V2X Internet of Vehicles emergency message forwarding method and system

Abstract

The invention provides a V2X Internet of Vehicles emergency message forwarding method and system, and the method aims at the defects of a conventional single relay strategy, dynamically determines the number of relay nodes according to a road topology structure, and formulates different forwarding strategies in combination with different forwarding objects, thereby effectively improving the effectiveness of an algorithm. The node state is evaluated by using information such as the speed, the course angle, the position and the channel condition of the nodes (OBU and RSU); in addition, an optimization algorithm based on a graffiti search algorithm-genetic algorithm is designed to decide a relay node, and the received emergency message is forwarded. According to the invention, the propagation speed of the emergency message in the complex traffic environment of the Internet of Vehicles can be effectively improved, the redundancy rate of the message is reduced, and the V2X emergency message communication stability and reliability of the Internet of Vehicles system are improved.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent connected vehicles and vehicle networking, and in particular to a V2X vehicle networking emergency message forwarding method and system. Background Art

[0002] As one of the most important application scenarios of Internet of Vehicles technology, intelligent transportation system road safety applications are of great significance for avoiding traffic accidents and reducing the loss of life and property caused by abnormal traffic incidents. Therefore, emergency message broadcast technology for road safety applications has received widespread attention. Since emergency messages are often transmitted through multi-hop broadcasts, the design of emergency message multi-hop broadcast protocols is of great significance for improving network performance in various application scenarios and meeting the communication requirements of emergency messages with low latency and high reliability. Existing multi-hop broadcast algorithms can be divided into four categories: delay-based, probability-based, location-based, and cluster-based.

[0003] Delay-based multi-hop broadcast algorithm, this type of algorithm is a timer-based forwarding algorithm. Once a vehicle receives a multi-hop data packet in the target area, it does not forward the received data packet immediately, but stores it in the buffer of the contention-based forwarding (CBF) node. Each queued data packet has an associated timer. When the timer expires, the relevant data packet will be rebroadcast. The timer duration is inversely proportional to the distance between the previous sender and the current vehicle. On the contrary, if another vehicle rebroadcasts the data packet before the timer expires, the data packet will be deleted from the CBF buffer. Therefore, farther vehicles tend to retransmit data packets earlier, while nearby vehicles unbuffer data packets based on CBF listening. Although delay-based methods avoid broadcast storms through broadcast suppression, this type of algorithm may cause the delay of messages to be too large or too small.

[0004] Probabilistic multi-hop broadcast algorithms do not require additional waiting time before rebroadcasting received packets. They allow each node to rebroadcast immediately with a predetermined probability. In most works, the forwarding probability is determined based on local information, such as the Euclidean distance from the forwarder to the source node. The simplest probabilistic multi-hop broadcast is called flooding. In flooding, each node rebroadcasts the packet immediately after receiving an urgent message from the source node. Although probabilistic methods can show good delay propagation, since each node is assigned a certain forwarding probability, multiple nodes may forward messages at the same time, resulting in an increase in redundancy, or no node forwards the message, resulting in premature termination of message forwarding.

[0005] A location-based multi-hop broadcast algorithm, in which a vehicle establishes a neighbor information source table by acquiring BSM messages periodically broadcast by neighboring vehicles. The current node (the node that forwards the message) makes forwarding decisions based on the neighbor information source table. Location information parameters may include location, direction, and distance from the boundary of the transmission range. Although the location-based multi-hop broadcast algorithm is efficient. However, high-mobility vehicles in the Internet of Vehicles will cause frequent topology changes, thereby reducing the efficiency of the location-based multi-hop broadcast algorithm. In addition, how to determine the BSM message cycle is also a challenge. A reduction in the BSM message cycle will cause problems such as untimely updates of the message source table, while a higher BSM message cycle will increase the burden on the network.

[0006] Cluster-based multi-hop broadcast algorithms. This type of method groups vehicles into clusters based on their characteristics. In each group of vehicles, factors such as vehicle density and channel conditions are used to dynamically adjust clustering and formulate a strategy for selecting cluster heads (CH). Vehicles other than CHs are called cluster members. Emergency message forwarding is only performed between CHs. The main advantage of this type of algorithm is that it can handle broadcast storms. However, since the clustering mechanism requires frequent message exchanges, this may increase the network burden and introduce additional delays. In addition, it is also necessary to consider how to select a suitable cluster head node to avoid the problem of uneven network load.

