Networked automobile collaborative awareness information transmission method

Abstract

The invention relates to a networked automobile cooperative sensing information transmission method, which comprises the following steps of: evaluating the priority of CAM (Content Addressable Memory) data packets by adopting an information value, setting differentiated reference signal receiving power thresholds for the CAM data packets with different priorities, and then sending the CAM data packets to a sending vehicle before the sending vehicle sends the CAM data packets. By re-evaluating the reservation condition of the sub-channel resources in the network, not only can the interference suffered by the high-priority CAM data packets during transmission be reduced, but also the mutual collision among the high-priority CAM data packets can be avoided, the transmission of redundant information is effectively reduced, and when the network of the networked automobile is in a congestion state, the transmission efficiency of the CAM data packets is improved. According to the technical scheme, the acceptance rate of the CAM data packets with the high priority can be improved to the maximum extent, so that the utilization rate of the CAM data packets with the high priority is improved, transmission of key information is guaranteed, and cooperative sensing information can be better shared among vehicles.

Description

Technical Field

[0001] The present invention relates to the field of 3GPP NRV2X communication technology, and in particular to a method for transmitting collaborative perception information of connected vehicles. Background Art

[0002] In 5G NR V2X MODE 2, connected vehicles can use two different resource scheduling schemes: Semi-Persistent Scheduling (SPS) and Dynamic Scheduling (DS). SPS is a periodic reservation of resources suitable for periodic messages of fixed size, while DS is a non-reservation scheme that requires new resources to be selected for each generated message and is suitable for non-periodic messages. The Cooperative Awareness Message (CAM) transmission mechanism uses the SPS scheduling scheme. Vehicles use selected subchannels to periodically transmit CAMs over a period of time, sharing real-time, periodic status information between vehicles to improve driving safety and traffic flow.

[0003] The transmission of collaborative perception information (CAM) is an important component of 5G NRV2X. It enables connected vehicles to exchange key driving data such as position, speed, and direction in real time, greatly enhancing the vehicle's ability to perceive the surrounding environment and providing important support for the collaborative perception technology of intelligent connected vehicles.

[0004] However, with the continuous evolution of connected vehicle technology, the amount of sensory data that connected vehicles must process is growing exponentially, and the complexity of intelligent driving algorithms is also rapidly increasing. This not only places tremendous pressure on connected vehicles in terms of data processing and computing, but also places an excessive burden on communication networks, resulting in the inability to meet the low-latency and high-reliability technical requirements for the transmission of collaborative sensory information. To meet this challenge, a more efficient collaborative sensory information transmission mechanism is urgently needed to optimize the efficiency of sensory information transmission and ensure the timeliness and accuracy of important information transmission, thereby supporting the safe, comfortable, and efficient driving goals of intelligent connected vehicles. Summary of the Invention

[0005] The technical problem to be solved by the present invention is how to optimize the transmission efficiency of perception information and ensure the timeliness and accuracy of the transmission of important information. In order to overcome the defects of the above-mentioned existing technologies, the present invention provides a method for collaborative perception information transmission of connected vehicles based on information value.

[0006] The present invention provides a method for transmitting cooperative sensing information of connected vehicles, wherein a sending vehicle in the connected vehicle randomly selects a vehicle within a communication range as a target receiving vehicle for communication, comprising:

[0007] Step 1. Within the base station coverage area, the base station broadcasts network sub-channel resource information to all vehicles within the coverage area, and the vehicles continuously monitor and record the signal receiving power on the sub-channel within the network;

[0008] Step 2. In time slot m, the sending vehicle senses the sub-channel resources in the network to reserve sub-channel resources. The reserved sub-channel resources are used to send CAM data packets containing its own location information, and the resource reservation interval RRI of the sending vehicle is preset. TX , perception window range [m-T0,mT proc ), select the window range [m+T1,m+T2], where T0, T1, and T2 are all preset constant values, and T proc Indicates the time required for the vehicle to complete the perception process;

[0009] Step 3: The sending vehicle searches for the time slot t of the historically transmitted CAM data packet within the sensing window. F , and judge t F +RRI i Is it within the selection window range [m+T1,m+T2]? If so, exclude time slot t F +RRI i , RRI i is any value in the resource reservation interval list RRI in the inner sub-channel resource information, and proceeds to step 4; if not, it is not excluded and proceeds to step 4;

[0010] Step 4. Traverse each time slot t in the selection window range G , and judge t F +RRI i Is it equal to t G +RRI TX , if so, delete time slot t G , if not, then keep time slot t G , then go to step 5;

[0011] Step 5. Traverse each time slot t retained in the selection window G , judge each time slot t G Whether the signal receiving power on the sub-channel within is greater than the preset reference signal receiving power threshold, if so, the sub-channel is excluded, if not, the sub-channel is retained; traversing to obtain a list of sub-channels with available resources;

[0012] Step 6. The sending vehicle randomly selects a subchannel from the subchannel list in step 5 to send a CAM data packet; after the CAM data packet is sent in the current cycle, m=m+T, and enters the next cycle, where T represents a scheduling cycle; and returns to step 2.

