Vehicle peer-to-peer cooperative blind area bidirectional early warning method, device and equipment

Abstract

The invention relates to the technical field of intelligent traffic and vehicle active safety, in particular to a vehicle peer-to-peer cooperative blind area bidirectional early warning method, device and equipment. The method comprises the following steps: periodically broadcasting own state information and a blind area model; according to the received state information broadcasted by the surrounding vehicles and a blind area model, whether the surrounding vehicles are located in the blind area of the vehicle or not is calculated, and meanwhile whether the vehicle is located in the blind area of the surrounding vehicles or not is calculated; if it is detected that the surrounding vehicles are located in the blind area of the vehicle, an active early warning message is sent to the corresponding surrounding vehicles; if it is judged that the vehicle is located in the blind area of the surrounding vehicle, introspection early warning is triggered, and confirmation request information is sent to the corresponding surrounding vehicle; and receiving an active early warning message or confirmation request information sent by the surrounding vehicles, and carrying out cooperative avoidance response. The problems that a blind area monitoring system is unidirectional, depends on single perception and cannot dynamically adapt to traffic scenes can be solved.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation and vehicle active safety technology, and in particular to a vehicle peer-to-peer cooperative two-way blind spot warning method, device and equipment. Background Technology

[0002] With the development of intelligent transportation technology, vehicle active safety systems have become a core support for improving driving safety. Blind spot monitoring, as a key function, is directly related to road traffic safety in terms of its reliability. In complex traffic scenarios such as highways and urban expressways, the risk of blind spot collisions when vehicles change lanes or drive side-by-side is frequent, making the need for accurate perception and timely warning of blind spot conditions increasingly urgent.

[0003] Current mainstream blind spot detection systems (BSD) are mostly based on onboard sensors for local detection, providing only warnings of targets within the blind spot to the driver of the vehicle. Some research explores blind spot warning solutions based on vehicle-to-everything (V2X) technology, but these still primarily rely on a one-way notification model of "driver vehicle detection - driver vehicle transmission - target vehicle reception".

[0004] Existing technologies have obvious limitations: First, information transmission is one-way, and target vehicles in blind spots cannot know their dangerous state, resulting in a prominent information asymmetry problem; second, they rely on the perception capabilities of a single vehicle, and sensor failure or missed detection can easily lead to warning failure; third, they lack dynamic role adaptation capabilities, which cannot meet the safety requirements of real-time vehicle role switching in traffic scenarios, and the passive defense mode is difficult to cope with blind spot risks in complex road conditions. Summary of the Invention

[0005] This invention provides a vehicle-to-vehicle cooperative two-way blind spot warning method, device, and equipment to solve the problems of blind spot monitoring systems being one-way, relying on a single perception, and unable to dynamically adapt to traffic scenarios.

[0006] In a first aspect, embodiments of the present invention provide a vehicle-to-vehicle cooperative blind spot two-way warning method, applied to each vehicle participating in the cooperation, including: Periodically broadcast its own state information and blind spot model; Based on the status information broadcast by surrounding vehicles and the blind spot model, calculate whether surrounding vehicles are within the blind spot of this vehicle, and at the same time calculate whether this vehicle is within the blind spot of surrounding vehicles. If a vehicle is detected to be in the blind spot of another vehicle, an active warning message is sent to the corresponding vehicle. If it is determined that the vehicle is in the blind spot of another vehicle, an introspective warning is triggered, and a confirmation request is sent to the corresponding vehicle. The confirmation request is a request for the corresponding vehicle to confirm whether the vehicle is in its blind spot. It receives proactive warning messages or confirmation requests from surrounding vehicles and responds in a coordinated manner to avoid them.

[0007] In one possible implementation, the blind spot model is a dataset of geographic coordinates of a blind spot polygon calculated based on vehicle dimensions and heading angle; The step of calculating whether surrounding vehicles are within the vehicle's blind spot based on the received status information broadcast by surrounding vehicles and the blind spot model, and simultaneously calculating whether the vehicle is within the blind spot of surrounding vehicles, includes: The vehicle receives the status information and blind spot model broadcast by surrounding vehicles, determines its relative position to surrounding vehicles based on the status information, and calculates whether surrounding vehicles are within its blind spot based on its own blind spot model. At the same time, it calculates whether its own vehicle is within the blind spot of surrounding vehicles based on the blind spot models of surrounding vehicles.

[0008] In one possible implementation, before periodically broadcasting its own state information and blind zone model, the following is also included: All vehicles synchronize their time.

[0009] In one possible implementation, after determining that the vehicle is in the blind spot of surrounding vehicles, triggering an introspective warning, and sending confirmation request information to the corresponding surrounding vehicles, the method further includes: If no perception confirmation response is received from the corresponding vehicle, the risk level is raised.

[0010] In one possible implementation, receiving proactive warning messages or confirmation request information from surrounding vehicles and responding with coordinated avoidance includes: After receiving the proactive warning message sent by surrounding vehicles, the system verifies the perception results and issues a warning to the driver of the vehicle based on the verified perception results. After receiving the confirmation request information, it verifies its own perception results and replies with a perception confirmation reply to the sender.

[0011] In one possible implementation, if the risk level of the self-introspection warning is increased, or if the self-perception result is verified to indicate that there is blind spot overlap and conflict risk, the current situation is determined to be a high-risk scenario, and a collaborative control negotiation process is initiated to reach a consensus on a collaborative avoidance strategy with the corresponding vehicle; the collaborative avoidance strategy is executed and the execution result is fed back.

[0012] In one possible implementation, the cooperative avoidance strategy agreed upon with the corresponding vehicle includes: Based on predetermined yield rules and road priorities, a cooperative avoidance strategy is achieved with the corresponding vehicle by exchanging control suggestions, which include deceleration, acceleration, or maintaining the current state.

[0013] In one possible implementation, executing the cooperative avoidance strategy and feeding back the execution result includes: The vehicle or a higher level of autonomous driving system automatically executes the aforementioned cooperative avoidance strategy; Once the execution is complete, the executing vehicle broadcasts the execution result and simultaneously notifies surrounding vehicles to lift the warning.

