Internet of vehicles emergency information dynamic broadcast and multi-vehicle cooperative response system and method

Abstract

The invention provides an Internet of Vehicles emergency information dynamic broadcast and multi-vehicle cooperative response system. The system comprises at least one vehicle in distress equipped with a vehicle-mounted terminal, a plurality of peripheral cooperative vehicles equipped with vehicle-mounted terminals, a cloud platform, a vehicle database and a sensor. The invention also provides a collaborative response method. The method comprises the following steps: S1, emergency detection and help-seeking triggering; s2, uploading help request information to a cloud platform; s3, dynamically matching surrounding response vehicles; s4, broadcasting help information in a grading manner; s5, response feedback processing is carried out; s6, rescue coordination and notification; and S7, dynamically updating and ending. The system is timely in response, efficient in cooperation, high in safety and compatible and extensive; the rescue process is more efficient and orderly; and the broadcast range and frequency are dynamically adjusted, so that enough surrounding vehicles can timely obtain help information, and interference is avoided.

Description

Technical Field

[0001] This invention relates to the field of vehicle networking (intelligent transportation) technology, and in particular to a vehicle networking emergency assistance information dynamic broadcasting and multi-vehicle collaborative response system and method. Background Technology

[0002] Currently, when a vehicle encounters an emergency such as an accident, breakdown, or sudden health problem for the driver while driving, common methods of seeking help include the driver calling public roadside assistance, activating hazard lights to warn nearby vehicles, or contacting a rescue center through the vehicle's built-in emergency call system. However, these traditional methods have shortcomings in terms of response speed and coverage. On the one hand, making a phone call requires manual operation, and waiting for professional rescue often takes a long time; on the other hand, hazard lights can only warn nearby vehicles to give way, and cannot actively solicit assistance from others. At the same time, existing in-vehicle emergency call systems mainly send accident information to a back-end service center, failing to fully utilize the readily available social rescue resource of nearby vehicles.

[0003] With the development of vehicle-to-everything (V2X) technology, real-time data sharing between vehicles and between vehicles and the cloud offers a new approach to solving the aforementioned problems. By sharing vehicle location and status information in real time, it is possible to build a collaborative mechanism that allows vehicles in distress to dynamically broadcast their distress requests to nearby vehicles, thereby obtaining timely assistance from multiple parties. However, current technologies lack such an effective collaborative processing mechanism for emergency distress information. Without unified coordination, a single vehicle in distress may struggle to promptly notify all potential helpers, and surrounding vehicles may not be able to perceive specific distress requests in a timely manner. Existing V2X applications focus more on traffic information services and collision warnings; how to achieve proactive collaborative rescue between vehicles in emergency situations remains a pressing technical problem to be solved. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by proposing a communication method and system that utilizes an in-vehicle terminal and a cloud platform to dynamically broadcast distress information and coordinate multi-vehicle responses when a vehicle encounters an emergency.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A vehicle-to-everything (V2X) emergency assistance information dynamic broadcasting and multi-vehicle collaborative response system includes at least one distressed vehicle equipped with an in-vehicle terminal, several surrounding collaborative vehicles equipped with in-vehicle terminals, a cloud platform, a vehicle database, and sensors. The vehicle-mounted terminal is used to detect vehicle emergency status, send help requests, receive and display help information or notification instructions issued by the cloud platform, and allow people in the vehicle to interact with it. The cloud platform is used to receive and process distress requests from vehicles in distress, filter and identify surrounding vehicles within the target broadcast range in real time and send distress information to them, receive and coordinate feedback information from responding vehicles, and then coordinate and notify relevant parties to complete the rescue process. The vehicle-mounted terminal is connected to the cloud platform via wireless communication; The sensor is installed on the vehicle, and the vehicle terminal interacts with the sensor and receives sensor signals. The vehicle database transmits information to the cloud platform. The vehicle database stores real-time vehicle information, including vehicle identification, real-time location coordinates, and status, which includes online and offline status.

[0006] Furthermore, the vehicle-mounted terminal includes an emergency state detection module, a positioning module, a wireless communication module, and a vehicle-mounted human-machine interaction unit; the emergency state detection module is connected to the sensor and is used to detect emergency events; the positioning module is used to obtain the current location of the vehicle; the wireless communication module is used to interact with the cloud platform; and the vehicle-mounted human-machine interaction unit is used for the driver to perform interactive operations. The cloud platform includes a location matching module, a message broadcasting module, a response processing module, and a data storage module; The calculation and matching module is used to calculate and match surrounding responding vehicles to obtain the target responding vehicle; The message broadcast module is used to push out requests for help and information on the rescue response. The response processing module is used to receive and coordinate feedback information from response vehicles and coordinate with relevant parties to complete the rescue process; The data storage module is used to store broadcast information tables and real-time vehicle information.

[0007] Furthermore, the broadcast information form includes the type of emergency, a description of the type of emergency, the level of urgency, and the estimated time required for rescue. The vehicle registration information form includes vehicle identification, vehicle color and model, vehicle type, special equipment configuration, driver's name, contact number, and driver qualifications; The vehicle types include small cars, heavy-duty semi-trailer tractors, special-purpose vehicles, and pure electric vehicles; special-purpose vehicles include medical vehicles, fire trucks, and trailers. The dedicated equipment configuration record shows whether it includes medical emergency equipment; The driver's qualifications record the type of rescue experience the driver possesses, including first aid experience and practical experience in roadside assistance.

