, the system comprising a router or a gateway communicating with a device associated with the sensor and a device associated with the actuator over in-building or in-vehicle networks, and an external Internet-connected control server associated with the control logic implementing a PID closed linear control loop and communicating with the router over external network for controlling the in-building or in-vehicle phenomenon. The sensor may be a microphone or a camera, and the system may include voice or image processing as part of the control logic. A redundancy is used by using multiple sensors or actuators, or by using multiple data paths over the building or vehicle internal or external communication. The networks may be wired or wireless, and may be BAN, PAN, LAN, WAN, or home networks.

The invention relates to the technical field of computers, in particular to a vehicle network switching method and device, electronic equipment and a storage medium. According to the vehicle network switching method, a route network prediction table is determined firstly, so that prediction conditions of a satellite beam and a ground network correspondingly covered by a preset position point of a vehicle on a driving route are known; the network signal strength in the current ground network state and the current driving state are judged in sequence, and when the network signal strength and the current driving state in the current ground network state are both met, the route network prediction table and the navigation route information of the vehicle are input into the network switching model to obtain a target network switching strategy, so that the network switching strategy can be continuously adjusted in real time, and the network switching efficiency is improved. The network coverage change is pre-judged in advance, the switching delay is reduced, and intelligent and accurate network switching is realized.

A system may include a plurality of network shared storage (NSS) client managers associated with a respective plurality of share entities in the vehicle. The system may include an NSS server manager communicatively coupled to the plurality of share entities and configured to manage access of the plurality of share entities to a shared data storage, wherein the NSS server manager is further configured to manage access of the plurality of share entities by configuring at least one of the plurality of NSS client managers to manage access to the shared data storage of an associated one of the respective plurality of share entities, wherein the NSS server manager is communicatively coupled to the plurality of share entities over a mixed in-vehicle network (IVN) including a plurality of different network types.

The invention provides a desktop-level hardware-in-the-loop test system building method, device and equipment, and relates to the technical field of hardware-in-the-loop simulation, and the method comprises the steps: configuring a vehicle network simulation and vehicle dynamics model in an upper computer with a CAN development environment and vehicle dynamics simulation software, a real-time data channel between the two is established through a full duplex transmission protocol; a driver instruction is generated through the driving control panel, and a vehicle state signal is generated through vehicle dynamics software; the wheel speed in the vehicle state signal is converted into a physical excitation signal, and a wheel cylinder pressure signal returned by the controller is collected; the pressure signal is fed back to the vehicle dynamics model to form a closed loop, a test scene is executed, and the desktop-level hardware-in-loop test of the brake controller is completed. By using vehicle dynamics simulation software, the test confidence coefficient is improved; data exchange is carried out by utilizing an FDX protocol of a CAN development environment, and complexity and potential risks of self-development of a communication interface are avoided.

The invention provides a fault repair and task unloading optimization method under a space-air-ground fusion vehicle-mounted network framework, and belongs to the technical field of Internet of Vehicles. According to the first stage, the optimal deployment point location of the unmanned aerial vehicle is searched globally based on the wolf pack algorithm, the flight path is planned dynamically in combination with the near-end strategy optimization algorithm, and network connectivity repair of a fault area is achieved; and in the second stage, a task unloading decision initial population is generated through multiple deep reinforcement learning agents, and a Pareto optimal solution set is obtained through optimization of a non-dominated sorting genetic algorithm II, so that multi-target balance of energy consumption, cost and time delay is realized. According to the method, the fault self-healing capability and task processing efficiency of the SAGVN can be remarkably improved, and the method adapts to the high-dynamic and high-reliability requirements of intelligent traffic.

The invention discloses a security encryption method, device, equipment and medium for a vehicle-gauge-level HSM, and relates to the technical field of vehicle network security, and the method comprises the steps: obtaining a target algorithm parameter corresponding to a target encryption task in an algorithm parameter register after receiving the target encryption task, and determining a corresponding encryption algorithm type; if the target algorithm type is a post quantum cryptography algorithm type, a true random number generation component of a vehicle gauge level HSM is called through a post quantum cryptography coprocessor to generate a true random seed, and a target encryption task is executed based on the target algorithm parameter and the true random seed; in the process of executing the target encryption task, second-order mask operation is carried out on the fast number theory transformation operation, whether error injection attacks exist or not is continuously detected in the sampling process, and operation results of the key steps are stored through a preset composite register set.