[0014] Secondly, embodiments of the present invention provide a vehicle peer-to-peer cooperative blind spot bidirectional warning device, applied to each vehicle participating in the cooperation, including: a broadcast module for periodically broadcasting its own status information and blind spot model; The calculation module is used to calculate whether the surrounding vehicles are within the blind spot of the vehicle, and at the same time calculate whether the vehicle is within the blind spot of the surrounding vehicles, based on the status information broadcast by the surrounding vehicles and the blind spot model. The warning module is used to send an active warning message to the corresponding surrounding vehicles if it detects that the vehicle is in the blind spot of the vehicle; if it determines that the vehicle is in the blind spot of the surrounding vehicles, it triggers an introspection warning and sends a confirmation request message to the corresponding surrounding vehicles. The confirmation request message is a request for the corresponding vehicle to confirm whether the vehicle is in its blind spot. The processing module is used to receive proactive warning messages or confirmation requests from surrounding vehicles and to respond in a coordinated avoidance manner.

[0015] Thirdly, embodiments of the present invention provide an apparatus including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method described in the first aspect or any possible implementation thereof.

[0016] This invention provides a vehicle-to-vehicle cooperative blind spot two-way warning method, device, and equipment. It periodically broadcasts its own status information and blind spot model; based on the received status information and blind spot model from surrounding vehicles, it calculates whether surrounding vehicles are within its own blind spot, and simultaneously calculates whether its own vehicle is within the blind spots of surrounding vehicles; if a surrounding vehicle is detected to be within its blind spot, it sends an active warning message to the corresponding surrounding vehicle; if it determines that its own vehicle is within the blind spot of a surrounding vehicle, it triggers an introspective warning and sends a confirmation request to the corresponding surrounding vehicle, requesting confirmation of whether its own vehicle is within its blind spot; it receives active warning messages or confirmation request messages from surrounding vehicles and performs a cooperative avoidance response. This invention, through two-way perception of risk status, informs other vehicles "you are in my blind spot" and also informs itself "I am in other vehicles' blind spots." The warning information originates from mutual calculation and confirmation, effectively eliminating information barriers, significantly reducing false alarm rates, and no longer relying on the perception capabilities of a single vehicle, thus improving warning response efficiency. Each vehicle is equipped with both "external warning" and "internal self-reflection" capabilities, and can adapt to the real-time changes in the vehicle's role in complex traffic (such as from "blind spot creator" to "blind spot victim") without switching modes, adapting to diverse scenario needs such as parallel driving on highways and lane changing on urban roads. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating the implementation of the vehicle peer-to-peer cooperative blind spot two-way warning method provided in this embodiment of the invention. Figure 2 This is a schematic diagram of the vehicle peer-to-peer cooperative blind spot two-way warning device provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the device provided in an embodiment of the present invention. Detailed Implementation

[0019] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0020] See Figure 1 The diagram illustrates a flowchart of a vehicle-to-vehicle cooperative blind spot two-way warning method provided by an embodiment of the present invention. This method is applied to all participating vehicles, and the implementing entities of this solution are the participating vehicles. Details are as follows: Step 101: Periodically broadcast its own state information and blind spot model.

[0021] This step is the basic data interaction link for vehicle-to-vehicle cooperative blind spot two-way warning and control. The core purpose is to realize the real-time synchronization of status and blind spot information among the participating vehicles, so as to provide accurate data support for subsequent dual calculation, risk assessment and cooperative control.

[0022] Each vehicle participating in the collaboration performs an information broadcast operation. The broadcast content includes two key types of information: first, the vehicle's precise status information; and second, a blind spot model generated in real time based on the vehicle's parameters.

[0023] The status information includes the vehicle's position, speed, heading, and dimensions. Position information is obtained through the Global Positioning System (GPS) or Real-time Kinematic (RTK) technology to ensure that the positioning accuracy meets the requirements for relative position calculation. Speed ​​and heading information are collected in real time by onboard sensors, reflecting the vehicle's current driving status. The dimensions are fixed parameters calibrated at the vehicle's factory and serve as the basis for generating the blind spot model.

[0024] The blind spot model is a dataset of geographic coordinates of polygonal blind spots. Its generation logic is as follows: based on the vehicle body size (such as length, width, wheelbase) and real-time heading angle, the geographic coordinate range of typical blind spots such as the side and rear of the vehicle and the A-pillar obstruction area is calculated by a preset algorithm to form closed polygonal data, ensuring the accurate definition of the blind spot range.

[0025] To ensure the real-time and consistency of information synchronization, the broadcast operation adopts a periodic triggering method, with the broadcast frequency set at 10Hz. This allows for timely updates of vehicle status and blind spot locations in complex traffic scenarios, avoiding risk misjudgments caused by information lag.

[0026] At the same time, while broadcasting information, each vehicle synchronizes its time with surrounding vehicles through Cellular-Vehicle to Everything (C-V2X) technology, ensuring that all participating vehicles perform subsequent data processing and risk calculations under a unified time reference, effectively eliminating judgment errors caused by communication delays.

[0027] The status information and blind spot model broadcast in this step will be received by surrounding vehicles participating in the collaboration and used for dual calculations. It is not only the core carrier for this vehicle to transmit its own driving status and danger zone to surrounding vehicles, but also the prerequisite for realizing the dual capabilities of "identifying its own blind spot" and "perceiving whether it is in the blind spot of other vehicles", laying the data foundation for the two-way early warning and collaborative control of the entire system.

[0028] Step 102: Based on the received status information broadcast by surrounding vehicles and the blind spot model, calculate whether surrounding vehicles are within the blind spot of this vehicle, and at the same time calculate whether this vehicle is within the blind spot of surrounding vehicles.

[0029] This step is the core calculation process for enabling vehicles to "look outward" and "look inward." By making a two-way determination of the blind spot position relationship between the vehicle and surrounding vehicles, it provides a direct basis for subsequent risk assessment and early warning decisions.

[0030] The prerequisite for dual computation is that the status information and blind spot model broadcast by surrounding vehicles participating in the collaboration have been received, and all vehicles have completed time synchronization with GPS / RTK technology through C-V2X to ensure a unified time base for computation and avoid errors caused by communication delays.