[0007] In summary, existing works only consider one or several factors to construct evaluation functions, which may lead to wrong decisions or just maintain suboptimal states. Therefore, in order to implement efficient multi-hop broadcast algorithms, the real-time status of nodes should be used to determine the suitability of nodes. The node status needs to be evaluated based on multiple attributes, while considering the weights of different attributes' contributions to the goal. Summary of the invention

[0008] Purpose of the invention: The technical problem to be solved by the present invention is to provide a V2X vehicle network emergency message forwarding method and system in view of the deficiencies of the prior art. , so as to reduce the emergency message transmission delay and improve the emergency message transmission efficiency.

[0009] In order to achieve the above-mentioned object, the first aspect of the present invention provides a V2X (Vehicle to Everything, V2X) vehicle network emergency message forwarding method, comprising the following steps:

[0010] Step 1, obtaining the number of casualties, average vehicle speed and vehicle density in the area where the traffic abnormality event occurred, and evaluating the area affected by the traffic abnormality event;

[0011] Step 2: Develop vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) forwarding strategies based on the number of intersection exits, the number of decision relays, and whether roadside equipment is deployed at the intersection.

[0012] Step 3, evaluate the node status using the node's speed, heading angle, position and channel status;

[0013] Step 4, design an optimization algorithm based on crow search algorithm and genetic algorithm to decide relay nodes;

[0014] Step 5, forward the emergency message;

[0015] Step 6: Design a receiving response mechanism to enable backup relays and improve the robustness of the algorithm.

[0016] In step 1, the severity of the abnormal traffic event is obtained by using the number of casualties in the abnormal traffic event, and the impact radius of the abnormal traffic event is obtained by the severity of the abnormal traffic event and the average speed of the node, the node density and the node transmission radius, including:

[0017] The severity of the abnormal traffic incident E is evaluated by obtaining the number of deaths D1, the number of serious injuries D2 and the number of minor injuries D3. r , E r The expression is:

[0018] E r =D1+0.33D2+0.1D3

[0019] The nodes include an on-board unit OBU (On Board Unit, OBU) and a road side unit RSU (Road Side Unit, RSU);

[0020] Using the severity of abnormal traffic events E r , average vehicle speed v avg and vehicle density ρ, evaluate the radius R of the area affected by traffic abnormalities z , R z The expression is:

[0021]

[0022] Where α is the proportional factor; R T is the maximum transmission distance; E max 、v max , max They are the maximum severity, the maximum speed allowed on the road, and the maximum vehicle density.

[0023] In step 2, different forwarding strategies are selected according to different road side unit (RSU) deployment scenarios, including:

[0024] The road scene is divided into three areas according to whether it is an intersection scene and whether it is covered by the roadside unit RSU. The first area 1 is an intersection with a roadside unit RSU deployed, and the nodes in the area communicate using V2I; the second area 2 is a non-intersection, and the nodes in the area communicate using V2V; the third area 3 is an intersection without a roadside unit RSU deployed, and the nodes in the area communicate using V2V.

[0025] V2I forwarding strategy and V2V forwarding strategy are used for different communication modes, including:

[0026] V2I forwarding strategy: The emergency message reaches the RSU coverage area through V2V, and the vehicle forwards the emergency message to the roadside unit RSU, which broadcasts the emergency message to the vehicles in the first area 1 through the PC5 link; when no available neighbor vehicles are observed in the intersection area, the roadside unit RSU will cache the data packet until the vehicle appears or the data packet expires, and at the same time, the roadside unit RSU broadcasts the message to the affected area radius R through the optical fiber link. z Roadside units RSU within range.

[0027] V2V forwarding strategy: Nodes in the second area 2 use the V2V forwarding strategy to select relays and broadcast data packets. The source node (i.e., the message generating node) directly forwards the data packet through a greedy strategy, so that the number of hops and delays experienced by the message in the forwarding process reach the optimal value; when the emergency message is transmitted in the second area 2, the vehicle forwards the message to the surrounding vehicles through the PC5 link; when the message is transmitted in the third area 3, the node (OBU, RSU) broadcasts the emergency message to the vehicles in the third area 3, and then the relay vehicle continues to forward the emergency message; when there is no available neighbor node within the communication range of the source node or forwarding node (relay vehicle), the vehicle node caches the message, and as the vehicle continues to move, until a neighbor vehicle appears or the data packet expires.

