Vehicle Running Status Field Model-Based Information Transmission Frequency Optimization Method in Internet of Vehicles

Abstract

A vehicle running status field model-based information transmission frequency optimization method in the Internet of Vehicles belongs to the technical field of network communications. The method establishes a running status field model according to the real-time running status of a road vehicle to describe the degree of risk of the vehicle, the degree of risk can be used to dynamically adjust the transmission frequency of safety-critical information, and the transmission frequency of non-safety-critical information is adjusted through the real-time transmission frequency of safety-critical information to achieve the purpose of improving the utilization ratio of link. The method establishes the running status field model of a moving vehicle, uses the risk intensity of the vehicle in the running status field to describe the current running risk of the vehicle, and takes account of different application scenarios, thereby having generality. In addition, the improved network resource optimization method can effectively improve the communication efficiency of heterogeneous networks, and dynamically adjust the transmission frequency of safety-critical information through the magnitude of the risk intensity to improve the utilization ratio of link.

Claims

1. A vehicle running status field model-based information transmission frequency optimization method in the Internet of Vehicles, wherein a running status field model is established according to the real-time running status of a road vehicle to describe the degree of risk of the vehicle, the degree of risk is used to dynamically adjust the transmission frequency of safety-critical information, and the transmission frequency of non-safety-critical information is adjusted through the real-time transmission frequency of safety-critical information; and the method comprises the following steps: (1) acquiring real-time road information through the Internet of Vehicles, including vehicle velocity V, vehicle distance r, road width d and vehicle type m; (2) with the vehicle as objective i as the reference system, establishing a vehicle running status field model: describing the degree of risk of the vehicle according to the Doppler effect and the running status field model, as shown in formula (1); $\begin{array}{cc}\{\begin{array}{c}{E}_i=\frac{K}{K-V\cos \theta }.Math.\frac{G{M}_i}{|r{|}^2}\\ V=V_i-V_0\\ M_i=m_i^{\prime }|V_i{|}^2\\ M_0=m_0^{\prime }.Math.|V_0{|}^2\\ F_0=E_i.Math.M_0\end{array}& \left(1\right)\end{array}$ wherein K and G are constants; the value of K is the maximum velocity allowed by the road, K=150 km/h, G=1, and M.sub.i is the relative mass of the vehicle as objective i and is related to the vehicle type and the vehicle velocity; and v.sub.0 is the velocity of the vehicle as observer 0, V.sub.i is the velocity of the vehicle as objective i, and θ is an included angle between the connection direction of the vehicle as objective i and the vehicle as observer 0 and the movement direction of the vehicle as objective i and is calculated by formula (2); $\theta =\hspace{1em}\hspace{1em}\{\begin{array}{cc}\frac{}{2}-\arcsin .Math.\frac{d}{r}.Math.& \mathrm{vehicle}\mathrm{as}\mathrm{observer}0\mathrm{is}\mathrm{in}\mathrm{front}\mathrm{of}\mathrm{vehicle}\mathrm{as}\mathrm{objective}i\\ \frac{}{2}+\arcsin .Math.\frac{d}{r}.Math.& \mathrm{vehicle}\mathrm{as}\mathrm{observer}0\mathrm{is}\mathrm{behind}\mathrm{vehicl}e\mathrm{as}\mathrm{objective}i\end{array}$ m is the vehicle type; and formula (3) is obtained after normalization; $\begin{array}{cc}{m}_i^{\prime }=\frac{m_i}{m_i+1}& \left(3\right)\end{array}$ F.sub.0 is the degree of risk of the vehicle as observer 0 in the running status field E; F.sub.MAX is defined as the maximum degree of risk of the vehicle as observer: $\begin{array}{cc}{F}_{\mathrm{MAX}}=\frac{K}{K-V}.Math.\frac{{\mathrm{GM}}_i{M}_0}{{.Math.s.Math.}^2}& \left(4\right)\end{array}$ wherein s is the minimum safe distance for vehicle running and is related to the current velocity of the vehicle; (3) calculating the transmission frequency of safety-critical information: calculating the real-time transmission frequency of WSM according to the obtained degree of risk of the vehicle: $\begin{array}{cc}{f}_{\mathrm{WSM}}=\{\begin{array}{cc}.Math.\frac{F_0}{F_{\mathrm{MAX}}}\times 10.Math.