[0013] Compared with the prior art, the present application has the following advantages: screening the time slots and sub-channels within the time slots in the network through steps 2 to 5 helps to reduce the interference received by the CAM data packets during transmission, so as to ensure that the CAM data packets of the sending vehicle can be received by the target receiving vehicle, improve the acceptance rate of the CAM data packets between the sending vehicle and the target receiving vehicle, optimize the exchange of status information between vehicles, and provide solid technical support for the intelligent connected vehicles to achieve the situation goals of safety, comfort and efficiency.

[0014] In a possible implementation, in step 2, before sending the sub-channel resource information in the vehicle perception network to reserve the sub-channel, priority determination is first performed on the CAM data packet, specifically including:

[0015] A1. The sending vehicle updates its location information at preset time intervals to form a CAM data packet containing location information, defining the sending vehicle v j In t n The position at the moment [x j (t n ),y j (t n )] and speed The state vector of

[0016]

[0017] The sending vehicle is at t n-1 to t n The state prediction model within the time period is represented by:

[0018] x j (t n )=F(t n )x j (t n-1 )+w j (t n )

[0019] Where, w j (t n ) indicates that it obeys the Gaussian distribution N(0,Q j (t n )) process noise;

[0020] The sending vehicle measures its own position through the onboard sensor, and the measured value z j (t n ) is expressed as:

[0021] z j (t n )=Hx j (t n )+vj (t n )

[0022] Where, v j (t n ) indicates that it obeys the Gaussian distribution N(0,R j (t n )) measurement noise, so the position information contained in the CAM data packet follows the Gaussian distribution N(z j (t n ),R j (t n ));

[0023] A2. When the sending vehicle sends the generated CAM data packet to the target receiving vehicle, the target receiving vehicle provides feedback of the CAM data packet reception record to the sending vehicle. The sending vehicle uses a Kalman filter iterative algorithm based on the CAM data packet reception record to estimate the target receiving vehicle's position relative to the sending vehicle. Specifically, the following steps are performed:

[0024] First, use Indicates that the target receiving vehicle is based on t n' As well as the CAM received previously for vehicle v j In t n State prediction at time t n Indicates the moment when the nth CAM data packet is received; the predicted state Initialized to [0,0,0,0] T , its covariance matrix P j (t0|t0) is initialized to σ0 is an arbitrary value, I 4×4 is the identity matrix;

[0025] Secondly, the Kalman filter iterative algorithm specifically includes:

[0026] A201. Target receiving vehicle based on t n-1 The state prediction at the time and the state prediction model established in A1 predict the sending vehicle v j In t n The state prediction formula is expressed as:

[0027]

[0028] A202.Update The corresponding covariance matrix P j (t n |t n-1 ):

[0029] P j (t n |tn-1 )=F(t n )P j (t n-1 |t n-1 )F(t n ) T +Q(t n )

[0030] A203. According to t n The CAM data packets received at any moment correct the state prediction:

[0031]

[0032] Where, K(t n ) is the Kalman gain coefficient, and the calculation formula is:

[0033] K(t n )=P j (t n |t n-1 )H T (R(t n )+HP j (t n |t n-1 )H T ) -1

[0034] A204.Update The corresponding covariance matrix P j (t n |t n ):

[0035] P j (t n |t n )=(IK(t n )H)P j (t n |t n-1 );

[0036] A3. Using an information value assessment method, combined with the CAM packet reception record, the priority of the sending vehicle's current CAM packet is evaluated, specifically including:

[0037] A301. After completing the Kalman filter iteration for n CAM data packets, the target receiving vehicle uses A201 and A202 for the last iteration to predict the sending vehicle v j At the current time t n+1 Status And the corresponding covariance matrix P j (t n+1 |t n );

[0038] A302. Order Gaussian distribution The probability density function of K pri (x j (t n+1 ) as a priori estimate;

[0039] A303. When the target receiving vehicle receives the n+1th CAM data packet, the modified state prediction is calculated using A203 and A204. and the corresponding covariance matrix P j (t n+1 |t n+1 ),make Gaussian distribution The probability density function, and K pos (x j (t n+1 )) as the posterior estimate;

[0040] A304. Use KL divergence to measure the difference between the prior estimate and the posterior estimate, and use it as the information value of the n+1th CAM data packet. The calculation formula is:

[0041]

[0042] In the formula, VOI represents the value of information. By dividing the range of VOI into intervals, the intervals are divided into low priority, medium priority and high priority from low to high.