[0028] Step 3 includes:

[0029] Model the node state as a triple c ij ={m ij ,p ij ,u ij}, the formula is:

[0030]

[0031] u ij =P ij =1-Fd (Rt ij ,Rs ij ,m),

[0032]

[0033] Where m ij represents the mobility factor between node i and node j; β is a smoothing factor, β=0.8 in the present invention; p ij is the position factor, which is used to describe the relative position relationship between vehicles; (x i ,y i ), (x j ,y j ) are the positions of node i and node j respectively; v i is the velocity of node i, v j is the velocity of node j, v max is the maximum speed allowed by the road; γ is a weight factor, indicating which part of the impact is more concerned, optionally, γ = 0.7. ;u ij is the channel factor, used to represent the channel condition; P ij Rt represents the probability of successful transmission of emergency messages between nodes i and j; ij is the signal receiving threshold; Rs ij is the average received signal strength; F d When the Euclidean distance between node i and node j is d, the signal receiving threshold is Rt ij , the average signal receiving strength is Rs ij , the cumulative distribution function of the fading parameter m; P t is the signal transmission power; G = (G t G r λ 2 ) / [(4π) 2 L]; G t and G r The distribution is the transmit antenna gain and the receive antenna gain; L is the path loss; λ is the wavelength;

[0034] The fading parameter m is determined by d and is expressed as:

[0035]

[0036] Step 4 includes:

[0037] The AP of the traditional Crow Search Algorithm (CSA) is a constant, and a fixed AP often falls into local optimization. Therefore, Self-adaptation Awareness Probability (SAP) is used to avoid this problem. Crows with strong fitness will tend to search locally, while crows with weak fitness will tend to search globally to obtain a stronger fitness value. Define SAP k Adaptive perception probability for crow k:

[0038]

[0039] Among them, AP min and AP max are the minimum and maximum perception probabilities of crows, respectively. Optionally, AP min =0.1,AP max =0.8; η k is the ranking (fitness value) of the kth crow in the population; N is the number of the population;

[0040] Since the CSA algorithm may fall into a local optimum, while the genetic algorithm moves more evenly to the optimal area. Therefore, in order to improve the convergence of the CSA algorithm, the genetic algorithm is introduced to make it find the optimal solution faster. Adaptive crossover and mutation probability are used. The adaptive crossover probability P is calculated using the following formula: c and adaptive mutation probability P m :

[0041]

[0042] Among them, f avg Represents the adaptive mean, i.e. c ij The mean value of max Indicates the maximum value of the fitness value;

[0043] In view of the advantages of the above algorithms, an optimization algorithm based on crow search algorithm and genetic algorithm (CSA-GA) is proposed, which not only makes the algorithm have fast convergence ability, but also has better global search ability. The optimization algorithm based on crow search algorithm and genetic algorithm is used to select the relay node sequence, which specifically includes the following steps:

[0044] Step 4-1, given the dimension E of the search space, the objective function f = c ij , population size N, flight distance fl, maximum number of iterations t max , maximum perception probability AP max and minimum perception probability AP min , and calculate SAP i ;

[0045] Step 4-2, initialize the population Po init ={x (1,0) ,x (2,0) ,…,x (N,0)} and memory location, where x (N,0) represents the position of crow N at the 0th iteration;

[0046] Step 4-3, calculate the fitness value f[x (i,t) ], where x (i,t) Indicates the position of crow i at the tth iteration; sorts the population according to the fitness value and assigns the appropriate SAP i ;

[0047] Step 4-4, update the position according to the following formula to determine whether it is a suitable position. If it is an invalid position, introduce a genetic algorithm to select the current crow and the tracked crow for crossover mutation operation to generate a child crow:

[0048]

[0049] Among them i is a uniformly distributed random number in the range (0,1]; fl (i,t) represents the flight distance of the i-th crow at the t-th iteration; me (j,t) represents the memory position of crow i at the tth iteration;

[0050] Step 4-5, update the memory value, sort by fitness value, and take the top N individuals as the new group;

[0051] Step 4-6, repeat steps 4-3 to 4-5 until the termination condition is met (the number of iterations is reached), and the optimal relay is used as the algorithm output.