[0008] A method for dynamic broadcasting of emergency assistance information and multi-vehicle collaborative response in vehicle-to-everything (V2X) networks, based on a V2X emergency assistance information dynamic broadcasting and multi-vehicle collaborative response system, includes the following steps: S1: Emergency Detection and Help Trigger; In an emergency requiring external assistance, the vehicle-mounted terminal detects relevant sensor signals or the occupants manually trigger a help command, and the vehicle-mounted terminal responds to the sensor signals or help command to generate help request data. S2: Request for assistance information is uploaded to the cloud platform; The vehicle-mounted terminal will send the generated emergency request data to the cloud platform via a wireless communication network; S3: Dynamically match nearby responding vehicles; After receiving a distress request, the cloud platform retrieves other online vehicles within a preset range from the currently online vehicle information in the vehicle database as responding vehicles, based on the real-time location of the distressed vehicle. S4: Tiered broadcast of emergency information; The cloud platform adopts a hierarchical broadcasting mechanism. First, it pushes the help request information to the selected responding vehicles. If there are not enough responses within the initial broadcast range, it expands the broadcast radius to obtain responding vehicles within the range and sends the help request information to the newly added responding vehicles within the range. S5: Response feedback processing; After receiving the distress message, the onboard terminal of a nearby responding vehicle will remind the driver on the human-machine interface. If the driver of a responding vehicle confirms that he is willing to provide assistance, he will send a response feedback to the cloud platform through the onboard terminal of the responding vehicle. When the cloud platform receives a response feedback from at least one nearby vehicle, it will stop broadcasting new distress messages to vehicles in a wider range and select the main rescue vehicle. S6: Rescue Coordination and Notification; The cloud platform obtains detailed information about the main rescue vehicles, pushes the detailed information of the main rescue vehicles to the vehicle in distress, and sends a status update that "the rescue mission has been accepted" to other nearby response vehicles that have received the distress call. S7: Dynamic update and termination; During the rescue process, the cloud platform dynamically adjusts the broadcast range and content of the distress information based on changes in the location of the distressed vehicle or the situation on site. After the rescue is completed, in response to the confirmation operation of the distressed vehicle or the rescue vehicle, the cloud platform stops broadcasting the relevant information and marks the event as closed.

[0009] Furthermore, step S3 includes: S31: Initial range filtering; The cloud platform responds to the distress request, obtains the real-time location coordinates of the distressed vehicle, sets the initial broadcast radius R0 (default is 3 kilometers), obtains real-time vehicle information from the vehicle database, and retrieves all candidate vehicles that are currently online and located within the circular area: it filters out all online vehicles from the real-time vehicle information, then calculates the straight-line distance between each online vehicle and the distressed vehicle based on the location coordinates of the online vehicles, filters out vehicles with a distance ≤ R0, obtains all candidate vehicles, and creates a new list of the filtered candidate vehicles to obtain the initial candidate vehicle list; S32: Distance weight calculation; Calculate the distance from the candidate vehicle to the vehicle in distress, and convert the distance into weights; Obtain the real-time location coordinates of the candidate vehicles, calculate the distance between the real-time location coordinates of the distressed vehicle and the real-time location coordinates of the candidate vehicles, and convert the distance into a weight: DistanceWeight(i) = 1 / (1+Distance(i) / 1000), and iterate through all candidate vehicles to obtain the distance weights between them and the distressed vehicle. S33: Relative driving direction assessment; Obtain the driving direction vectors of the distressed vehicle and all candidate vehicles respectively, and calculate the cosine of the angle between the driving direction vectors of the distressed vehicle and each candidate vehicle as the direction correlation coefficient DirectionScore(i). S34 driving status assessment; Obtain the real-time speed of the candidate vehicle, adjust the driving speed based on the real-time road conditions to obtain the effective driving speed of the candidate vehicle, and obtain the estimated arrival time EstimatedTime(i) based on the effective driving speed. S35: Overall score ranking; Calculate the overall matching score for each candidate vehicle: Score(i) = α×DirectionScore(i) + β×DistanceWeight(i) + γ×(1 / EstimatedTime(i)), where α=0.4, β=0.3, and γ=0.3 are weighting coefficients; select the top 5-8 vehicles as the most suitable response vehicles.

[0010] Furthermore, S33 includes: S331: Obtain the driving direction vector; The positioning module periodically collects location data to obtain the position coordinates of the distressed vehicle and each candidate vehicle at two consecutive sampling time points after the initial range filtering is completed. The position coordinates of the later time are subtracted from the position coordinates of the previous time to obtain the driving direction vectors of the distressed vehicle and the candidate vehicle, respectively. S332: Calculate the directional correlation coefficient; The directional correlation coefficient is obtained by calculating the cosine of the vector between the direction of travel of the distressed vehicle and the direction of travel of each candidate vehicle.

[0011] Furthermore, it also includes: S341: Calculate the real-time speed of the candidate vehicle: Obtain the real-time speed by dividing the magnitude of the candidate vehicle's driving direction vector by the time interval between two consecutive sampling points. S342: Obtain correction coefficient based on real-time traffic conditions: The cloud platform sends a request to the traffic data platform to obtain traffic data. The traffic data platform responds to the request and returns response data, which includes traffic conditions, congestion level, and sets the correction coefficient corresponding to the congestion level. S343: Calculate the effective driving speed of candidate vehicles: Obtain the effective driving speed of candidate vehicles by multiplying the real-time speed of candidate vehicles by the corresponding road condition correction factor; S344: Obtain the estimated arrival time: The estimated arrival time is obtained by dividing the calculated distance from the candidate vehicle to the distressed vehicle by the effective speed of the candidate vehicle.