[0043] Compared with the existing technology, the above technical solution can accurately express the importance of the sending vehicle position information relative to the receiving vehicle. By applying it to the resource allocation strategy, the target receiving vehicle can more accurately infer the position of the sending vehicle.

[0044] In a possible implementation, the reference signal received power threshold preset in step 5 is set according to the priority of the CAM data packet. The higher the priority of the CAM data packet, the lower the reference signal received power threshold.

[0045] Compared with the existing technology, the above technical solution determines the priority of CAM data packets based on the information value of the CAM data packets during the sub-channel resource allocation stage within the network, and sets differentiated reference signal receiving power thresholds for CAM data packets of different priorities. This differentiated sub-channel resource allocation strategy within the network helps reduce the interference experienced by high-priority CAM data packets during transmission, ensures the efficient transmission of high-priority CAM data packets, maximizes the acceptance rate of high-priority CAM data packets, and ensures driving safety.

[0046] In one possible implementation, in step 6, before the sending vehicle randomly selects a sub-channel from the available sub-channel list in step 5 to send a CAM data packet, it first determines whether the CAM data packet to be sent is of high priority. If the CAM data packet is of high priority, steps 2 to 5 are repeated, and the sub-channel corresponding to the high-priority CAM data packet is re-evaluated to determine whether the sub-channel corresponding to the high-priority CAM data packet is in the available sub-channel list. If so, the high-priority CAM data packet is sent using the sub-channel corresponding to the high-priority CAM data packet. If not, proceed to step 6; if the CAM data packet is not of high priority, proceed directly to step 6.

[0047] Compared with the existing technology, the information value is used to evaluate the priority of the CAM data packet, and differentiated reference signal receiving power thresholds are set for CAM data packets of different priorities. Then, before the sending vehicle sends the CAM data packet, the reservation of sub-channel resources in the network is re-evaluated, which not only reduces the interference of high-priority CAM data packets during transmission, but also avoids mutual collisions between high-priority CAM data packets. The acceptance rate of high-priority CAM data packets is greatly improved, effectively reducing the transmission of redundant data. When the network of the connected car is in a congested state, the acceptance rate of high-priority CAM data packets can be maximized, thereby improving the utilization rate of high-priority CAM data packets, ensuring the transmission of key information, and enabling vehicles to better share collaborative perception information.

[0048] In a possible implementation, the sub-channel resource information within the network in step 1 includes the number of sub-channels, the time-frequency resource size of the sub-channels, and a resource reservation interval list RRI. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 Schematic diagram of the process of the specific embodiment 1 of the present invention;

[0050] Figure 2 This is a schematic diagram of a flow chart of a specific embodiment 2 of the present invention;

[0051] Figure 3 This is a Nago SUMO traffic scene diagram in the simulation implementation of the present invention;

[0052] Figure 4 is the cumulative distribution function of the trajectory tracking error of the simulation implementation results of the present invention;

[0053] Figure 5 It is the average packet receiving rate of CAM with different information values ​​in the simulation implementation results of the present invention. DETAILED DESCRIPTION

[0054] First, those skilled in the art should understand that these embodiments are merely used to explain the technical principles of the embodiments of the present application and are not intended to limit the scope of protection of the embodiments of the present application. Those skilled in the art may adjust them as needed to suit specific application scenarios.

[0055] In the description of the embodiments of this application, it should be noted that, unless otherwise specified or limited, the terms "connected" and "connection" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium. Those skilled in the art will understand the specific meanings of the above terms in the embodiments of this application based on the specific circumstances.

[0056] In the embodiments of the present application, unless otherwise specified and limited, the first feature being "above" or "below" the second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, the first feature being "above", "above" and "above" the second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. The first feature being "below", "below" and "below" the second feature may mean that the first feature is

[0057] The present application will be further described in detail below with reference to the accompanying drawings and specific embodiments. Specific embodiment 1

[0059] like Figure 1 A method for transmitting cooperative sensing information of connected vehicles is shown, in which a sending vehicle in a connected vehicle randomly selects a vehicle within a communication range as a target receiving vehicle for communication, including:

[0060] Step 1. Within the coverage area of ​​the base station, the base station broadcasts the sub-channel resource information within the network to all vehicles within the coverage area, and the vehicles continuously monitor and record the signal receiving power on the sub-channel within the network; the sub-channel resource information within the network includes the number of sub-channels, the time-frequency resource size of the sub-channel, and the resource reservation interval list RRI. In this specific embodiment, there are multiple sub-channel resources in one time slot.