[0052] In step 4-5, the memory value is updated according to the following formula:

[0053]

[0054] In step 6, the design of a receiving response mechanism to enable the backup relay specifically includes:

[0055] When the relay node receives a message, it will send a response signal to the source node via unicast. When the source node does not receive the response signal from the relay node, it will send a signal to the backup relay node via unicast to designate the backup relay node as a relay. After receiving the signal, the backup relay will execute the message forwarding procedure.

[0056] The present invention also provides a V2X vehicle network emergency message forwarding system for implementing the method, comprising a V2X message preprocessing module, a message forwarding strategy module, a relay decision module and a standby relay decision module;

[0057] The V2X message preprocessing module is used to calculate the impact radius, mobility factor, channel factor and location factor of the emergency message, and filter the processing of messages irrelevant to the vehicle;

[0058] The message forwarding strategy module is used to determine the corresponding forwarding strategy to use in the current scenario;

[0059] The message forwarding strategy module is used to decide on relay nodes, and uses the node's mobility factor, channel factor, and location factor for comprehensive analysis, and uses the CSA-GA optimization algorithm to decide on relay nodes and obtain a relay node sequence;

[0060] The standby relay decision module is used to decide on a standby relay node when a relay link is interrupted, obtain the standby relay node, and continue to forward the emergency message.

[0061] The present invention also provides an electronic device, comprising a processor and a memory, wherein the memory stores program code, and when the program code is executed by the processor, the processor executes the steps of the described method.

[0062] The present invention also provides a storage medium storing a computer program or instruction. When the computer program or instruction is run on a computer, the steps of the method described are executed.

[0063] Compared with the prior art, the present invention has the following beneficial effects:

[0064] The V2X vehicle network emergency message forwarding method and system described in the present invention are mainly characterized in that a node state evaluation function is designed by comprehensively considering the severity of traffic abnormal events, node mobility, node location attention, node density and channel conditions to evaluate the node state; for relay node selection, a CSA-GA algorithm is proposed for relay node sequence selection, and the delivery rate of emergency messages is improved and the transmission delay of emergency messages is reduced through global optimization; at the same time, considering the possible interruption of the relay link, a receiving response mechanism is designed to improve the robustness of the system.

[0065] Based on the following detailed description of specific embodiments of the present invention in conjunction with the accompanying drawings, those skilled in the art will become more aware of the above-mentioned objects, advantages and features of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments, and the above and / or other advantages of the present invention will become more clear.

[0067] Figure 1 It is a flow chart of a multi-hop broadcast algorithm based on multi-factor evaluation provided by the present invention.

[0068] Figure 2 It is a schematic diagram of the road partition diagram provided by the present invention.

[0069] Figure 3 It is a flow chart of the CSA-GA algorithm provided by the present invention.

[0070] Figure 4 This is a backup relay decision flow chart provided by the present invention.

[0071] Figure 5 It is a module structure diagram of the system provided by the present invention. DETAILED DESCRIPTION

[0072] The purpose of the present invention is to propose a V2X vehicle network emergency message forwarding method for emergency message broadcasting under the vehicle network. A V2X vehicle network emergency message forwarding method is provided to reduce the emergency message transmission delay and improve the emergency message transmission efficiency.

[0073] Embodiment 1 of the present invention provides a V2X vehicle network emergency message forwarding method. The overall flow chart of the method of the present invention is as follows: Figure 1 As shown, the method of the present invention comprises the following steps:

[0074] Step 1: Obtain information such as the number of casualties, average vehicle speed, and vehicle density in the area where the traffic abnormality occurred, and evaluate the area affected by the traffic abnormality;

[0075] Step 2: Develop V2V and V2I forwarding strategies based on the number of intersection exits, the number of decision relays, and whether roadside equipment is deployed at the intersection;

[0076] Step 3: Evaluate the node status using information such as the node's speed, heading angle, position, and channel status;

[0077] Step 4: Design an optimization algorithm based on crow search algorithm-genetic algorithm to decide relay nodes;

[0078] Step 5: Forward the emergency message;

[0079] Step 6: Design a receive response mechanism to enable backup relays and improve the robustness of the algorithm.