[0031] In one embodiment, based on the received status information broadcast by surrounding vehicles and a blind spot model, it is calculated whether surrounding vehicles are within the vehicle's blind spot, and simultaneously, it is calculated whether the vehicle is within the blind spot of surrounding vehicles, including: It receives status information and blind spot models broadcast by surrounding vehicles, determines its relative position to surrounding vehicles based on the status information, and calculates whether surrounding vehicles are within its blind spot based on its own blind spot model. At the same time, it calculates whether its own vehicle is within the blind spot of surrounding vehicles based on the blind spot models of surrounding vehicles.

[0032] Calculating whether surrounding vehicles are within the vehicle's blind spot and calculating whether the vehicle itself is within the blind spot of surrounding vehicles are two sub-steps that are executed in parallel.

[0033] When calculating whether surrounding vehicles are within the vehicle's blind spot, the vehicle first uses received status information from surrounding vehicles, combined with its own positioning information, to determine the real-time relative position between itself and each surrounding vehicle using a preset algorithm. This includes relative distance and relative orientation. Then, the vehicle's blind spot model is invoked, and the coordinates of the surrounding vehicles' body outlines are geometrically superimposed with the coordinates of the vehicle's blind spot polygon for judgment. If the body outlines of surrounding vehicles fall entirely or partially within the vehicle's blind spot polygon, and a potential conflict risk is identified based on the speed and heading of both vehicles (e.g., the vehicle intends to change lanes, or the distance between the two vehicles is continuously decreasing), then the surrounding vehicle is determined to be within the vehicle's blind spot and marked as a "potential threat target." Simultaneously, local sensors, such as radar, cameras, and lidar installed on the vehicle, monitor the blind spot to assist in verifying the calculation results and improve the accuracy of the judgment.

[0034] Optionally, in this embodiment, there is no limitation on the preset algorithm for determining the real-time relative position relationship between the vehicle and every surrounding vehicle; any existing algorithm can be used.

[0035] When calculating whether the vehicle is within the blind spot of surrounding vehicles, this sub-step uses mirror logic from the first sub-step. It extracts the blind spot models broadcast by surrounding vehicles and simultaneously obtains the vehicle's body outline coordinates, which can be generated based on the vehicle's dimensions. Combining the previously determined relative positional relationships, the vehicle's body outline coordinates are geometrically superimposed with the blind spot polygon coordinates of the surrounding vehicles for judgment. If the vehicle's body outline falls entirely or partially within the blind spot polygon range of the surrounding vehicles, it is determined that the vehicle is within the blind spot of those surrounding vehicles, thus identifying the risk of "being a threat target."

[0036] The two sub-steps described above are executed synchronously and in parallel, ensuring that the vehicle can simultaneously grasp two key pieces of information: "whether there are other vehicles in its blind spot" and "whether it is in the blind spot of other vehicles." During the calculation process, real-time broadcast information from surrounding vehicles is continuously received, and the relative positional relationships and blind spot determination results are dynamically updated to adapt to the dynamic changes in vehicle driving status in traffic scenarios, providing real-time and accurate computational support for subsequent risk level assessment and two-way warning triggering.

[0037] Step 103: If surrounding vehicles are detected to be in the blind spot of this vehicle, send an active warning message to the corresponding surrounding vehicles; if it is determined that this vehicle is in the blind spot of surrounding vehicles, trigger an introspection warning and send a confirmation request message to the corresponding surrounding vehicles. The confirmation request message is a message requesting the corresponding vehicle to confirm whether this vehicle is in its blind spot.

[0038] This step is the core execution link for realizing the vehicle's two-way warning function. Based on the potential collision risk assessment results in step 103, a reliable risk warning system is constructed through the two-way triggering of active warning and self-reflective warning, combined with a status confirmation mechanism, to provide a decision-making basis for subsequent collaborative control. The specific implementation process is as follows: The two-way warning is triggered based on the results of the dual calculation in step 102 and the risk assessment in step 103, namely, whether "surrounding vehicles are in the vehicle's blind spot and there is a risk of conflict" and "whether the vehicle is in the blind spot of surrounding vehicles and there is a risk of collision". Step 103, the risk assessment, is based on the dual calculation results of step 102, combined with the vehicle's driving status and traffic scene characteristics, to accurately determine whether there is a potential collision risk, providing a basis for subsequent warning triggering and collaborative strategy formulation. The specific implementation process is as follows: The core input for risk assessment is the dual calculation result of step 102, namely "whether the surrounding vehicles are in the blind spot of this vehicle" and "whether this vehicle is in the blind spot of the surrounding vehicles". At the same time, it is necessary to combine the real-time status information of this vehicle and surrounding vehicles (including position, speed, and heading) and traffic scene attributes (such as road type and driving direction) for comprehensive analysis.

[0039] The specific judgment logic is divided into the following two scenarios, which can be judged independently or in combination: 1. Risk assessment based on "surrounding vehicles are in the blind spot of this vehicle".

[0040] When the dual calculation results show that there are surrounding vehicles in the vehicle's blind spot, the vehicle first confirms that the outline of the surrounding vehicle falls within the range of the vehicle's blind spot polygon, such as falling entirely or partially within it. Then, it combines the speed difference, relative distance, and heading change trend of the two vehicles to determine whether there is a risk of conflict.

[0041] For example, if the vehicle intends to change lanes, and the surrounding vehicles in the blind spot are traveling at similar speeds and the relative distance between them is continuously decreasing, then a potential collision risk is determined; for example, the vehicle's intention to change lanes can be determined through onboard turn signals and driving trajectory prediction. If the vehicle maintains a straight line and its relative position to vehicles in the blind spot remains stable with no tendency to intersect, the risk level is determined to be low or no risk. Simultaneously, the vehicle's local sensors, such as radar, cameras, and lidar, will collect dynamic data on vehicles in the blind spot to cross-validate the risk assessment results, avoiding misjudgments due to a single data source.

[0042] 2. Risk assessment based on "the vehicle is in the blind spot of surrounding vehicles".