[0012] Furthermore, step S5 includes: S51: Response information generation; After receiving the distress message, the vehicle-mounted terminal of a nearby vehicle displays the distress details on the interface of the human-machine interaction unit and issues an audio and visual reminder. If the driver confirms that he is willing to provide assistance, the vehicle-mounted terminal responds to the driver's confirmation operation, collects the location of the responding vehicle, obtains the vehicle identifier and driver's basic information from the vehicle registration information table, and calls the navigation engine to calculate the estimated arrival time based on the current traffic conditions. The driver's basic information includes the driver's name and contact number. S52: Response priority determination, select the primary rescue vehicle; The cloud platform receives response feedback, obtains the estimated arrival time, and prioritizes vehicles based on their vehicle identification, vehicle type, special equipment configuration, and driver qualifications from the vehicle registration information table; the top 1-2 vehicles are selected as the main rescue vehicles. S53: Broadcast control mechanism: When a sufficient number of valid responses are received, stop expanding the broadcast radius and continue sending distress messages to vehicles outside the current broadcast range.

[0013] Furthermore, S52 specifically involves assigning 20 points to vehicles with medical first-aid kits or towing capabilities based on vehicle type and specialized equipment configuration, and 0 points to those without. Drivers with relevant rescue experience are also assigned 20 points, and 0 points otherwise. The estimated arrival time of the responding vehicles is obtained, and these vehicles are sorted in descending order of estimated arrival time, with points assigned sequentially from 1 to N, where N is the number of responding vehicles. All scores for each responding vehicle are summed to calculate a comprehensive score. Based on the comprehensive score, the responding vehicles are prioritized, and the top 1-2 vehicles with the highest comprehensive scores are designated as primary rescue vehicles.

[0014] Furthermore, step S7 includes: S71: On-site situation monitoring: Real-time assessment of the on-site situation based on the sensors of the distressed vehicle and the on-site images / videos fed back by the rescue vehicle, to determine whether the on-site situation is deteriorating; when the following situations are detected, the situation is determined to be deteriorating: abnormal vital signs of the occupants, vehicle fire or fuel leak, secondary collision, or rescue vehicle reports a complex scene. S72: Dynamic Range Adjustment: If the situation worsens or the need for rescue increases, the broadcast radius is expanded to R2=2×R0, and the request for help is updated and marked as "emergency escalation". A request for reinforcements is sent to vehicles within the new range. S73: Location Tracking Update: If the location of the distressed vehicle changes and the distance moved exceeds 100 meters, the location information will be updated immediately and all vehicles involved in the rescue will be notified. S74: Rescue Completion Confirmation: In response to the completion confirmation operation of the distressed vehicle or the rescue vehicle, when the cloud platform receives the "rescue completed" confirmation from the distressed vehicle or the rescue vehicle reports "mission completed", it stops broadcasting all relevant information, records the rescue process data, and sends a thank-you notification to the participating vehicles.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. Timely response: By using the cloud platform to match nearby vehicles in real time and broadcast help information, the time for distressed vehicles to receive assistance is greatly shortened, social rescue forces are introduced at the first time, and the response speed in emergency situations is improved.

[0016] 2. Collaborative and efficient: The system intelligently selects the most suitable assistance vehicle and coordinates multiple vehicle responses, avoiding disorderly requests for help or redundant rescue by multiple people, making the rescue process more efficient and orderly.

[0017] 3. Dynamic coverage: Through unified coordination in the cloud, the broadcast range and frequency can be dynamically adjusted as needed, ensuring that enough surrounding vehicles receive the distress information in a timely manner, while avoiding interference from vehicles that are too far away receiving irrelevant information.

[0018] 4. Enhanced safety: When surrounding vehicles receive timely information about an accident, they can not only participate in the rescue but also take safety measures such as slowing down and detouring in advance, reducing the risk of secondary accidents and improving the overall safety level of the road traffic environment.

[0019] 5. Compatibility and Expansion: The collaborative mechanism of this invention can be integrated with existing emergency rescue systems. For example, it can automatically notify professional rescue organizations when no response is received from civilian vehicles for an extended period, forming a multi-layered emergency response network where public mutual assistance and professional rescue complement each other. Furthermore, this mechanism is universally applicable to communication methods and vehicle types, and can be extended to more scenarios. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating the steps of a method for dynamic broadcasting of emergency assistance information and multi-vehicle collaborative response in the Internet of Vehicles according to the present invention. Figure 2 This is a schematic diagram illustrating the principle of a method for dynamic broadcasting of emergency assistance information and multi-vehicle collaborative response in the Internet of Vehicles according to the present invention. Figure 3 This is a schematic diagram of the processing flow of a method for dynamic broadcasting of emergency assistance information and multi-vehicle collaborative response in the Internet of Vehicles according to the present invention; Detailed Implementation

[0021] To provide a further understanding of the purpose, structure, features, and functions of the present invention, detailed descriptions are provided below with reference to specific embodiments.

[0022] A method for dynamic broadcasting of emergency assistance information and multi-vehicle collaborative response in the Internet of Vehicles (IoV) is based on an IoV emergency assistance information dynamic broadcasting and multi-vehicle collaborative response system. The system includes: at least one distressed vehicle equipped with an on-board terminal, several surrounding collaborative vehicles equipped with on-board terminals, a cloud platform, a vehicle database, and sensors, etc. The vehicle-mounted terminal is used to detect vehicle emergency conditions, send help requests, receive and display help information or notification instructions sent from the cloud, and allow people in the vehicle to interact with it. The cloud platform is used to receive and process distress requests from vehicles in distress, filter and identify surrounding vehicles within the target broadcast range in real time and send distress information to them, receive and coordinate feedback information from responding vehicles, and then coordinate and notify relevant parties to complete the rescue process.