& F_0\le F_{\mathrm{MAX}}\\ 10& F_0>F_{\mathrm{MAX}}\end{array}& \left(5\right)\end{array}$ wherein F.sub.0 is the risk intensity of the vehicle as observer 0, and F.sub.MAX is the maximum risk intensity; and when F.sub.0≤F.sub.MAX, the vehicle is in a steady status, the transmission frequency of WSM is automatically adjusted with the ratio of F.sub.0 to F.sub.MAX; when F.sub.0>F.sub.MAX, the vehicle is in a risk status, and at this time, the transmission frequency of WSM is the largest; (4) calculating the maximum transmission frequency of non-safety-critical information the calculation formula for the number c of non-WSM that can be transmitted by the IEEE 802.11p link in a WSM cycle is $c=\frac{T}{f};$ wherein T is the current maximum throughput of the link, and f is the transmission frequency of WSM; and by judging whether the remaining space of the send buffer at the MAC layer is larger than c, the maximum distribution frequency f.sub.u max of non-safety-critical messages of the IEEE 802.11p link is obtained as follows: $\begin{array}{cc}{f}_{u\max }=\{\begin{array}{cc}f.Math.c& L_{\mathrm{MAX}}-L\left(t\right)\ge c\\ f\left(L_{\mathrm{MAX}}-L\left(t\right)\right)& L_{\mathrm{MAX}}-L\left(t\right)<c\end{array}& \left(6\right)\end{array}$ wherein L.sub.MAX is the maximum load value of the link, and L(t) is the current load value of the link; when the distribution frequency of non-WSM of the IEEE 802.11p link reaches f.sub.u max, WSM and non-WSM reach Pareto Optimality, and both obtain the maximum transmission benefit; (5) selecting a link: the set of links is N{0,1,2 . . . i}, wherein 0 represents the 802.11p link, and 1-i represent other links; acquiring the data message type, if the type is safety-critical information WSM, directly transmitting the data message by the 802.11p link, and if the type is non-safety-critical information, selecting a transmission link; and selecting a link according to the delayed response time RTT and the link load L(T), and determining whether to transmit on the 802.11p link or a link rather than 802.11p, as shown in formula (7); $\begin{array}{cc}{W}_{\mathrm{LS}-i}=\{\begin{array}{cc}{\left(\frac{\mathrm{RTT}}{{\mathrm{RTT}}_{\max }}+\frac{L\left(t\right)}{L_{\max }-L_{\mathrm{safe}}\left(t\right)}\right)}_{802.11p}& \mathrm{if}i=0\\ {\left(\frac{\mathrm{RTT}}{{\mathrm{RTT}}_{\max }}+\frac{L\left(t\right)}{L_{\max }}\right)}_i& \mathrm{if}i\ne 0\end{array}& \left(7\right)\end{array}$ wherein W.sub.LS-0 is the selection weight of the 802.11p link, W.sub.LS-i is the selection weight of the i.sup.th link, RTT.sub.max is the maximum allowable delayed response time of the link, and L.sub.max is the maximum load of the link; and L.sub.safe is the estimated safety-critical information traffic, i∈N, and the expression thereof is (8);
L.sub.safe(t)=f.sub.WSM.Math.P.Math.R  (8) wherein f.sub.WSM is the transmission frequency of safety-critical information obtained in step (3); and P is the number of security applications in the current network, R is the average communication distance between vehicles collected in the current network, and such parameters are obtained by communications between vehicles and the network; when the i link exists to let W.sub.LS-i≤W.sub.LS-0, the i link is selected to transmit the non-safety-critical information message, and if W.sub.LS-i>W.sub.LS-0 for any link i, the 802.11p link is selected to transmit the non-safety-critical information message; when it is determined that the non-safety-critical information message is transmitted on the 802.11p link, entering step (6); and if the non-safety-critical information message is transmitted on a link rather than 802.11p, transmitting according to the transmission mechanism of the underlying layer of the link; (6) calculating the distribution frequency of non-safety-critical data message; If the data message p is distributed to the IEEE 802.11p link, it is required to calculate the maximum distribution frequency f.sub.u max of non-WSM of the IEEE 802.11p link by formula (6), and then the two latest non-safety-critical messages arriving on the IEEE 802.11p link are used to calculate the instantaneous distribution frequency f.sub.u of non-safety-critical information on the IEEE 802.11p link at this time; $\begin{array}{cc}{f}_u=\frac{1}{t_2-t_1}& \left(9\right)\end{array}$ wherein t.sub.1, t.sub.2 are the arrival time of two adjacent non-safety-critical information messages on the link; when f.sub.u≤f.sub.u max, the non-safety-critical message is transmitted in the 802.11p link, and when f.sub.u>f.sub.u max, the non-safety-critical message is discarded to ensure the normal transmission of safety-critical messages.