[0043] When the dual calculation results show that the vehicle is in the blind spot of a certain surrounding vehicle, the vehicle will analyze the risk by combining the relative motion state of the vehicle and the surrounding vehicles.

[0044] For example, if surrounding vehicles accelerate or turn, potentially altering their trajectories, and the relative distance between this vehicle and those vehicles is less than a safety threshold, a potential collision risk is identified. If surrounding vehicles maintain a constant speed and travel in a straight line, and this vehicle does not enter their core blind spot (e.g., a close-range area to the side or rear), the risk level is considered low. Furthermore, if this vehicle sends a status confirmation request to a surrounding vehicle but does not receive a confirmation response within a preset time, it indicates that the other vehicle may not have detected this vehicle, significantly increasing the risk level and classifying it as a high-risk scenario.

[0045] During the risk assessment process, based on preset risk level classification rules, such as combining parameters like relative speed, distance, blind spot overlap range, and vehicle action intent, the assessment results are categorized into four levels: "no risk," "low risk," "medium risk," and "high risk." "Medium risk" and "high risk" scenarios will trigger corresponding early warning mechanisms, while "high risk" scenarios will also trigger subsequent collaborative control negotiation processes. Simultaneously, the risk assessment results are dynamically adjusted based on real-time updates of vehicle status information, ensuring timely adaptation to changes in traffic scenarios and providing accurate and real-time decision support for subsequent stages.

[0046] Based on the risk assessment results above, the early warning execution process can be divided into two scenarios, as follows: 1. Triggering and sending proactive alerts; When the risk assessment indicates the presence of surrounding vehicles in the vehicle's blind spot with a potential collision risk, the vehicle immediately triggers an active warning. The vehicle generates a targeted active warning message, which clearly includes the vehicle's identification, current location, driving status, and a warning message stating "You are in this vehicle's blind spot, please be careful," ensuring that the receiving vehicle is clearly aware of the source and scenario of the risk.

[0047] Subsequently, the vehicle forwards the proactive warning message to the corresponding surrounding vehicles. This targeted forwarding mechanism ensures that the warning information is accurately delivered to the target vehicle, avoiding irrelevant vehicles receiving redundant information, while also improving information transmission efficiency and ensuring the real-time nature of the warning. The transmission of the proactive warning message is cross-referenced with the monitoring results of the vehicle's local sensors, further ensuring the accuracy of the warning and avoiding false warnings caused by a single calculation result.

[0048] 2. Triggering and confirmation request process for self-reflection and early warning; When the risk assessment results indicate that the vehicle is in the blind spot of a surrounding vehicle and there is a risk of collision, the vehicle triggers a self-reflection warning and issues a clear warning to the driver through human-machine interaction. The warning information includes audible and visual alarms and visual prompts (such as "Warning, you are in the blind spot of the vehicle on your left"), allowing the driver to intuitively understand the dangerous situation they are in.

[0049] After triggering the self-reflection warning, to further confirm the authenticity of the risk and avoid safety hazards caused by information asymmetry, a confirmation request is sent to the corresponding vehicle. This confirmation request requests the corresponding vehicle to confirm whether the vehicle is in its blind spot. The core content of the confirmation request is to ask surrounding vehicles to confirm whether they have detected the vehicle's presence and whether the vehicle is within their blind spot. This confirmation request is also sent to the corresponding surrounding vehicles, awaiting their response.

[0050] In one embodiment, if no perception confirmation response is received from the corresponding vehicle, the risk level is increased.

[0051] If the vehicle does not receive a perception confirmation response from the surrounding vehicles within a preset time, it indicates that the surrounding vehicles may not have detected the vehicle, or that their perception systems may have missed or malfunctioned. In this case, the vehicle's risk level will be greatly increased, such as from "medium risk" to "high risk," and the warning prompts will be strengthened through human-machine interaction. At the same time, it will provide a basis for initiating the collaborative control negotiation process. If a perception confirmation response is received from the surrounding vehicles, and the response information shows that the other party has detected the vehicle, the current risk level will be maintained, and the risk status will continue to be synchronized with the driver through human-machine interaction.

[0052] Optionally, the above preset time can be set based on the real-time requirements of traffic scenarios, typically in the millisecond range.

[0053] This step, through the bidirectional triggering of proactive and self-reflective early warnings, breaks through the limitations of one-way information transmission in traditional blind spot monitoring systems. Combined with a confirmation request mechanism, it effectively solves the problem of information asymmetry. Simultaneously, the dynamic adjustment of risk levels based on the response results further improves the accuracy and reliability of risk assessment, laying a crucial foundation for building a proactive, collaborative, and redundant security network.

[0054] Step 104: Receive proactive warning messages or confirmation request information sent by surrounding vehicles and respond in a coordinated avoidance manner.

[0055] This step is the core response link for two-way information exchange between vehicles. It involves targeted processing of proactive warning messages and confirmation requests sent by surrounding vehicles, combined with local perception verification to achieve mutual verification of information and risk synchronization, laying the foundation for collaborative control in subsequent high-risk scenarios.

[0056] The types of messages received include proactive warning messages and confirmation request messages sent by surrounding vehicles. The response processes for these two types of messages are independent of each other and logically complete.

[0057] In one embodiment, receiving proactive warning messages or confirmation request information from surrounding vehicles and responding to coordinated avoidance may include: After receiving proactive warning messages from surrounding vehicles, the system verifies the perception results and, based on the verified perception results, issues a warning to the driver of the vehicle. After receiving the confirmation request, it verifies its own perception results and sends a perception confirmation reply to the sender.

[0058] When a vehicle receives a proactive warning message from a surrounding vehicle, it first parses the message content to extract the sender vehicle's identification, location, driving status, and warning prompts (such as "You are in this vehicle's blind spot, please be careful"), thus identifying the source of the risk and the associated vehicle.

[0059] Subsequently, a local perception verification process is triggered. The instruction uses onboard sensors, such as radar, cameras, and lidar, to monitor the position of the sending vehicle and its own blind spot in real time, verifying whether the sending vehicle's statement that "this vehicle is in its blind spot" is consistent with the local perception result. For example, if the receiving vehicle is vehicle B, after receiving a warning message from vehicle A that "you are in my right blind spot," vehicle B's sensors will focus on monitoring its own right-side area and the position of vehicle A to confirm whether vehicle A is indeed located to its side and rear, and whether vehicle B has fallen within vehicle A's blind spot range.