[0023] The sensor is installed on the vehicle, and the vehicle terminal interacts with the sensor, receiving sensor signals.

[0024] The sensors include collision sensors, airbag deployment sensors, in-vehicle cameras, microphones, vital signs monitoring devices, etc.; the vehicle terminal is connected to the cloud platform via wireless communication (such as cellular mobile data or dedicated vehicle network communication).

[0025] The vehicle-mounted terminal includes components such as an emergency state detection module, a positioning module, a wireless communication module, and a vehicle-mounted human-machine interaction unit. The emergency state detection module is connected to the sensor and is used to detect emergency events. The positioning module is used to obtain the current location of the vehicle. The wireless communication module is used to interact with the cloud platform. The vehicle-mounted human-machine interaction unit is used for the driver to perform interactive operations.

[0026] The cloud platform includes a location matching module, a message broadcasting module, a response processing module, and a data storage module, etc. The calculation and matching module is used to calculate and match surrounding responding vehicles to obtain the target responding vehicle; The message broadcast module is used to push out information such as requests for help and rescue response status; The response processing module is used to receive and coordinate feedback information from response vehicles and coordinate with relevant parties to complete the rescue process; The data storage module is used to store broadcast information tables and real-time vehicle information, etc. The broadcast information table includes the type of emergency, a description of the type of emergency, the level of urgency, and the estimated time required for rescue.

[0027] The vehicle registration information form includes vehicle identification, vehicle color and model, vehicle type, special equipment configuration, driver's name, contact number, driver's qualifications, etc. The vehicle types mentioned include small cars, heavy semi-trailer tractors, special-purpose vehicles, pure electric vehicles, etc. Special-purpose vehicles include medical vehicles, fire trucks, tow trucks, etc., which are used to determine whether a vehicle has the corresponding rescue capabilities, such as medical emergency capabilities, towing capabilities, etc., based on the vehicle type.

[0028] The dedicated equipment configuration record shows whether it includes medical emergency equipment; The driver's qualifications record what kind of rescue experience the driver has, such as first aid experience, roadside assistance experience, etc.

[0029] The vehicle database transmits information to the cloud platform. The vehicle database stores real-time vehicle information, including vehicle identification, real-time location coordinates (longitude and latitude), and status fields. Status includes online, offline, etc.

[0030] Includes the following steps: S1: Emergency Detection and Help Trigger; When a vehicle is involved in an emergency requiring external assistance, such as a collision, a serious malfunction, or a sudden illness of a passenger, the onboard terminal automatically detects relevant sensor signals (such as collision sensors, airbag deployment, etc.) or the passenger manually triggers a help command. The onboard terminal then responds to the sensor signals or the help command to generate help request data. The data for a distress call includes the vehicle's current location, the type of emergency, and the vehicle's identification number. The vehicle's current location (latitude and longitude) is obtained by the onboard positioning module.

[0031] Emergency event types are determined by sensor signals or manual selection; A vehicle identification number (VIN) is a unique identifier used to distinguish different vehicles, such as a license plate number. The VIN is directly linked to the vehicle's onboard terminal.

[0032] S2: Request for assistance information is uploaded to the cloud platform; The vehicle-mounted terminal sends the generated help request data to the cloud platform via a wireless communication network.

[0033] S3: Dynamically match nearby responding vehicles; After receiving a distress request, the cloud platform retrieves other online vehicles within a preset range from the vehicle database's currently online vehicle information based on the distressed vehicle's real-time location as candidate response vehicles.

[0034] Specifically, it includes: S31: Initial range filtering; The cloud platform responds to the distress request, obtains the real-time location coordinates (x0, y0) of the distressed vehicle, sets an initial broadcast radius R0 (default is 3 kilometers), retrieves real-time vehicle information from the vehicle database, and searches for all candidate vehicles currently online and located within the circular area: it filters out all online vehicles from the real-time vehicle information, then calculates the straight-line distance between each online vehicle and the distressed vehicle based on the location coordinates of the online vehicles, filters out vehicles with a distance ≤ 3 kilometers, obtains all candidate vehicles, and creates a new list of the filtered candidate vehicles to obtain the initial candidate vehicle list.

[0035] S32: Distance weight calculation; Calculate the Euclidean distance from the candidate vehicle to the distressed vehicle, and convert the distance into weights.

[0036] Obtain the real-time position coordinates of the candidate vehicle, and obtain the real-time position coordinates (x, y) of candidate vehicle i. i , y i ), where i represents the i-th candidate vehicle in the initial candidate vehicle list, based on: Calculate the real-time position coordinates (x0, y0) of the distressed vehicle and the real-time position coordinates (x, y0) of candidate vehicle i. i , y iThe distance between the candidate vehicles and the distressed vehicle is calculated in meters (m). The distance is then converted into a weight: DistanceWeight(i) = 1 / (1+Distance(i) / 1000). The distance weights between all candidate vehicles and distressed vehicles are obtained by iterating through the data.

[0037] S33: Relative driving direction assessment; The driving direction vectors of the distressed vehicle and all candidate vehicles are obtained respectively, and the cosine of the angle between the driving direction vectors of the distressed vehicle and each candidate vehicle is calculated as the directional correlation coefficient. S331: Obtain the driving direction vector; Obtain the position coordinates of the distressed vehicle at two adjacent moments, subtract the coordinates of the previous moment from the coordinates of the later moment to obtain the driving direction vector of the distressed vehicle, and obtain the driving direction vectors of all candidate vehicles in the same way. The vehicle positioning module periodically collects location data to obtain the position coordinates of the distressed vehicle and each candidate vehicle at two consecutive sampling time points after the initial range screening is completed. The coordinates of the later time are subtracted from the coordinates of the previous time to obtain the driving direction vectors of the distressed vehicle and the candidate vehicle, respectively. Let t0 and t1 be two consecutive sampling time points. Obtain the position coordinates of the distressed vehicle and each candidate vehicle at the two sampling time points, respectively. Obtain the position coordinates (x, y) of the distressed vehicle at time t0. 0_0 , y 0_0 ), position at time t1 (x 0_1 ,y 0_1 Let the direction vector of the distressed vehicle be V0(v x0 , v y0 ), where v x0 = x 0_1 - x 0_0 v y0 = y 0_1 - y 0_0 .