[0061] Step 2. In time slot m, the sending vehicle senses the sub-channel resources in the network to reserve sub-channel resources. The reserved sub-channel resources are used to send CAM data packets containing its own location information, and the resource reservation interval RRI of the sending vehicle is preset. TX , perception window range [m-T0,mT proc ), select the window range [m+T1,m+T2], where T0, T1, and T2 are all preset constant values, and T procIndicates the time required for the vehicle to complete the perception process.

[0062] Step 3: The sending vehicle searches for the time slot t of the historically transmitted CAM data packet within the sensing window. F , and judge t F +RRI i Is it within the selection window range [m+T1,m+T2]? If so, exclude time slot t F +RRI i ;RRI i If it is any value in the resource reservation interval list RRI in the inner sub-channel resource information, the process goes to step 4; if not, it is not excluded and the process goes to step 4.

[0063] Step 4. Traverse each time slot t in the selection window range G , and judge t F +RRI i Is it equal to t G +RRI TX , if so, delete time slot t G , if not, then keep time slot t G , then go to step 5.

[0064] Step 5. Traverse each time slot t retained in the selection window G , judge each time slot t G Whether the signal receiving power on the sub-channel within is greater than a preset reference signal receiving power threshold, if so, the sub-channel is excluded, if not, the sub-channel is retained; traversing to obtain a list of sub-channels with available resources.

[0065] Step 6. The sending vehicle randomly selects a subchannel from the subchannel list in step 5 to send a CAM data packet; after the CAM data packet is sent in the current cycle, m=m+T, and enters the next cycle, where T represents a scheduling cycle; and returns to step 2. Specific embodiment 2

[0067] like Figure 2 A method for transmitting cooperative sensing information of connected vehicles is shown, in which a sending vehicle in a connected vehicle randomly selects a vehicle within a communication range as a target receiving vehicle for communication, including:

[0068] Step 1. Within the coverage area of ​​the base station, the base station broadcasts the sub-channel resource information within the network to all vehicles within the coverage area, and the vehicles continuously monitor and record the signal receiving power on the sub-channel within the network. The sub-channel resource information within the network includes the number of sub-channels, the time-frequency resource size of the sub-channel, and the resource reservation interval list RRI. In this specific embodiment, there are multiple sub-channel resources in one time slot.

[0069] Step 2. In time slot m, the sending vehicle senses the sub-channel resources in the network to reserve sub-channel resources. The reserved sub-channel resources are used to send CAM data packets containing its own location information, and the resource reservation interval RRI of the sending vehicle is preset. TX , perception window range [m-T0,mT proc ), select the window range [m+T1,m+T2], where T0, T1, and T2 are all preset constant values, and T proc Indicates the time required for the vehicle to complete the sensing process. In this specific embodiment, T0 = 100ms, T1 ≤ 3ms, T 2min ≤T2≤T PDB , T 2min =1ms, T PDB T is the maximum data packet delay allowed by the sending vehicle. proc Indicates the time required for the vehicle to complete the sensing process; by setting the subcarrier spacing to 15 kHz so that one time slot is equal to 1 ms; before the sending vehicle senses the subchannel resources in the network to reserve subchannel resources, a priority judgment is first made on the CAM data packet, specifically including A1. The sending vehicle updates the location information according to the preset time interval to form a CAM data packet containing the location information, and defines the sending vehicle v j In t n The position at the moment [x j (t n ),y j (t n )] and speed The state vector of The sending vehicle is at t n-1 to t n The state prediction model within the time period is represented by: j (t n )=F(t n )x j (t n-1 )+w j (t n );

[0070] Where, w j (t n ) indicates that it obeys the Gaussian distribution N(0,Q j (t n )) process noise;

[0071] The sending vehicle measures its own position through the onboard sensor, and the measured value z j (t n ) is expressed as:

[0072] z j(t n )=Hx j (t n )+v j (t n )

[0073] Where, v j (t n ) indicates that it obeys the Gaussian distribution N(0,R j (t n )) measurement noise, so the position information contained in the CAM data packet follows the Gaussian distribution N(z j (t n ),R j (t n ));