Description

DESCRIPTION OF DRAWINGS

[0030] FIG. 1 is a schematic diagram of Vehicle to Everything (V2X) in the Internet of Vehicles.

[0031] In the figure, 1 is a base station (road side unit), 2 is a transport facility, and 3 is a vehicle.

[0032] FIG. 2 is a schematic diagram of degree of risk distribution of a moving vehicle i.

[0033] FIG. 3 is a schematic diagram of a traffic scenario for vehicle running.

[0034] FIG. 4 is a schematic diagram of an MAC sublayer of an LLC layer.

[0035] FIG. 5 is a flow chart of a vehicle running status field model-based information transmission frequency optimization method.

DETAILED DESCRIPTION

[0036] Detailed description of the present invention is described below in combination with accompanying drawings.

Step 1. Acquiring Data

[0037] Acquiring the information of the road and neighbor vehicles in the network at a frequency of 10 Hz per second, including vehicle velocity V vehicle distance r, road width d and vehicle type m.

Step 2. Establishing a Vehicle Running Status Field Model

[0038] With the vehicle as objective i as the reference system, establishing a vehicle running status field model. Calculating the relative velocity of the surrounding vehicles. Mutual influence exists between vehicles and vehicles and between vehicles and objects, the effect thereof can be equivalently regarded as a “physical field” which is similar to a charge field, vehicles and objects can be equivalently regarded as electric charges, and each electric charge is influenced by other electric charges.

[0039] The charge field is used to describe the vehicle running status field. Objects on the road generally include vehicles, obstacles and pedestrians. The size of the running status field depends on the types and velocities of the objects. When an object is in motion, the distribution of the running status field formed thereby is different from that in a static status. From the practical experience, the degree of risk in front of a moving object is higher than the degree of risk behind, as shown in FIG. 2, which is similar to the Doppler effect. The Doppler effect refers to the change in the wavelength of a wave radiated by an object due to the relative movement of the wave source and the mover. In front of a moving wave source, the wavelength becomes shorter and the frequency becomes higher; and behind the moving wave source, the wavelength becomes longer and the frequency becomes lower.

[0040] The vehicle running status field model is related to the vehicle type, the vehicle velocity and the vehicle distance. Such information can be obtained in real time through real-time communication between the vehicle and the road side unit or other vehicles.

[0041] The degree of risk of the vehicle is described according to the Doppler effect and the running status field model, as shown in formula (1).

[00010]$\begin{array}{cc}\{\begin{array}{c}{E}_i=\frac{K}{K-V\cos \theta }.Math.\frac{G{M}_i}{{.Math.r.Math.}^2}\\ V=V_i-V_0\\ M_i=m_i^{\prime }{.Math.V_i.Math.}^2\\ M_0=m_0^{\prime }.Math.{.Math.V_i.Math.}^2\\ F_0=E_i.Math.M_0\end{array}& \left(1\right)\end{array}$

[0042] wherein K and G are constants. The value of K is the maximum velocity allowed by the road, generally, K=150 km/h, G=1, and M.sub.i is the relative mass of the vehicle as objective i and is related to the vehicle type and the vehicle velocity. V.sub.0 is the velocity of the vehicle as observer 0, V.sub.i is the velocity of the vehicle as objective i, and θ is an included angle between the connection direction of the vehicle as objective i and the vehicle as observer 0 and the movement direction of the vehicle as objective i and is calculated by formula (2).