[0080] In step 1, the severity of the abnormal traffic event is obtained by using the number of casualties of the abnormal traffic event, and the impact radius of the abnormal traffic event is obtained by the severity of the abnormal traffic event and the average speed of the nodes (OBU, RSU), the node density, and the node transmission radius, including:

[0081] The severity of the abnormal traffic incident E is evaluated by obtaining the number of deaths D1, the number of serious injuries D2, and the number of minor injuries D3. r , E r The expression is:

[0082] E r =D1+0.33D2+0.1D3

[0083] Using E r , average vehicle speed and vehicle density, and evaluate the radius R of the area affected by traffic abnormalities z , R z The expression is:

[0084]

[0085] Where α is the proportional factor; R T is the maximum transmission distance; E max 、v max , max are the maximum severity, the maximum speed allowed on the road, and the maximum vehicle density. The impact range of abnormal events is generally several kilometers, and the transmission distance is often only about 300 meters. Optionally, α=12.

[0086] like Figure 2 As shown, in step 2, different forwarding strategies are selected according to different RSU deployment scenarios, including:

[0087] The road scene is divided into three areas according to whether it is an intersection scene and whether it is covered by RSU. Area 1 is an intersection where RSU is deployed, and the nodes in this area communicate using V2I; Area 2 is a non-intersection, and the nodes in the area communicate using V2V; Area 3 is an intersection where RSU is not deployed, and the nodes in the area communicate using V2V.

[0088] V2I forwarding strategy and V2V forwarding strategy are used for different communication modes, which are described as follows:

[0089] V2I forwarding strategy: Emergency messages arrive at the RSU coverage area through V2V, and the vehicle forwards the emergency message to the RSU, which broadcasts it to the vehicles in area 1 through the PC5 link. When no available neighbor vehicles are observed in the intersection area, the RSU caches the data packet until the vehicle appears or the data packet expires. At the same time, the RSU broadcasts the message to the vehicles in the influence radius R through the optical fiber link. z RSUs within the scope.

[0090] V2V forwarding strategy: Nodes in area 2 use this forwarding strategy to select relays and broadcast data packets. The source node directly forwards the data packet through a greedy strategy, so that the number of hops and delays experienced by the message during the forwarding process reach the optimal value. When the emergency message is transmitted in area 2, the vehicle forwards the message to the surrounding vehicles through the PC5 link. When the message is transmitted in area 3, the node broadcasts the emergency message to the vehicles in area 3, and then the relay vehicle continues to forward the message. When there are no available neighbor nodes within the communication range of the source node or forwarding node. The vehicle node caches the message, and as the vehicle continues to move, until a neighbor vehicle appears or the data packet expires.

[0091] In step 3, the node status is evaluated by using information such as the node's speed, heading angle, position, and channel status, which specifically includes:

[0092] Model the node state as a triple c ij ={m ij ,p ij ,u ij}. c ij The formula is:

[0093]

[0094] m ij is the mobility factor, m ij The expression is as follows:

[0095]

[0096] In the formula, m ij represents the mobility factor between node i and node j; β is the smoothing factor, and its value is set to 0.8. ij The smaller the value, the smaller the relative speed and the more stable it is;

[0097] p ij is the position factor, describing the relative position relationship between vehicles; p ij The expression is as follows:

[0098]

[0099] In the formula, (x i ,y i ), (x j ,y j ) are the positions of the two vehicles respectively; y is the weight factor, indicating which part’s influence is more concerned, optionally, γ=0.7.

[0100] u ijis the channel factor, which indicates the channel condition. Studies have shown that the Nakagami-m distribution with parameter m is the most suitable model to describe the fading of radio wave propagation in the Internet of Vehicles. Using this model, we can obtain the probability P of successful transmission of emergency messages between nodes i and j. ij ,u ij =P ij It is expressed as the following formula:

[0101] u ij =P ij =1-F d (Rt ij ,Rs ij ,m),

[0102]

[0103] Among them, Rt ij is the signal receiving threshold; Rs ij is the average received signal strength; F d Indicates that for distance d, the signal reception threshold is Rt ij , the average signal receiving strength is Rs ij , the cumulative distribution function of the fading parameter m; the fading parameter m is determined by d, and the expression is as follows:

[0104]

[0105] P t is the signal transmission power; G = (G t G r λ 2 ) / [(4π) 2 L]; G t and G r The distribution is the transmit antenna and receive antenna gain; L is the path loss; λ is the wavelength.