[0074] A2. When the sending vehicle sends a generated CAM data packet to the target receiving vehicle, the target receiving vehicle provides feedback on the CAM data packet reception record to the sending vehicle. Based on the CAM data packet reception record, the sending vehicle employs a Kalman filter iterative algorithm to estimate the target receiving vehicle's position relative to the sending vehicle, thereby ensuring that the sending vehicle accurately infers the target receiving vehicle's position relative to the sending vehicle. Specifically, this includes:

[0075] First, use Indicates that the target receiving vehicle is based on t n' As well as the CAM received previously for vehicle v j In t n State prediction at time t n Indicates the moment when the nth CAM data packet is received; the predicted state Initialized to [0,0,0,0] T , its covariance matrix P j (t0|t0) is initialized to σ0 is an arbitrary value, I 4×4 is the identity matrix;

[0076] Secondly, the Kalman filter iterative algorithm specifically includes:

[0077] A201. Target receiving vehicle based on t n-1 The state prediction at the time and the state prediction model established in A1 predict the sending vehicle v j In t n The state prediction formula is expressed as:

[0078]

[0079] A202.Update The corresponding covariance matrix P j (tn |t n-1 ):

[0080] P j (t n |t n-1 )=F(t n )P j (t n-1 |t n-1 )F(t n ) T +Q(t n )

[0081] A203. According to t n The CAM data packets received at any moment correct the state prediction:

[0082]

[0083] Where, K(t n ) is the Kalman gain coefficient, and the calculation formula is:

[0084] K(t n )=P j (t n |t n-1 )H T (R(t n )+HP j (t n |t n-1 )H T ) -1

[0085] A204.Update The corresponding covariance matrix P j (t n |t n ):

[0086] P j (t n |t n )=(IK(t n )H)P j (t n |t n-1 );

[0087] A3. Using an information value assessment method, combined with the CAM packet reception record, the priority of the sending vehicle's current CAM packet is evaluated, specifically including:

[0088] A301. After completing the Kalman filter iteration for n CAM data packets, the target receiving vehicle uses A201 and A202 for the last iteration to predict the sending vehicle v jAt the current time t n+1 Status And the corresponding covariance matrix P j (t n+1 |t n );

[0089] A302. Order Gaussian distribution The probability density function of K pri (x j (t n+1 ) as a priori estimate;

[0090] A303. When the target receiving vehicle receives the n+1th CAM data packet, the modified state prediction is calculated using A203 and A204. and the corresponding covariance matrix P j (t n+1 |t n+1 ),make Gaussian distribution The probability density function, and K pos (x j (t n+1 )) as the posterior estimate;

[0091] A304. Use KL divergence to measure the difference between the prior estimate and the posterior estimate, and use it as the information value of the n+1th CAM data packet. The calculation formula is:

[0092]

[0093] Wherein, VOI represents information value; by dividing the range of VOI into intervals, the interval range is divided into low priority, medium priority and high priority from low to high; in this specific embodiment, the information value range corresponding to the low-priority CAM data packet is [0, 1), the information value range corresponding to the medium-priority CAM data packet is [1, 2), and the information value range corresponding to the high-priority CAM data packet is [2, +∞).

[0094] Step 3: The sending vehicle searches for the time slot t of the historically transmitted CAM data packet within the sensing window. F , and judge t F +RRI i Is it within the selection window range [m+T1,m+T2]? If so, exclude time slot t F +RRI i ;RRI i If it is any value in the resource reservation interval list RRI in the inner sub-channel resource information, the process goes to step 4; if not, it is not excluded and the process goes to step 4.

[0095] Step 4. Traverse each time slot t in the selection window range G , and judge t F +RRI i Is it equal to t G +RRI TX , if so, delete time slot t G , if not, then keep time slot t G , then go to step 5.

[0096] Step 5. Traverse each time slot t retained in the selection window G , judge each time slot t G Whether the signal receiving power on the sub-channel within is greater than the preset reference signal receiving power threshold, if so, the sub-channel is excluded, if not, the sub-channel is retained; traverse to obtain a list of sub-channels with available resources; the preset reference signal receiving power threshold is set according to the priority of the CAM data packet, the higher the priority of the CAM data packet, the lower the reference signal receiving power threshold; in this specific embodiment, the differentiated setting of the reference signal receiving power threshold is to make the number of available sub-channels after exclusion account for X% of the total number of sub-channels within the selection window when CAM data packets of different priorities are performing sub-channel selection. In this specific embodiment, the proportion of available sub-channels after screening corresponding to high-priority CAM data packets is 20%, the proportion of available sub-channels after screening corresponding to medium-priority CAM data packets is 35%, and the proportion of available sub-channels after screening corresponding to low-priority CAM data packets is 50%, and X increases with decreasing priority.