[0060] After verification, the vehicle issues a precise warning to its driver based on the verification results. If the local perception result matches the proactive warning message, a clear audible and visual alarm and visual prompt (such as "The vehicle on your left has warned you that you are in its blind spot; please do not change lanes") are issued through human-machine interaction to enhance the driver's risk awareness. If the local perception result does not match the proactive warning message, such as if the sending vehicle is not detected, the warning level is lowered, and the driver is informed of the relevant warning information in the form of a prompt, such as "Received warning from the vehicle on your left; no corresponding vehicle detected; please drive cautiously," to avoid false alarms affecting the driver's judgment. The entire response process ensures both the timeliness of the warning and improves the reliability of the information through local perception verification.

[0061] When a vehicle receives a confirmation request from a surrounding vehicle, it parses the core content of the message to clarify the matter the sending vehicle is requesting confirmation of, namely, "whether the sending vehicle is within the vehicle's blind spot" and "whether the vehicle has detected the sending vehicle".

[0062] The vehicle initiates its own perception result verification process. Combining the received status information of the sending vehicle, such as position, speed, heading, and vehicle dimensions, it uses onboard sensors to accurately locate the sending vehicle and calculate blind spot matching. This verifies whether the sending vehicle is indeed within the vehicle's blind spot and whether the vehicle's sensors have effectively detected its presence. For example, if the receiving vehicle is vehicle B, upon receiving a request from vehicle A to confirm whether it has detected the vehicle and whether it is within the recipient's blind spot, vehicle B will scan its own blind spot using sensors to confirm whether vehicle A's position falls within the blind spot polygon, and simultaneously verify whether its sensors have identified vehicle A as a target.

[0063] After verification, a perception confirmation response is sent to the sending vehicle based on the verification results. The response clearly includes two core conclusions: "Whether the sending vehicle was detected" and "Whether the sending vehicle is in this vehicle's blind spot." For example, "Your vehicle has been detected; you are in this vehicle's left rear blind spot" or "Your vehicle was not detected; you are not in this vehicle's blind spot." This response is sent directly to the requesting vehicle, providing crucial evidence for adjusting its risk level and enabling information verification and risk coordination between vehicles.

[0064] This step constructs a closed-loop logic of "message reception - local verification - precise feedback" by responding to different types of messages. It not only solves the problem of insufficient information reliability in traditional one-way early warning, but also strengthens the risk consensus between vehicles through perception and mutual verification. This provides accurate decision support for initiating collaborative control negotiation processes in subsequent high-risk scenarios and further improves the distributed safety redundancy system.

[0065] In one embodiment, if the risk level of the self-introspection warning is increased, or if the self-perception result is determined to be that there is blind spot overlap and conflict risk, the current situation is determined to be a high-risk scenario, and a collaborative control negotiation process is initiated to reach a consensus on a collaborative avoidance strategy with the corresponding vehicle; the collaborative avoidance strategy is executed and the execution result is fed back.

[0066] This section is the core handling link of the system in dealing with high-risk blind spot conflicts. It reaches a consensus on avoidance strategy by initiating a collaborative control negotiation process and then executes it, avoiding dangers caused by single vehicle decisions and ensuring driving safety in complex traffic scenarios.

[0067] When a vehicle determines that it meets any of the following conditions, it is identified as a high-risk scenario, triggering the collaborative control negotiation process: The risk level of the self-reflection warning has been increased. After a vehicle triggers a self-reflection warning, it sends a status confirmation request to the surrounding vehicles. If no confirmation response is received from the other party within a preset time, it means that the other party may not have detected the vehicle. The system then raises the risk level of the self-reflection warning from "medium risk" to "high risk," classifying it as a high-risk scenario.

[0068] When the perception verification confirms that there is blind spot overlap and a risk of conflict, that is, after the vehicle receives the active warning message or confirmation request information from the surrounding vehicles, it verifies its own perception results through local sensors. If it is confirmed that there is blind spot overlap between the vehicle and the other vehicle (that is, the vehicle is in the other vehicle's blind spot and the other vehicle is also in the vehicle's blind spot), and combined with the status information such as the speed, heading, and relative distance of the two vehicles, it is determined that there is a risk of collision conflict such as lane changing or parallel intersection, and it is judged as a high-risk scenario.

[0069] The determination of high-risk scenarios is strictly based on information verification between vehicles and local perception verification to ensure the accuracy of risk level classification and avoid excessive triggering of collaborative processes that may affect traffic efficiency.

[0070] In high-risk scenarios, vehicles engage in rapid negotiation with each other. In one embodiment, reaching a consensus on a cooperative avoidance strategy with the corresponding vehicle includes: based on predetermined yielding rules and road priorities, exchanging control suggestions to reach a cooperative avoidance strategy with the corresponding vehicle, whereby the control suggestions include deceleration, acceleration, or maintaining the current state.

[0071] The following section details the collaborative avoidance strategy: First, initiate negotiation. The vehicle initiating the negotiation (e.g., vehicle B) first generates a cooperative control request, which includes the vehicle's current status (e.g., position, speed, heading), a description of the risk scenario (e.g., "I am in your right rear blind spot, you are accelerating, there is a risk of collision"), and preliminary control suggestions (e.g., "I suggest you slow down and give way"), and sends it to the corresponding vehicle (e.g., vehicle A).

[0072] Then, the two vehicles exchange control suggestions. After receiving the cooperative control request, the corresponding vehicle (Vehicle A) combines its own risk assessment and driving intentions to generate a response control suggestion (such as "Agreed, I will maintain the current speed" or "I suggest I accelerate to overtake, you remain stable"), and feeds it back to the vehicle that initiated the negotiation (Vehicle B). If there is a discrepancy in the initial control suggestions between the two parties, the suggestions can be adjusted through multiple rounds of rapid interaction to ensure the efficiency of the negotiation.