[0106] like Figure 3 As shown, in step 4, an optimization algorithm based on a crow search algorithm-genetic algorithm is designed to decide on relay nodes, including:

[0107] The AP of the traditional Crow Search Algorithm (CSA) is a constant, and a fixed AP often falls into local optimization. Therefore, Self-adaptation Awareness Probability (SAP) is used to avoid this problem. Crows with strong fitness will tend to search locally, while crows with weak fitness will tend to search globally to obtain a stronger fitness value. Define SAP i is the adaptive perception probability of crow i, which is calculated by the following formula:

[0108]

[0109] Where AP min and AP max are the minimum and maximum perception probabilities of crows, respectively. Optionally, AP min =0.1,AP max =0.8; η i is the ranking of the i-th crow in the population; N is the number of the population.

[0110] Since the CSA algorithm may fall into a local optimum, while the genetic algorithm moves more evenly to the optimal area, in order to improve the convergence of the CSA algorithm, the genetic algorithm is introduced to make it find the optimal solution faster. Adaptive crossover and mutation probability are used. Adaptive crossover probability P c and adaptive mutation probability P m See the following formula:

[0111]

[0112] In view of the advantages of the above algorithms, an optimization algorithm based on the crow search algorithm-genetic algorithm (CSA-GA) is proposed, which not only makes the algorithm have fast convergence ability, but also has better global search ability. The specific process of using this algorithm to select the relay node sequence is as follows:

[0113] (1) Given the dimension E of the search space, the objective function f = c ij , population size N, flight distance fl, maximum number of iterations t max , maximum perception probability AP max and minimum perception probability AP min , and calculate SAP i .

[0114] (2) Initialize the population Po init ={x (1,0) ,x (2,0) ,…,x (N,0)} and memorize the location.

[0115] (3) Calculate the fitness value f[x (i,t) ]; and sort the population according to the fitness value and assign appropriate SAP to it i .

[0116] (4) Update the position according to the following formula to determine whether it is a suitable position. If it is an invalid position, introduce a genetic algorithm to select the current crow and the tracked crow for crossover mutation operation to generate a child crow.

[0117]

[0118] In the formula, ra i is a uniformly distributed random number in the range (0,1]; fl (i,t) represents the flight distance of the i-th crow at the t-th iteration.

[0119] (5) Update the memory value according to the following formula, sort by fitness value, and take the first N individuals as the new group.

[0120]

[0121] (6) Repeat steps (3) to (5) until the termination condition is met and take the optimal relay as the algorithm output.

[0122] like Figure 4 As shown, in step 6, a receiving response mechanism is designed to enable the backup relay, including:

[0123] Since vehicle nodes are very fast, the communication link between vehicles is likely to be interrupted. In order to effectively avoid this problem, a backup relay is used to handle this problem. When the relay node link is disconnected, the forwarding node will automatically select another backup relay node to forward the message, thereby reducing the link reconstruction time and improving performance.

[0124] When the relay node receives a message, it sends a response signal to the source node via unicast. When the source node does not receive the response signal from the relay node, it sends a signal to the backup relay node via unicast to designate it as a relay. When the backup relay receives the signal, it will execute the message forwarding procedure.

[0125] For example, Figure 2 In the example, when v1 detects (e.g., by deep learning) a traffic anomaly ahead, v1 becomes the source node and uses the detected casualties to calculate E r =0.76 (assuming 0 deaths, 2 serious injuries, and 1 minor injury) (E max =4.29 (calculated based on 3 deaths, 3 serious injuries, and 3 minor injuries), set v avg =30km / h, v max Take 60km / h, ρ take 20 vehicles / (km*number of lanes), ρ max =100 vehicles / (km*number of lanes), R T Take 300m, α=12 to get R z =1052.4m, calculate all neighbors c ij , and then input the neighbor information into the CSA-GA algorithm, and obtain the optimal relay node (such as v2) and the suboptimal relay node through iteration, and then use the accident information, its own location, R zThe emergency message is written into the relay node (v2), the emergency message is broadcasted, and the waiting timer is started. If a response signal is received, the source node ends forwarding the emergency message. If no response signal is received, a signal designated as a relay is sent to the backup node, and the suboptimal node becomes a relay node. The message forwarding is completed in one hop. In the Nth hop, the relay node of the previous hop becomes the forwarding node of this hop (v2~v4), and the "calculation of all neighbor c ij ", until the straight-line distance from the source node is greater than R z .