[0097] Step 6. The sending vehicle randomly selects a subchannel from the subchannel list in Step 5 to send a CAM data packet. Prior to this, it is first determined whether the CAM data packet has a high priority. If the CAM data packet has a high priority, steps 2 to 5 are looped to re-evaluate the subchannel corresponding to the high-priority CAM data packet to determine whether the subchannel corresponding to the high-priority CAM data packet is still in the available subchannel list. If so, the high-priority CAM data packet is sent using the subchannel corresponding to the high-priority CAM data packet. If not, the process proceeds to Step 6. If the CAM data packet is not a high priority, the process proceeds directly to Step 6. After the CAM data packet is sent in the current cycle, m = m + T, and the next cycle begins, where T represents a scheduling cycle. The process then returns to Step 2. The priority of the CAM data packet is determined based on its information value, and differentiated reference signal received power thresholds are set for CAM data packets of different priorities. This differentiated network subchannel resource allocation strategy helps reduce interference experienced by high-priority CAM data packets during transmission, ensures efficient transmission of high-priority CAM data packets, maximizes the acceptance rate of high-priority CAM data packets, and ensures driving safety.

[0098] The present invention evaluates the priority of CAM data packets based on information value, and sets differentiated reference signal receiving power thresholds for CAM data packets of different priorities. Then, before the sending vehicle sends the CAM data packet, by re-evaluating the reservation of sub-channel resources in the network, not only can the interference of high-priority CAM data packets during transmission be reduced, but also collisions between high-priority CAM data packets can be avoided. The acceptance rate of high-priority CAM data packets is greatly improved, and the transmission of redundant information is effectively reduced. When the network of the connected car is in a congested state, the acceptance rate of high-priority CAM data packets can be maximized, thereby improving the utilization rate of high-priority CAM data packets, ensuring the transmission of key information, and enabling vehicles to better share collaborative perception information, providing solid technical support for intelligent connected cars to achieve safety, comfort and efficiency goals.

[0099] In the simulation implementation of the present invention, the scene is selected from the Monaco road scene simulated by SUMO, such as Figure 3 As shown in the figure, the coordinates of 50 vehicles were extracted over 20 seconds to simulate the vehicle trajectory changes in real driving scenarios. The simulation process is based on the update of the time step time (one time step is 1ms), specifically including:

[0100] Step 1. Set the initial time step time = 1ms;

[0101] Step 2. Every 100ms, the position of the sending vehicle is updated based on the SUMO data, and the trajectory of the target receiving vehicle is tracked;

[0102] Step 3. All sending vehicles generate CAM packets about their own location information and extract the CAM packet reception records of the target receiving vehicles; evaluate the priority of the CAM packets generated by the sending vehicles based on the contents of A1-A3;

[0103] Step 4. Sending the vehicle according to the priority of the CAM data packet, the collection of steps 2-5 to obtain the content of the sub-channel list available within the network as the reserved sub-channel resources for sending CAM data packets;

[0104] Step 5. The vehicle uses the reserved sub-channel resources to send CAM data packets, detects interfering vehicles using the same sub-channel resources, calculates the signal-to-interference-plus-noise ratio (SINR), calculates the packet reception rate (PRR) based on the SINR, generates a random number rand uniformly distributed between [0, 1], and determines whether rand < PRR is satisfied. If it is satisfied, it is determined that the target receiving vehicle has successfully received the packet, and the CAM packet reception record of the target receiving vehicle is updated and fed back to the sending vehicle; if not, it is determined that the target receiving vehicle has not received the CAM packet, and the reception record is not updated; proceed to Step 6.

[0105] Step 6. Update the time step, time = time + 1 ms. If time ≤ 20 s, return to Step 2; if not, end.

[0106] This simulation implementation is carried out in a Monte Carlo manner, and all simulation results are obtained based on 50 trials. For the simulation parameters and deployments of each trial, we set the number of vehicle users to 50 and the single simulation duration to 20 s. The detailed parameters are shown in Table 1.