[0073] Finally, a strategy is reached. During the negotiation process, both systems make decisions based on preset negotiation rules (including right-of-way rules stipulated by traffic regulations, road priorities, vehicle driving status priorities, etc.). For example, in a highway scenario, the principle of "yielding speed but not lane" is prioritized, or the avoidance priority is determined based on the vehicle's lane and speed. Through millisecond-level information exchange, both parties ultimately reach a consensus on a collaborative avoidance strategy, which includes specific action instructions for each participating vehicle (such as vehicle A maintaining speed, vehicle B decelerating to exit the blind spot, or vehicle A accelerating to overtake, vehicle B maintaining its current position, etc.).

[0074] The successful implementation of the collaborative avoidance strategy fully embodies the core concept of "peer-to-peer collaboration," avoiding unilateral decision-making by individual vehicles and ensuring the coordination and safety of avoidance maneuvers.

[0075] Once the two vehicles reach a cooperative avoidance strategy, the execution and feedback phase begins. In one embodiment, executing the cooperative avoidance strategy and providing feedback on the execution result may include: This vehicle or a higher level of autonomous driving system automatically executes cooperative avoidance strategies; Once the execution is complete, the executing vehicle broadcasts the execution result and simultaneously notifies surrounding vehicles to lift the warning.

[0076] Optionally, the driver can manually execute the strategy based on the prompts; if the vehicle has advanced autonomous driving capabilities, the system can directly convert the cooperative avoidance strategy into control commands, which will be executed automatically by the autonomous driving system without driver intervention.

[0077] After the strategy is executed, the executing vehicle broadcasts the execution result (such as "current speed maintained" or "decelerated to 80km / h, out of blind spot") to relevant surrounding vehicles. After receiving the execution result, the relevant vehicles verify the change in blind spot status (such as confirming that the other party has left their blind spot and the collision risk has been eliminated), and then deactivate the corresponding active warning or self-reflection warning, ending the current collaborative control process.

[0078] By employing a closed-loop logic of "negotiation-execution-feedback," the effective implementation of collaborative avoidance strategies is ensured. This not only prevents dangers caused by inconsistent driver responses but also enables precise cancellation of warnings through timely feedback, improving the safety and efficiency of overall traffic flow. Furthermore, this process provides feasible technical support for conflict-free collaboration in future connected autonomous vehicles, enhancing the distributed safety redundancy system.

[0079] This invention provides a vehicle-to-vehicle cooperative blind spot two-way warning method. It periodically broadcasts its own status information and blind spot model; based on the received status information and blind spot model from surrounding vehicles, it calculates whether surrounding vehicles are within its own blind spot, and simultaneously calculates whether its own vehicle is within the blind spots of surrounding vehicles; if a surrounding vehicle is detected to be within its blind spot, it sends an active warning message to the corresponding surrounding vehicle; if it determines that its own vehicle is within the blind spot of a surrounding vehicle, it triggers an introspective warning and sends a confirmation request to the corresponding surrounding vehicle, requesting confirmation of whether its own vehicle is within its blind spot; it receives active warning messages or confirmation requests from surrounding vehicles and performs a cooperative avoidance response. This invention, through two-way risk perception, informs other vehicles "you are in my blind spot" and also informs itself "I am in someone else's blind spot." The warning information originates from mutual calculation and confirmation, effectively eliminating information barriers, significantly reducing false alarm rates, enhancing driver trust in system prompts, and improving warning response efficiency. Each vehicle is equipped with both "external warning" and "internal self-reflection" capabilities, and can adapt to the real-time changes in the vehicle's role in complex traffic (such as from "blind spot creator" to "blind spot victim") without switching modes, adapting to diverse scenario needs such as parallel driving on highways and lane changing on urban roads.

[0080] This invention breaks away from the reliance of traditional blind spot monitoring systems on the perception of a single vehicle, forming a dual insurance of "self-detection + other vehicle self-reflection". Even if the sensor of one vehicle fails or misses a detection, another vehicle can still identify the risk and draw the other's attention through "self-reflection warning + confirmation request", which greatly reduces the probability of warning failure due to the failure of a single perception and improves the reliability of the system.

[0081] This invention accurately identifies high-risk scenarios through a confirmation request mechanism and avoids blind decision-making by individual vehicles by combining coordinated avoidance responses. Vehicles can form smooth and coordinated avoidance actions based on consensus, reducing the risk of collisions caused by inconsistent driver responses, while avoiding unnecessary rapid acceleration and deceleration, thus ensuring the stability and continuity of traffic flow.

[0082] The closed-loop logic of "state broadcasting - bidirectional computation - information verification - collaborative response" implemented in this invention constructs a core interactive framework for cooperation among connected vehicles. It can seamlessly connect with high-level autonomous driving systems, providing key technical support for future scenarios such as multi-vehicle conflict-free collaborative lane changing and overtaking, and promoting technological upgrades in the field of intelligent transportation.

[0083] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0084] The following are device embodiments of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0085] Figure 2 A schematic diagram of a vehicle-to-vehicle cooperative blind spot two-way warning device according to an embodiment of the present invention is shown. For ease of explanation, only the parts related to the embodiment of the present invention are shown, and are described in detail below: like Figure 2 As shown, the vehicle-to-vehicle cooperative blind spot two-way warning device is applied to each vehicle participating in the cooperation and includes: broadcast module 21, calculation module 22, warning module 23 and processing module 24.

[0086] Broadcast module 21 is used to periodically broadcast its own status information and blind spot model; The calculation module 22 is used to calculate whether the surrounding vehicles are within the blind spot of the vehicle based on the received status information broadcast by the surrounding vehicles and the blind spot model, and at the same time calculate whether the vehicle is within the blind spot of the surrounding vehicles. The warning module 23 is used to send an active warning message to the corresponding surrounding vehicles if it detects that the surrounding vehicles are in the blind spot of the vehicle; if it determines that the vehicle is in the blind spot of the surrounding vehicles, it triggers a self-reflection warning and sends a confirmation request message to the corresponding surrounding vehicles. The confirmation request message is a message requesting the corresponding vehicle to confirm whether the vehicle is in its blind spot. The processing module 24 is used to receive proactive warning messages or confirmation request information sent by surrounding vehicles and to perform coordinated avoidance responses.