[0126] Embodiment 2 of the present invention provides a V2X vehicle network emergency message forwarding system for implementing the method described in Embodiment 1 above, such as Figure 5 As shown, the system includes: a V2X message preprocessing module, a message forwarding strategy module, a relay decision module and a standby relay decision module;

[0127] The V2X message preprocessing module is used to calculate the impact radius, mobility factor, channel factor and location factor of the emergency message, and filter the processing of messages irrelevant to the vehicle;

[0128] The message forwarding strategy module is used to determine the corresponding forwarding strategy to use in the current scenario;

[0129] The message forwarding strategy module is used to decide on relay nodes, and uses the node's mobility factor, channel factor, and location factor for comprehensive analysis, and uses the CSA-GA optimization algorithm to decide on relay nodes and obtain a relay node sequence;

[0130] The standby relay decision module is used to decide on a standby relay node when a relay link is interrupted, obtain the standby relay node, and continue to forward the emergency message.

[0131] The present invention provides a V2X vehicle network emergency message forwarding method and system. There are many methods and ways to implement the technical solution. The above is only a preferred implementation of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the protection scope of the present invention. All components not specified in this embodiment can be implemented by existing technologies.

Claims

1. A V2X vehicle network emergency message forwarding method, characterized in that: The following steps are involved: Step 1, obtaining the number of casualties, average vehicle speed and vehicle density in the area where the traffic abnormality event occurred, and evaluating the area affected by the traffic abnormality event; Step 2: Develop V2V and V2I forwarding strategies based on the number of intersection exits, the number of decision relays, and whether roadside equipment is deployed at the intersection. Step 3, evaluate the node status using the node's speed, heading angle, position and channel status; Step 4, design an optimization algorithm based on crow search algorithm and genetic algorithm to decide relay nodes; Step 5, forward the emergency message; Step 6: Design a receive response mechanism to enable the backup relay.

2. The method according to claim 1, characterized in that In step 1, the severity of the abnormal traffic event is obtained by using the number of casualties in the abnormal traffic event, and the impact radius of the abnormal traffic event is obtained by the severity of the abnormal traffic event and the average speed of the node, the node density and the node transmission radius, including: The severity of the abnormal traffic incident E is evaluated by obtaining the number of deaths D1, the number of serious injuries D2, and the number of minor injuries D3. r , E r The expression is: AND r =D1+0.33D2+0.1D3 The nodes include an on-board unit OBU and a roadside unit RSU; Using the severity of abnormal traffic events E r , average vehicle speed v avg and vehicle density ρ, evaluate the radius R of the area affected by traffic abnormalities z , R z The expression is: Where α is the proportional factor; R T is the maximum transmission distance; E max 、v max , max They are the maximum severity, the maximum speed allowed on the road, and the maximum vehicle density.

3. The method according to claim 2, characterized in that In step 2, different forwarding strategies are selected according to different roadside unit (RSU) deployment scenarios, including: The road scene is divided into three areas according to whether it is an intersection scene and whether it is covered by the roadside unit RSU. The first area 1 is an intersection with a roadside unit RSU deployed, and the nodes in the area communicate using the V2I method; the second area 2 is a non-intersection, and the nodes in the area communicate using the V2V method; the third area 3 is an intersection without a roadside unit RSU deployed, and the nodes in the area communicate using the V2V method; V2I forwarding strategy and V2V forwarding strategy are used for different communication modes, including: V2I forwarding strategy: The emergency message reaches the RSU coverage area through V2V, and the vehicle forwards the emergency message to the roadside unit RSU, which broadcasts the emergency message to the vehicles in the first area 1 through the PC5 link; when no available neighbor vehicles are observed in the intersection area, the roadside unit RSU will cache the data packet until the vehicle appears or the data packet expires, and at the same time, the roadside unit RSU broadcasts the message to the affected area radius R through the optical fiber link. z Roadside units RSU within range; V2V forwarding strategy: Nodes in the second area 2 use the V2V forwarding strategy to select relays and broadcast data packets. The source node directly forwards the data packet through a greedy strategy, so that the number of hops and delays experienced by the message in the forwarding process reach the optimal value; when the emergency message is transmitted in the second area 2, the vehicle forwards the message to the surrounding vehicles through the PC5 link; when the message is transmitted in the third area 3, the node broadcasts the emergency message to the vehicles in the third area 3, and then the relay vehicle continues to forward the emergency message; when there is no available neighbor node within the communication range of the source node or forwarding node, the vehicle node caches the message, and as the vehicle continues to move, until a neighbor vehicle appears or the data packet expires.