[0107] Table 1. Simulation result data table

[0108] Number of vehicle users 50 vehicles Duration of one test 20s Number of trials 50 times Resource Reservation Interval (RRI) 100ms Resource reselection probability p 0.8 Number of sub-channel resources 3 Perception window length 100ms Select window length 100ms

[0109] To further evaluate the performance of the proposed scheme in this invention, the transmission mechanism without VoI optimization in this invention is used as a benchmark, and the trajectory tracking error and the average packet reception rate of CAM packets under the two schemes are compared. Figure 4 The data shown indicates that: under the implementation of the scheme in this invention, the proportion of data with a trajectory tracking error greater than 2 meters is generally smaller. At the same time, 90% of the trajectory errors are effectively controlled within 4.1 meters. Compared with the error range of 5 meters under the benchmark, this improvement means that the accuracy of trajectory tracking has been significantly improved, and the vehicle can more accurately infer the positions of surrounding vehicles, and the perception ability of the surrounding environment has been significantly enhanced.

[0110] In addition, this invention sets the highest priority for CAM packets with an information value (VoI) greater than 2. Figure 5 The data shows that: under the resource allocation scheme proposed in this invention, the reception rate of high-priority CAM packets is significantly higher than that of the benchmark, reaching more than 95%, while the benchmark fluctuates around 80%. This shows that the scheme proposed in this invention has unparalleled efficiency compared with the benchmark scheme when transmitting CAM packets with high information value (VoI), and can transmit key information more reliably.

[0111] Combined with Figure 4 and Figure 5The experimental results above show that the solution of the present invention effectively improves the reception rate of CAM packets with high value of information (VoI) and significantly reduces the error in vehicle trajectory tracking. After receiving CAM packets with high value of information (VoI), the target receiving vehicle can more accurately track the trajectories of surrounding vehicles. This shows that the present invention uses value of information (VoI) as a criterion for CAM packet priority evaluation, accurately reflecting the importance of different CAM packets. At the same time, the resource allocation strategy improved by value of information (VoI) successfully ensures the transmission of important information.

[0112] When the network is congested, the proposed solution can ensure the efficiency and accuracy of collaborative observation between connected vehicles. In practical applications, this improvement will directly translate into a smoother, safer and more comfortable driving experience. For example, in autonomous driving scenarios, vehicles can rely on more efficient and accurate collaborative perception information (CAM) to respond more quickly to emergencies and avoid potential collisions. Finally, by ensuring the accurate transmission of critical information, the proposed solution improves the efficiency of information exchange between connected vehicles, thereby optimizing the operational performance of the entire Internet of Vehicles system and providing the necessary technical support for the implementation of advanced use cases such as safety services and autonomous driving.

[0113] In the description of the embodiments of the present application, it should be noted that in the description of the present application, terms such as "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and does not indicate or imply that the device or component must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present application.

[0114] In the description of the present application, the description with reference to the terms "one embodiment", "some embodiments", "in the present embodiment", "specific example", or "some examples" means that the specific features, mechanisms, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, mechanisms, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0115] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for transmitting cooperative sensing information in connected vehicles, wherein a sending vehicle in a connected vehicle randomly selects a vehicle within a communication range as a target receiving vehicle for communication, characterized in that: include: Step 1. Within the base station coverage area, the base station broadcasts network sub-channel resource information to all vehicles within the coverage area, and the vehicles continuously monitor and record the signal receiving power on the network sub-channels. The sending vehicle periodically sends a CAM data packet containing its own location information to the target receiving vehicle via the network sub-channel resources. Step 2. In time slot m, the sending vehicle senses the sub-channel resources in the network to reserve sub-channel resources. The reserved sub-channel resources are used to send CAM data packets containing its own location information, and the resource reservation interval RRI of the sending vehicle is preset. TX , perception window range [m-T0,mT proc ), select the window range [m+T1,m+T2], where T0, T1, and T2 are all preset constant values, and T proc Indicates the time required for the vehicle to complete the perception process; Step 3: The sending vehicle searches for the time slot t of the historically transmitted CAM data packet within the sensing window. F , and judge t F +RRI i Is it within the selection window range [m+T1,m+T2]? If so, exclude time slot t F +RRI i ;RRI i is any value in the resource reservation interval list RRI in the inner sub-channel resource information, and proceeds to step 4; if not, proceeds to step 4; Step 4. Traverse each time slot t in the selection window range G , and judge t F +RRI i Is it equal to t G +RRI TX , if so, delete time slot t G , if not, then keep time slot t G , then go to step 5; Step 5. Traverse each time slot t retained in the selection window G , judge each time slot t G Whether the signal receiving power on the sub-channel within is greater than the preset reference signal receiving power threshold, if so, the sub-channel is excluded, if not, the sub-channel is retained; traversing to obtain a list of sub-channels with available resources; Step 6. The sending vehicle randomly selects a subchannel from the subchannel list in step 5 to send a CAM data packet; after the CAM data packet is sent in the current cycle, m=m+T, and enters the next cycle, where T represents a scheduling cycle; and returns to step 2.