[0087] In one possible implementation, the blind spot model is a dataset of geographic coordinates of the blind spot polygon calculated based on the vehicle body size and heading angle. The calculation module 22 calculates whether surrounding vehicles are within the vehicle's blind spot based on the received status information broadcast by surrounding vehicles and the blind spot model. Simultaneously, when calculating whether the vehicle is within the blind spot of surrounding vehicles, it is used for: It receives status information and blind spot models broadcast by surrounding vehicles, determines its relative position to surrounding vehicles based on the status information, and calculates whether surrounding vehicles are within its blind spot based on its own blind spot model. At the same time, it calculates whether its own vehicle is within the blind spot of surrounding vehicles based on the blind spot models of surrounding vehicles.

[0088] In one possible implementation, before the broadcast module 21 periodically broadcasts its own status information and blind spot model, the processing module 24 is also used to: synchronize the time of each vehicle.

[0089] In one possible implementation, after determining that the vehicle is in the blind spot of surrounding vehicles, the warning module 23 triggers an introspective warning and sends confirmation request information to the corresponding surrounding vehicles, it is further used for: If no perception confirmation response is received from the corresponding vehicle, the risk level will be raised.

[0090] In one possible implementation, when processing module 24 receives proactive warning messages or confirmation request information from surrounding vehicles and performs a cooperative avoidance response, it is used to: After receiving proactive warning messages from surrounding vehicles, the system verifies the perception results and, based on the verified perception results, issues a warning to the driver of the vehicle. After receiving the confirmation request, it verifies its own perception results and sends a perception confirmation reply to the sender.

[0091] In one possible implementation, the processing module 24 is further configured to: If the risk level of the self-introspection warning is increased, or if the self-perception result is verified to indicate that there is blind spot overlap and conflict risk, the current situation is determined to be a high-risk scenario, and the collaborative control negotiation process is initiated to reach a consensus on the collaborative avoidance strategy with the corresponding vehicle; the collaborative avoidance strategy is executed and the execution result is fed back.

[0092] In one possible implementation, when the processing module 24 reaches a cooperative avoidance strategy with the corresponding vehicle, it is used for: Based on predetermined yield rules and road priorities, a cooperative avoidance strategy is achieved with the corresponding vehicle by exchanging control suggestions, which may include deceleration, acceleration, or maintaining the current state.

[0093] In one possible implementation, when the processing module 24 executes the cooperative avoidance strategy and reports the execution result, it is used for: This vehicle or a higher level of autonomous driving system automatically executes cooperative avoidance strategies; Once the execution is complete, the executing vehicle broadcasts the execution result and simultaneously notifies surrounding vehicles to lift the warning.

[0094] The above embodiment provides a vehicle-to-vehicle cooperative blind spot bidirectional warning device. A broadcast module periodically broadcasts its own status information and blind spot model. A calculation module calculates whether surrounding vehicles are within the vehicle's blind spot based on the received status information and blind spot model from surrounding vehicles, and simultaneously calculates whether the vehicle is within the blind spots of surrounding vehicles. If a surrounding vehicle is detected in the vehicle's blind spot, the warning module sends an active warning message to the corresponding surrounding vehicle. If the vehicle is determined to be within the blind spot of a surrounding vehicle, a self-reflection warning is triggered, and a confirmation request is sent to the corresponding surrounding vehicle requesting confirmation of whether the vehicle is within its blind spot. A processing module receives the active warning message or confirmation request from surrounding vehicles and performs a cooperative avoidance response. This embodiment of the invention, through bidirectional perception of risk status, informs other vehicles "you are in my blind spot" and also informs the user "I am in someone else's blind spot." The warning information originates from mutual calculation and confirmation, effectively eliminating information barriers, significantly reducing false alarm rates, enhancing driver trust in system prompts, and improving warning response efficiency. Each vehicle is equipped with both "external warning" and "internal self-reflection" capabilities, and can adapt to the real-time changes in the vehicle's role in complex traffic (such as from "blind spot creator" to "blind spot victim") without switching modes, adapting to diverse scenario needs such as parallel driving on highways and lane changing on urban roads.

[0095] This invention breaks away from the reliance of traditional blind spot monitoring systems on the perception of a single vehicle, forming a dual insurance of "self-detection + other vehicle self-reflection". Even if the sensor of one vehicle fails or misses a detection, another vehicle can still identify the risk and draw the other's attention through "self-reflection warning + confirmation request", which greatly reduces the probability of warning failure due to the failure of a single perception and improves the reliability of the system.

[0096] This invention accurately identifies high-risk scenarios through a confirmation request mechanism and avoids blind decision-making by individual vehicles by combining coordinated avoidance responses. Vehicles can form smooth and coordinated avoidance actions based on consensus, reducing the risk of collisions caused by inconsistent driver responses, while avoiding unnecessary rapid acceleration and deceleration, thus ensuring the stability and continuity of traffic flow.

[0097] The closed-loop logic of "state broadcasting - bidirectional computation - information verification - collaborative response" implemented in this invention constructs a core interactive framework for cooperation among connected vehicles. It can seamlessly connect with high-level autonomous driving systems, providing key technical support for future scenarios such as multi-vehicle conflict-free collaborative lane changing and overtaking, and promoting technological upgrades in the field of intelligent transportation.

[0098] Figure 3 This is a schematic diagram of the device provided in an embodiment of the present invention. Figure 3As shown, the device 3 in this embodiment includes a processor 30 and a memory 31. The memory 31 stores a computer program 32. When the processor 30 executes the computer program 32, it implements the steps in the various method embodiments described above. Alternatively, when the processor 30 executes the computer program 32, it implements the functions of each module / unit in the various device embodiments described above.

[0099] For example, computer program 32 may be divided into one or more modules / units, which are stored in memory 31 and executed by processor 30 to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of computer program 32 in device 3.

[0100] Device 3 may include, but is not limited to, processor 30 and memory 31. Those skilled in the art will understand that... Figure 3 This is merely an example of device 3 and does not constitute a limitation on device 3. It may include more or fewer components than shown, or combine certain components, or different components. For example, device 3 may also include input / output devices, network access devices, buses, etc.