[00011]$\begin{array}{cc}\theta =\{\begin{array}{cc}\frac{\pi }{2}-\arcsin .Math.\frac{d}{r}.Math.& \begin{array}{c}\mathrm{vehicle}\mathrm{as}\mathrm{observer}0\mathrm{is}\mathrm{in}\\ \mathrm{front}\mathrm{of}\mathrm{vehicle}\mathrm{as}\mathrm{objective}i\end{array}\\ \frac{\pi }{2}+\arcsin .Math.\frac{d}{r}.Math.& \begin{array}{c}\mathrm{vehicle}\mathrm{as}\mathrm{observer}0\mathrm{is}\\ \mathrm{behind}\mathrm{vehicle}\mathrm{as}\mathrm{objective}i\end{array}\end{array}& \left(2\right)\end{array}$

[0043] m is the vehicle type; and according to the actual situation, the moving objects on the road are divided into 6 types: 1: obstacle, 2: pedestrian, 3: non-motorized vehicle, 4: small vehicle, 5: medium vehicle, and 6: large vehicle. Formula (3) is obtained after normalization.

[00012]$\begin{array}{cc}{m}_i^{\prime }=\frac{m_i}{m_i+1}& \left(3\right)\end{array}$

[0044] F.sub.0 is the degree of risk of the vehicle as observer 0 in the running status field E.

[0045] F.sub.MAX is defined as the maximum degree of risk of the vehicle as observer:

[00013]$\begin{array}{cc}{F}_{\mathrm{MAX}}=\frac{K}{K-V}.Math.\frac{{\mathrm{GM}}_i{M}_0}{|s{|}^2}& \left(4\right)\end{array}$

[0046] wherein s is the minimum safe distance for vehicle running and is related to the current velocity of the vehicle, and the acquisition method is shown in Table 1 below.

TABLE-US-00001 TABLE 1 Relationship between Safe Distance and Running Velocity Running Nature Condition Safe Distance High-Speed Running V >100 km/h s ≥m Fast Running 70 km/h < V ≤ 100 km/h s ≥V Medium-Speed Running 40 km/h < V ≤ 70 km/h s ≥60 m Low-Speed Running 20 km/h < V ≤ 40 km/h s ≥30 m Slow Running V ≤20 km/h s ≥10 m

[0047] Information distribution mechanism: In the environment of the Internet of Vehicles, according to the degree of urgency of data, data messages are mainly divided into two types: safety-critical information (WSM) and non-safety-critical information, as shown in FIG. 3. To ensure the transfer efficiency of WSM and meet the transfer needs of security applications, in the process of transmitting the data messages from the LLC layer to the MAC layer, the transmission frequency of non-safety-critical message shall be limited, but in the multi-MAC and multi-link Internet of Vehicles, the distribution frequency of non-safety-critical message from the LLC layer to the IEEE 802.11p link is the largest.

Step 3. Calculating the Transmission Frequency of Safety-Critical Information

[0048] The current status message broadcast frequency specified by the Internet of Vehicles communication protocol standard is 1 Hz-10 Hz. The higher the frequency is, the more frequent the safety-critical message exchange of vehicles is, and the safer the environment in which vehicles move is, but more channel resources will be occupied. When the actual traffic situation is not particularly complex, the idle safety-critical information channel resources can be transferred to non-safety-critical information for transmission, thereby improving the utilization ratio of channel. The technical solution is as follows:

[0049] Calculating the real-time transmission frequency of WSM according to the degree of risk of the vehicle obtained above:

[00014]$\begin{array}{cc}{f}_{\mathrm{WSM}}=\{\begin{array}{cc}.Math.\frac{F_0}{F_{\mathrm{MAX}}}\times 10.Math.& F_0\le F_{\mathrm{MAX}}\\ 10& F_0>F_{\mathrm{MAX}}\end{array}& \left(5\right)\end{array}$

wherein F.sub.0 is the risk intensity of the vehicle as observer 0, and F.sub.MAX is the maximum risk intensity. When F.sub.0≤F.sub.MAX, the vehicle is in a steady status, the transmission frequency of WSM is automatically adjusted with the ratio of F.sub.0 to F.sub.MAX; when F.sub.0>F.sub.MAX, the vehicle is in a risk status, and at this time, the transmission frequency of WSM is the largest.