[0038] Obtain the position coordinates (x, y) of the candidate vehicle at time t0. i_0 , y i_0 ), position at time t1 (x i_1 , y i_1 The driving direction vector of candidate vehicle i is Vᵢ(v xi , v yi ), where v xi = x i_1 - x i_0 v yi = y i_1 - y i_0 ; S332: Calculate the directional correlation coefficient; The directional correlation coefficient is obtained by calculating the cosine of the vector between the direction of travel of the distressed vehicle and the direction of travel of each candidate vehicle. The correlation coefficient ranges from [-1, 1]. The larger the value, the more consistent the directions of travel of the two vehicles are, and the faster they can reach the scene. According to the formula for calculating the directional correlation coefficient: DirectionScore(i) = cos(θ) = (V0·V i ) / (|V0||V i |) Obtain the directional correlation coefficient, where θ is the angle between the driving directions of the two vehicles.

[0039] S34 driving status assessment; Obtain the real-time speed of the candidate vehicles, adjust the driving speed based on real-time traffic conditions to obtain the effective driving speed of the candidate vehicles, and obtain the estimated arrival time based on the effective driving speed. S341: Calculate the real-time speed of the candidate vehicle: Obtain the real-time speed by dividing the magnitude of the candidate vehicle's driving direction vector by the time interval between two consecutive sampling points; Real-time speed of candidate vehicle i: .

[0040] S342: Correction coefficients are obtained based on real-time traffic conditions: The cloud platform sends requests to traffic data platforms (such as Gaode Maps, Baidu Maps API, or sensor networks of transportation departments) to obtain traffic data. The traffic data platform responds to the requests and returns response data, which includes information such as traffic conditions and congestion levels. Correction coefficients are obtained based on the congestion level, with a range of (0.3-1.0). There are five congestion levels: smooth traffic, mostly smooth traffic, light congestion, moderate congestion, and severe congestion. Correction coefficients are set for each congestion level. These can be designed as fixed values: 0.95 for smooth traffic; 0.8 for mostly smooth traffic; 0.6 for light congestion; 0.45 for moderate congestion; and 0.3 for severe congestion.

[0041] S343: Calculate the effective speed of candidate vehicles: The effective speed of candidate vehicles is obtained by multiplying their real-time speed by the corresponding road condition correction factor. That is, EffectiveSpeed(i) = Speed i × TrafficFactor(i); where TrafficFactor(i) is a correction factor based on real-time traffic conditions.

[0042] S344: Obtain the estimated arrival time: The estimated arrival time is obtained by dividing the calculated distance from the candidate vehicle to the distressed vehicle by the effective speed of the candidate vehicle. That is EstimatedTime(i) = Distance(i) / EffectiveSpeed(i).

[0043] S35: Overall score ranking; Calculate the overall matching score for each candidate vehicle: Score(i) = α×DirectionScore(i) + β×DistanceWeight(i) + γ×(1 / EstimatedTime(i)), where α=0.4, β=0.3, and γ=0.3 are weighting coefficients. Select the top 5-8 vehicles with the highest scores as the most suitable response vehicles.

[0044] This matching algorithm introduces relative driving direction evaluation, prioritizing vehicles traveling in the same or opposite direction as the distressed vehicle, significantly improving rescue arrival efficiency; at the same time, it comprehensively considers multi-dimensional evaluation of distance, time and traffic conditions to ensure that the selected vehicles have the best rescue response capabilities.

[0045] S4: Tiered broadcast of emergency information; The cloud platform adopts a hierarchical broadcasting mechanism. First, it pushes the help request information to the selected responding vehicles. If there are not enough responses within the initial broadcast range, the broadcast radius is expanded to R1=1.5×R0 to obtain the responding vehicles within the range, and then the help request information is sent to the responding vehicles in the newly added range.

[0046] The broadcast content includes the location coordinates of the distressed vehicle, a description of the type of incident, the level of urgency, the estimated duration of the rescue operation, and contact information. In response to distress requests, the cloud platform obtains the broadcast information table, and based on the emergency event type in the distress request data, obtains the event type description, urgency level, and estimated rescue duration; it also obtains the vehicle registration information table, extracts contact information and other content from the vehicle registration information table, and broadcasts the real-time location coordinates of the distressed vehicle to the responding vehicle.

[0047] Furthermore, the cloud platform generates temporary communication channel identifiers for direct communication between vehicles.

[0048] S5: Response feedback processing; After receiving the distress request, the onboard terminals of nearby responding vehicles remind the driver through the human-machine interface. If the driver of a responding vehicle confirms that he is willing to provide assistance, the responding vehicle sends a response feedback to the cloud platform through its onboard terminal. When the cloud platform receives a response feedback from at least one nearby vehicle, it stops broadcasting new distress requests to vehicles in a wider range and selects the primary rescue vehicle.