2. The method for transmitting collaborative perception information of connected vehicles according to claim 1, characterized in that: In step 2, before sending the sub-channel resource information in the vehicle perception network to reserve the sub-channel, the priority of the CAM data packet is first determined, specifically including: A1. The sending vehicle updates its location information at preset time intervals to form a CAM data packet containing location information, defining the sending vehicle v j In t n The position at the moment [x j (t n ), y j (t n )] and speed The state vector of The sending vehicle is at t n-1 to t n The state prediction model within the time period is represented by: j (t n )=F(t n )x j (t n-1 )+w j (t n ); Where, w j (t n ) indicates that it obeys the Gaussian distribution N(0, Q j (t n )) process noise; The sending vehicle measures its own position through the onboard sensor, and the measured value z j (t n ) is expressed as: z j (t n )=Hx i (t n )+v j (t n ) Where, v j (t n ) indicates that it obeys the Gaussian distribution N(0, R j (t n )) measurement noise, so the position information contained in the CAM data packet follows the Gaussian distribution N(z j (t n ), R j (t n )); A2. When the sending vehicle sends the generated CAM data packet to the target receiving vehicle, the target receiving vehicle provides feedback of the CAM data packet reception record to the sending vehicle. The sending vehicle uses a Kalman filter iterative algorithm based on the CAM data packet reception record to estimate the target receiving vehicle's position relative to the sending vehicle. Specifically, the following steps are performed: First, use Indicates that the target receiving vehicle is based on t n′ As well as the CAM received previously for vehicle v j In t n State prediction at time t n Indicates the moment when the nth CAM data packet is received; the predicted state Initialized to [0, 0, 0, 0] T , its covariance matrix P j (t0|t0) is initialized to σ0 is an arbitrary value, I 4×4 is the identity matrix; Secondly, the Kalman filter iterative algorithm specifically includes: A201. Target receiving vehicle based on t n-1 The state prediction at the time and the state prediction model established in A1 predict the sending vehicle v j In t n The state prediction formula is expressed as: A202.Update The corresponding covariance matrix P j (t n |t n-1 ): P j (t n |t n-1 )=F(t n )P j (t n-1 |t n-1 )F(t n ) T +Q(t n ) A203. According to t n The CAM data packets received at any moment correct the state prediction: Where, K(t n ) is the Kalman gain coefficient, and the calculation formula is: K(t n )=P j (t n |t n-1 )H T (R(t n )+HP j (t n |t n-1 )H T ) -1 A204.Update The corresponding covariance matrix P j (t n |t n ): P j (t n |t n )=(I-K(t n ) H )P j (t n |t n-1 ); A3. Using an information value assessment method, combined with the CAM packet reception record, the priority of the sending vehicle's current CAM packet is evaluated, specifically including: A301. After completing the Kalman filter iteration for n CAM data packets, the target receiving vehicle uses A201 and A202 for the last iteration to predict the sending vehicle v j At the current time t n+1 Status And the corresponding covariance matrix P j (t n+1 |t n ); A302. Order Gaussian distribution The probability density function of K pri (x j (t n+1 ) as a priori estimate; A303. When the target receiving vehicle receives the n+1th CAM data packet, the modified state prediction is calculated using A203 and A204. and the corresponding covariance matrix P j (t n+1 |t n+1 ),make Gaussian distribution The probability density function of K pos (x j (t n+1 )) as the posterior estimate; A304. Use KL divergence to measure the difference between the prior estimate and the posterior estimate, and use it as the information value of the n+1th CAM data packet. The calculation formula is: In the formula, VOI represents the value of information. By dividing the range of VOI into intervals, the intervals are divided into low priority, medium priority and high priority from low to high.

3. The method for transmitting cooperative perception information of connected vehicles according to claim 2, characterized in that: The reference signal received power threshold preset in step 5 is set according to the priority of the CAM data packet. The higher the priority of the CAM data packet, the lower the reference signal received power threshold.

4. The method for transmitting connected vehicle collaborative perception information according to claim 2, characterized in that: In step 6, before the sending vehicle randomly selects a sub-channel from the sub-channel list in step 5 to send the CAM data packet, it first determines whether the CAM data packet is of high priority. If so, steps 2 to 5 are repeated to re-evaluate the sub-channel resources in the network, and then proceed to step 6; if not, directly proceed to step 6.

5. The method for transmitting cooperative perception information of connected vehicles according to claim 1, characterized in that: The sub-channel resource information in the network in step 1 includes the number of sub-channels, the time-frequency resource size of the sub-channels, and the resource reservation interval list RRI.

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