[0101] The processor 30 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0102] The memory 31 can be an internal storage unit of the device 3, such as a hard disk or RAM of the device 3. The memory 31 can also be an external storage device of the device 3, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the device 3. Furthermore, the memory 31 can include both internal and external storage units of the device 3. The memory 31 is used to store the computer program 32 and other programs and data required by the device 3. The memory 31 can also be used to temporarily store data that has been output or will be output.

[0103] For the sake of simplicity and clarity, only the above-described functional modules / units are used as examples. In practical applications, the functions described above can be assigned to different functional modules / units as needed. These modules / units can be implemented in hardware, software, or a combination of both.

[0104] This invention also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the methods described in the above-described method embodiments.

[0105] This invention also provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the methods described in the above-described method embodiments.

[0106] Computer programs include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. Computer-readable media can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0107] In the above embodiments, the descriptions of each embodiment have their own emphasis. Parts not detailed or described in a particular embodiment can be referred to in the relevant descriptions of other embodiments. Unless otherwise specified or in conflict with logic, the terminology and / or descriptions between different embodiments are consistent and can be referenced interchangeably. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0108] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A vehicle-to-vehicle cooperative blind spot two-way warning method, characterized in that, Applied to all vehicles participating in the collaboration, including: Periodically broadcast its own state information and blind spot model; Based on the status information broadcast by surrounding vehicles and the blind spot model, calculate whether surrounding vehicles are within the blind spot of this vehicle, and at the same time calculate whether this vehicle is within the blind spot of surrounding vehicles. If a vehicle is detected to be in the blind spot of another vehicle, an active warning message is sent to the corresponding vehicle. If it is determined that the vehicle is in the blind spot of another vehicle, an introspective warning is triggered, and a confirmation request is sent to the corresponding vehicle. The confirmation request is a request for the corresponding vehicle to confirm whether the vehicle is in its blind spot. It receives proactive warning messages or confirmation requests from surrounding vehicles and responds in a coordinated manner to avoid them.

2. The vehicle-to-vehicle cooperative blind spot two-way warning method according to claim 1, characterized in that, The blind spot model is a dataset of geographic coordinates of the blind spot polygons calculated based on the vehicle body size and heading angle. The step of calculating whether surrounding vehicles are within the vehicle's blind spot based on the received status information broadcast by surrounding vehicles and the blind spot model, and simultaneously calculating whether the vehicle is within the blind spot of surrounding vehicles, includes: The vehicle receives the status information and blind spot model broadcast by surrounding vehicles, determines its relative position to surrounding vehicles based on the status information, and calculates whether surrounding vehicles are within its blind spot based on its own blind spot model. At the same time, it calculates whether its own vehicle is within the blind spot of surrounding vehicles based on the blind spot models of surrounding vehicles.

3. The vehicle-to-vehicle cooperative blind spot two-way warning method according to claim 2, characterized in that, Before periodically broadcasting its own state information and blind spot model, it also includes: All vehicles synchronize their time.

4. The vehicle-to-vehicle cooperative blind spot two-way warning method according to any one of claims 1-3, characterized in that, If the system determines that the vehicle is in the blind spot of surrounding vehicles, triggers a self-monitoring warning, and sends confirmation request information to the corresponding surrounding vehicles, it also includes: If no perception confirmation response is received from the corresponding vehicle, the risk level is raised.

5. The vehicle-to-vehicle cooperative blind spot two-way warning method according to claim 4, characterized in that, The step of receiving proactive warning messages or confirmation request information sent by surrounding vehicles and responding in a coordinated avoidance manner includes: After receiving the proactive warning message sent by surrounding vehicles, the system verifies the perception results and issues a warning to the driver of the vehicle based on the verified perception results. After receiving the confirmation request information, it verifies its own perception results and replies with a perception confirmation reply to the sender.

6. The vehicle-to-vehicle cooperative blind spot two-way warning method according to claim 5, characterized in that, If the risk level of the self-introspection warning is increased, or if the self-perception result is verified to indicate that there is blind spot overlap and conflict risk, the current situation is determined to be a high-risk scenario, and the collaborative control negotiation process is initiated to reach a consensus on the collaborative avoidance strategy with the corresponding vehicle. Execute the cooperative avoidance strategy and provide feedback on the execution results.

7. The vehicle-to-vehicle cooperative blind spot two-way warning method according to claim 6, characterized in that, A coordinated avoidance strategy agreed upon with the corresponding vehicle includes: Based on predetermined yield rules and road priorities, a cooperative avoidance strategy is achieved with the corresponding vehicle by exchanging control suggestions, which include deceleration, acceleration, or maintaining the current state.

8. The vehicle-to-vehicle cooperative blind spot two-way warning method according to claim 7, characterized in that, Execute the cooperative avoidance strategy and provide feedback on the execution results, including: The vehicle or a higher level of autonomous driving system automatically executes the aforementioned cooperative avoidance strategy; Once the execution is complete, the executing vehicle broadcasts the execution result and simultaneously notifies surrounding vehicles to lift the warning.

9. A vehicle-to-vehicle cooperative blind spot bidirectional warning device, characterized in that, Applied to all vehicles participating in the collaboration, including: The broadcast module is used to periodically broadcast its own status information and blind spot model; The calculation module is used to calculate whether the surrounding vehicles are within the blind spot of the vehicle, and at the same time calculate whether the vehicle is within the blind spot of the surrounding vehicles, based on the status information broadcast by the surrounding vehicles and the blind spot model. The warning module is used to send an active warning message to the corresponding surrounding vehicles if it detects that the vehicle is in the blind spot of the vehicle; if it determines that the vehicle is in the blind spot of the surrounding vehicles, it triggers an introspection warning and sends a confirmation request message to the corresponding surrounding vehicles. The confirmation request message is a request for the corresponding vehicle to confirm whether the vehicle is in its blind spot. The processing module is used to receive proactive warning messages or confirmation requests from surrounding vehicles and to respond in a coordinated avoidance manner.

10. A device, characterized in that, It includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method as described in any one of claims 1 to 8.

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