[0049] Specifically, it includes: S51: Response information generation; After receiving the distress request, the onboard terminals of nearby vehicles display the details of the distress request on the human-machine interface and issue an audio-visual alert. If the driver confirms their willingness to provide assistance, in response to the driver's confirmation, the onboard terminal collects the location of the responding vehicle, obtains the vehicle identifier and driver's basic information (name, contact number) from the vehicle registration information table, and uses the navigation engine to calculate the estimated arrival time based on the current traffic conditions. Specifically, the navigation engine is invoked to obtain multiple candidate paths from the current location of the responding vehicle to the location of the distressed vehicle based on map road network data (road grade, speed limit, etc.). Based on real-time traffic data, the estimated arrival time for each candidate path is calculated. The estimated arrival times of all candidate paths are compared, and the path with the shortest travel time is selected as the optimal path and its estimated arrival time is output. The method used by the navigation engine to plan and calculate the estimated arrival time based on actual traffic conditions is existing technology. This application merely uses this method without modifying or innovating it. The process and principle of calculating the estimated arrival time will not be elaborated upon here.

[0050] S52: Response priority determination, select the primary rescue vehicle; The cloud platform receives response feedback, obtains the estimated arrival time, and prioritizes vehicles based on their vehicle identification, vehicle registration information, vehicle type, specialized equipment configuration, and driver qualifications. Vehicles with medical first-aid kits or towing capabilities are assigned 20 points, while those without are assigned 0 points. Drivers with relevant rescue experience are assigned 20 points, otherwise 0 points. The estimated arrival time of each vehicle is obtained, and the vehicles are sorted in descending order of estimated arrival time, with points assigned sequentially from 1 to N, where N is the number of vehicles. All scores for each vehicle are summed to calculate a comprehensive score. Based on the comprehensive score, the vehicles are prioritized, and the top 1-2 vehicles with the highest comprehensive scores are designated as primary rescue vehicles.

[0051] The selection criteria are: prioritizing vehicles with the shortest estimated arrival time, those with the necessary rescue capabilities (such as first aid kits and towing capacity), and drivers with rescue experience. Individual vehicles in distress should promptly notify all potential helpers to obtain timely assistance from multiple parties.

[0052] S53: Broadcast control mechanism: When a sufficient number of valid responses are received (usually 2-3 vehicles), the broadcast radius is stopped from expanding, and the distress message is sent to vehicles outside the current broadcast range to avoid excessive response causing traffic congestion.

[0053] S6: Rescue Coordination and Notification; The cloud platform obtains detailed information about the main rescue vehicle, pushes the detailed information to the vehicle in distress, and sends a status update that "the rescue mission has been accepted" to other nearby responding vehicles that have received the distress call, thus avoiding duplicate responses.

[0054] Detailed information about the rescue vehicle, including license plate number (vehicle identification), vehicle color and model, driver's name, contact number, and estimated arrival time.

[0055] S7: Dynamic update and termination; During the rescue operation, the cloud platform dynamically adjusts the broadcast range and content of the distress call based on changes in the location of the vehicle in distress or the situation on site. Once the rescue is completed, the cloud platform stops broadcasting the relevant information and marks the event as closed.

[0056] include: S71: On-site situation monitoring: Real-time assessment of the on-site situation using onboard sensors of the distressed vehicle (such as in-vehicle cameras, microphones, vital signs monitoring equipment) and on-site images / videos fed back by rescue vehicles, to determine whether the on-site situation is deteriorating. A situation is considered deteriorating when the following conditions are detected: abnormal vital signs of occupants, vehicle fire or fuel leak, secondary collision, or rescue vehicle reports a complex on-site situation. S72: Dynamic Range Adjustment: If the situation worsens or the need for rescue increases, the broadcast radius is expanded to R2=2×R0, and the request for help is updated and marked as "emergency escalation". A request for reinforcements is sent to vehicles within the new range. S73: Location Tracking Update: If the location of the distressed vehicle changes and the distance moved exceeds 100 meters, the location information will be updated immediately and all vehicles involved in the rescue will be notified. S74: Rescue Completion Confirmation: In response to the completion confirmation operation of the distressed vehicle or the rescue vehicle, when the cloud platform receives the "rescue completed" confirmation from the distressed vehicle or the rescue vehicle reports "mission completed", it stops broadcasting all relevant information, records the rescue process data, and sends a thank-you notification to the participating vehicles.

[0057] Furthermore, if no vehicle responds, the cloud platform notifies the rescue agency to request rescue. Once the rescue is completed, the distressed vehicle confirms "rescue completed," and the cloud platform marks the event as over, thus ending the process.

[0058] The present invention has been described in the above-described embodiments; however, these embodiments are merely examples for implementing the present invention. It must be noted that the disclosed embodiments do not limit the scope of the present invention. Conversely, any modifications and refinements made without departing from the spirit and scope of the present invention are within the scope of patent protection of the present invention.

Claims

1. A vehicle-to-everything (V2X) emergency assistance information dynamic broadcasting and multi-vehicle collaborative response system, characterized in that: This includes at least one distressed vehicle equipped with an onboard terminal, several surrounding collaborative vehicles equipped with onboard terminals, a cloud platform, a vehicle database, and sensors; The vehicle-mounted terminal is used to detect vehicle emergency status, send help requests, receive and display help information or notification instructions issued by the cloud platform, and allow people in the vehicle to interact with it. The cloud platform is used to receive and process distress requests from vehicles in distress, filter and identify surrounding vehicles within the target broadcast range in real time and send distress information to them, receive and coordinate feedback information from responding vehicles, and then coordinate and notify relevant parties to complete the rescue process. The vehicle-mounted terminal is connected to the cloud platform via wireless communication; The sensor is installed on the vehicle, and the vehicle terminal interacts with the sensor and receives sensor signals. The vehicle database transmits information to the cloud platform. The vehicle database stores real-time vehicle information, including vehicle identification, real-time location coordinates, and status, which includes online and offline status.