4. The method according to claim 3, characterized in that Step 3 includes: Model the node state as a triple c ij ={m ij , p ij ,u ij }, the formula is: u ij =P ij =1-F d (Rt ij ,Rs ij ,m), Where m ij represents the mobility factor between node i and node j; β is the smoothing factor; p ij is the position factor, which is used to describe the relative position relationship between vehicles; (x i ,y i ), (x j ,y j ) are the positions of node i and node j respectively; v i is the velocity of node i, v j is the velocity of node j, v max is the maximum speed allowed by the road; γ is the weight factor; u ij is the channel factor, used to represent the channel condition; P ij Rt represents the probability of successful transmission of emergency messages between nodes i and j; ij is the signal receiving threshold; Rs ij is the average received signal strength; F d When the Euclidean distance between node i and node j is d, the signal receiving threshold is Rt ij , the average signal receiving strength is Rs ij , the cumulative distribution function of the fading parameter m; P t is the signal transmission power; G = (G t G r λ 2 ) / [(4π) 2 L]; G t and G r The distribution is the transmit antenna gain and the receive antenna gain; L is the path loss; λ is the wavelength; The fading parameter m is determined by d and is expressed as:

5. The method according to claim 4, characterized in that Step 4 includes: Defining SAP k Adaptive perception probability for crow k: Among them, AP min and AP max are the minimum and maximum perception probabilities of crows, respectively; η k is the ranking of the kth crow in the population; N is the number of the population; The adaptive crossover probability P is calculated using the following formula: c and adaptive mutation probability P m : Among them, f avg Represents the adaptive mean, i.e. c ij The mean value of max Indicates the maximum value of the fitness value; The relay node sequence is selected using an optimization algorithm based on the crow search algorithm and the genetic algorithm, which specifically includes the following steps: Step 4-1, given the dimension E of the search space, the objective function f = c ij , population size N, flight distance fl, maximum number of iterations t max , maximum perception probability AP max and minimum perception probability AP min , and calculate SAP i ; Step 4-2, initialize the population Po init ={x (1，0) , x (2，0) , …, x (N，0) } and memory location, where x (N，0) represents the position of crow NNN at the 0th iteration; Step 4-3, calculate the fitness value f[x (i，t) ], where x (i，t) Indicates the position of crow i at the tth iteration; sorts the population according to the fitness value and assigns the appropriate SAP i ; Step 4-4, update the position according to the following formula to determine whether it is a suitable position. If it is an invalid position, introduce a genetic algorithm to select the current crow and the tracked crow for crossover mutation operation to generate a child crow: Among them i is a uniformly distributed random number in the range of (0, 1]; fl (i，t) represents the flight distance of the i-th crow at the t-th iteration; me (j，t) represents the memory position of crow i at the tth iteration; Step 4-5, update the memory value, sort by fitness value, and take the top N individuals as the new group; Step 4-6, repeat steps 4-3 to 4-5 until the termination condition is met, and output the optimal relay as the algorithm output.

6. The method according to claim 5, characterized in that In step 4-5, the memory value is updated according to the following formula:

7. The method according to claim 6, characterized in that In step 6, the design of a receiving response mechanism to enable the backup relay specifically includes: When the relay node receives a message, it will send a response signal to the source node via unicast. When the source node does not receive the response signal from the relay node, it will send a signal to the backup relay node via unicast to designate the backup relay node as a relay. After receiving the signal, the backup relay will execute the message forwarding procedure.

8. A V2X vehicle network emergency message forwarding system for implementing the method according to any one of claims 1 to 7, characterized in that: The system includes a V2X message preprocessing module, a message forwarding strategy module, a relay decision module and a standby relay decision module; The V2X message preprocessing module is used to calculate the impact radius, mobility factor, channel factor and location factor of the emergency message, and filter the processing of messages irrelevant to the vehicle; The message forwarding strategy module is used to determine the corresponding forwarding strategy to use in the current scenario; The message forwarding strategy module is used to decide on relay nodes, and uses the node's mobility factor, channel factor, and location factor for comprehensive analysis, and uses the CSA-GA optimization algorithm to decide on relay nodes and obtain a relay node sequence; The standby relay decision module is used to decide on a standby relay node when a relay link is interrupted, obtain the standby relay node, and continue to forward the emergency message.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores program codes, and when the program codes are executed by the processor, the processor executes the steps of the method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: A computer program or instruction is stored, and when the computer program or instruction is run on a computer, the steps of the method according to any one of claims 1 to 7 are executed.

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