2. The vehicle-to-everything (V2X) emergency assistance information dynamic broadcasting and multi-vehicle collaborative response system as described in claim 1, characterized in that: The vehicle-mounted terminal includes an emergency state detection module, a positioning module, a wireless communication module, and a vehicle-mounted human-machine interaction unit. An emergency state detection module is connected to the sensor to detect emergency events; a positioning module is used to obtain the vehicle's current location; a wireless communication module is used to interact with the cloud platform; and an in-vehicle human-machine interaction unit is used for the driver to perform interactive operations. The cloud platform includes a location matching module, a message broadcasting module, a response processing module, and a data storage module; The calculation and matching module is used to calculate and match surrounding responding vehicles to obtain the target responding vehicle; The message broadcast module is used to push out requests for help and information on the rescue response. The response processing module is used to receive and coordinate feedback information from response vehicles and coordinate with relevant parties to complete the rescue process; The data storage module is used to store broadcast information tables and real-time vehicle information.

3. The vehicle-to-everything (V2X) emergency assistance information dynamic broadcasting and multi-vehicle collaborative response system as described in claim 2, characterized in that: The broadcast information form includes the type of emergency, a description of the type of emergency, the level of urgency, and the estimated time required for rescue. The vehicle registration information form includes vehicle identification, vehicle color and model, vehicle type, special equipment configuration, driver's name, contact number, and driver qualifications; The vehicle types include small cars, heavy-duty semi-trailer tractors, special-purpose vehicles, and pure electric vehicles; special-purpose vehicles include medical vehicles, fire trucks, and trailers. The dedicated equipment configuration record shows whether it includes medical emergency equipment; The driver's qualifications record the type of rescue experience the driver possesses, including first aid experience and practical experience in roadside assistance.

4. A method for dynamic broadcasting of emergency assistance information and multi-vehicle collaborative response in a vehicle-to-everything (V2X) network, based on the V2X dynamic broadcasting of emergency assistance information and multi-vehicle collaborative response system according to any one of claims 1-3, characterized in that: Includes the following steps: S1: Emergency Detection and Help Trigger; In an emergency requiring external assistance, the vehicle-mounted terminal detects relevant sensor signals or the occupants manually trigger a help command, and the vehicle-mounted terminal responds to the sensor signals or help command to generate help request data. S2: Request for assistance information is uploaded to the cloud platform; The vehicle-mounted terminal will send the generated emergency request data to the cloud platform via a wireless communication network; S3: Dynamically match nearby responding vehicles; After receiving a distress request, the cloud platform retrieves other online vehicles within a preset range from the currently online vehicle information in the vehicle database as responding vehicles, based on the real-time location of the distressed vehicle. S4: Tiered broadcast of emergency information; The cloud platform adopts a hierarchical broadcasting mechanism. First, it pushes the help request information to the selected responding vehicles. If there are not enough responses within the initial broadcast range, it expands the broadcast radius to obtain responding vehicles within the range and sends the help request information to the newly added responding vehicles within the range. S5: Response feedback processing; After receiving the distress message, the onboard terminal of a nearby responding vehicle will remind the driver on the human-machine interface. If the driver of a responding vehicle confirms that he is willing to provide assistance, he will send a response feedback to the cloud platform through the onboard terminal of the responding vehicle. When the cloud platform receives a response feedback from at least one nearby vehicle, it will stop broadcasting new distress messages to vehicles in a wider range and select the main rescue vehicle. S6: Rescue Coordination and Notification; The cloud platform obtains detailed information about the main rescue vehicles, pushes the detailed information of the main rescue vehicles to the vehicle in distress, and sends a status update that "the rescue mission has been accepted" to other nearby response vehicles that have received the distress call. S7: Dynamic update and termination; During the rescue process, the cloud platform dynamically adjusts the broadcast range and content of the distress information based on changes in the location of the distressed vehicle or the situation on site. After the rescue is completed, in response to the confirmation operation of the distressed vehicle or the rescue vehicle, the cloud platform stops broadcasting the relevant information and marks the event as closed.

5. The method for dynamic broadcasting of emergency assistance information and multi-vehicle collaborative response in the Internet of Vehicles as described in claim 4, characterized in that: Step S3 includes: S31: Initial range filtering; The cloud platform responds to the distress request, obtains the real-time location coordinates of the distressed vehicle, sets the initial broadcast radius R0 (default is 3 kilometers), obtains real-time vehicle information from the vehicle database, and retrieves all candidate vehicles that are currently online and located within the circular area: it filters out all online vehicles from the real-time vehicle information, then calculates the straight-line distance between each online vehicle and the distressed vehicle based on the location coordinates of the online vehicles, filters out vehicles with a distance ≤ R0, obtains all candidate vehicles, and creates a new list of the filtered candidate vehicles to obtain the initial candidate vehicle list; S32: Distance weight calculation; Calculate the distance from the candidate vehicle to the vehicle in distress, and convert the distance into weights; Obtain the real-time location coordinates of the candidate vehicles, calculate the distance between the real-time location coordinates of the distressed vehicle and the real-time location coordinates of the candidate vehicles, and convert the distance into a weight: DistanceWeight(i) = 1 / (1+Distance(i) / 1000), and iterate through all candidate vehicles to obtain the distance weights between them and the distressed vehicle. S33: Relative driving direction assessment; Obtain the driving direction vectors of the distressed vehicle and all candidate vehicles respectively, and calculate the cosine of the angle between the driving direction vectors of the distressed vehicle and each candidate vehicle as the direction correlation coefficient DirectionScore(i). S34 driving status assessment; Obtain the real-time speed of the candidate vehicle, adjust the driving speed based on the real-time road conditions to obtain the effective driving speed of the candidate vehicle, and obtain the estimated arrival time EstimatedTime(i) based on the effective driving speed. S35: Overall score ranking; Calculate the overall matching score for each candidate vehicle: Score(i) = α×DirectionScore(i) + β×DistanceWeight(i) + γ×(1 / EstimatedTime(i)), where α=0.4, β=0.3, and γ=0.3 are weighting coefficients; select the top 5-8 vehicles as the most suitable response vehicles.

6. The method for dynamic broadcasting of emergency assistance information and multi-vehicle collaborative response in vehicle networking as described in claim 5, characterized in that: S33 includes: S331: Obtain the driving direction vector; The positioning module periodically collects location data to obtain the position coordinates of the distressed vehicle and each candidate vehicle at two consecutive sampling time points after the initial range filtering is completed. The position coordinates of the later time are subtracted from the position coordinates of the previous time to obtain the driving direction vectors of the distressed vehicle and the candidate vehicle, respectively. S332: Calculate the directional correlation coefficient; The directional correlation coefficient is obtained by calculating the cosine of the vector between the direction of travel of the distressed vehicle and the direction of travel of each candidate vehicle.

7. The method for dynamic broadcasting of emergency assistance information and multi-vehicle collaborative response in the Internet of Vehicles as described in claim 5, characterized in that: Also includes: S341: Calculate the real-time speed of the candidate vehicle: Obtain the real-time speed by dividing the magnitude of the candidate vehicle's driving direction vector by the time interval between two consecutive sampling points. S342: Obtain correction coefficient based on real-time traffic conditions: The cloud platform sends a request to the traffic data platform to obtain traffic data. The traffic data platform responds to the request and returns response data, which includes traffic conditions, congestion level, and sets the correction coefficient corresponding to the congestion level. S343: Calculate the effective driving speed of candidate vehicles: Obtain the effective driving speed of candidate vehicles by multiplying the real-time speed of candidate vehicles by the corresponding road condition correction factor; S344: Obtain the estimated arrival time: The estimated arrival time is obtained by dividing the calculated distance from the candidate vehicle to the distressed vehicle by the effective speed of the candidate vehicle.

8. The method for dynamic broadcasting of emergency assistance information and multi-vehicle collaborative response in the Internet of Vehicles as described in claim 4, characterized in that: Step S5 includes: S51: Response information generation; After receiving the distress message, the vehicle-mounted terminal of a nearby vehicle displays the distress details on the interface of the human-machine interaction unit and issues an audio and visual reminder. If the driver confirms that he is willing to provide assistance, the vehicle-mounted terminal responds to the driver's confirmation operation, collects the location of the responding vehicle, obtains the vehicle identifier and driver's basic information from the vehicle registration information table, and calls the navigation engine to calculate the estimated arrival time based on the current traffic conditions. The driver's basic information includes the driver's name and contact number. S52: Response priority determination, select the primary rescue vehicle; The cloud platform receives response feedback, obtains the estimated arrival time, and prioritizes vehicles based on their vehicle identification, vehicle type, special equipment configuration, and driver qualifications from the vehicle registration information table; the top 1-2 vehicles are selected as the main rescue vehicles. S53: Broadcast control mechanism: When a sufficient number of valid responses are received, stop expanding the broadcast radius and continue sending distress messages to vehicles outside the current broadcast range.

9. The method for dynamic broadcasting of emergency assistance information and multi-vehicle collaborative response in vehicle networking as described in claim 8, characterized in that: Specifically, S52 assigns 20 points to vehicles with medical first-aid kits or towing capabilities based on vehicle type and specialized equipment configuration, and 0 points to those without. It also assigns 20 points to drivers with relevant rescue experience, and 0 points to drivers without such experience. The estimated arrival time of responding vehicles is obtained, and these vehicles are sorted in descending order of estimated arrival time, with points assigned sequentially from 1 to N, where N is the number of responding vehicles. All scores for each responding vehicle are summed to calculate a comprehensive score. Based on the comprehensive score, the responding vehicles are prioritized, and the top 1-2 vehicles with the highest comprehensive scores are designated as primary rescue vehicles.

10. The method for dynamic broadcasting of emergency assistance information and multi-vehicle collaborative response in the Internet of Vehicles as described in claim 5, characterized in that: Step S7 includes: S71: On-site situation monitoring: Real-time assessment of the on-site situation based on the sensors of the distressed vehicle and the on-site images / videos fed back by the rescue vehicle, to determine whether the on-site situation is deteriorating; when the following situations are detected, the situation is determined to be deteriorating: abnormal vital signs of the occupants of the vehicle, vehicle fire or fuel leak, secondary collision occurs, rescue vehicle reports a complex scene; S72: Dynamic Range Adjustment: If the situation worsens or the need for rescue increases, the broadcast radius is expanded to R2=2×R0, and the request for help is updated and marked as "emergency escalation", and a request for reinforcements is sent to vehicles within the new range; S73: Location Tracking Update: If the location of the distressed vehicle changes and the distance moved exceeds 100 meters, the location information will be updated immediately and all vehicles involved in the rescue will be notified. S74: Rescue Completion Confirmation: In response to the completion confirmation operation of the distressed vehicle or the rescue vehicle, when the cloud platform receives the "rescue completed" confirmation from the distressed vehicle or the rescue vehicle reports "mission completed", it stops broadcasting all relevant information, records the rescue process data, and sends a thank-you notification to the participating vehicles.

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