Step 4. Calculating the Maximum Transmission Frequency of Non-Safety-Critical Information

[0050] In the process of data distribution, WSM and non-WSM are in a competitive relationship, but in the environment of the Internet of Vehicles, the benefit of WSM shall be guaranteed first. Therefore, on the premise that the benefits of WSM are not impaired, the benefit of non-WSM shall be maximized, the result obtained is Pareto Optimality, and the maximum distribution frequency of non-WSM currently adopted is the Pareto optimal solution.

[0051] The calculation formula for the number c of non-WSM that can be transmitted by the IEEE 802.11p link in a WSM cycle is

[00015]$c=\frac{T}{f}.$

[0052] wherein T is the current maximum throughput of the link, and f is the transmission frequency of WSM.

[0053] In an ideal status, after a non-safety-critical message with a size of c is transmitted, the next safety-critical message can be transmitted directly without waiting, which will not affect the transmission requirements of safety-critical messages. Therefore, in actual conditions, by judging whether the remaining space of the send buffer at the MAC layer is larger than C the maximum distribution frequency f.sub.u max of non-safety-critical messages of the IEEE 802.11p link can be obtained as follows:

[00016]$\begin{array}{cc}{f}_{u\max }=\{\begin{array}{cc}f.Math.c& L_{\mathrm{MAX}}-L\left(t\right)\ge c\\ f\left(L_{\mathrm{MAX}}-L\left(t\right)\right)& L_{\mathrm{MAX}}-L\left(t\right)<c\end{array}& \left(6\right)\end{array}$

[0054] wherein L.sub.MAX is the maximum load value of the link, and L(t) is the current load value of the link.

[0055] When the distribution frequency of non-WSM of the IEEE 802.11p link reaches f.sub.u max, WSM and non-WSM reach Pareto Optimality, and both obtain the maximum transmission benefit.

Step 5. Selecting a link

[0056] The set of links is N{0,1,2 . . . i}, wherein 0 represents the 802.11p link, and 1-i represent other links. Acquiring the data message type, if the type is safety-critical information (WSM), directly transmitting the data message by the 802.11p link, and if the type is non-safety-critical information, selecting a transmission link. Selecting a link according to the delayed response time RTT and the link load L(T), and determining whether to transmit on the 802.11p link or a link rather than 802.11p, as shown in formula (7).

[00017]$\begin{array}{cc}{W}_{\mathrm{LS}-i}=\{\begin{array}{cc}{\left(\frac{\mathrm{RTT}}{{\mathrm{RTT}}_{\max }}+\frac{L\left(t\right)}{L_{\max }-L_{\mathrm{safe}}\left(t\right)}\right)}_{802.11p}& \mathrm{if}i=0\\ {\left(\frac{\mathrm{RTT}}{{\mathrm{RTT}}_{\max }}+\frac{L\left(t\right)}{L_{\max }}\right)}_i& \mathrm{if}i\ne 0\end{array}& \left(7\right)\end{array}$

[0057] wherein W.sub.LS-0 is the selection weight of the 802.11p link, W.sub.LS-i is the selection weight of the i.sup.th link, RTT.sub.max is the maximum allowable delayed response time of the link, and L.sub.max is the maximum load of the link. L.sub.safe is the estimated safety-critical information traffic, i∈N, and the expression thereof is (8).

L.sub.safe(t)=f.sub.WSM.Math.P.Math.R  (8)

[0058] wherein f.sub.WSM is the transmission frequency of safety-critical information obtained in step 3. P is the number of security applications in the current network, R is the average communication distance between vehicles collected in the current network, and such parameters can be obtained by communications between vehicles and the network.

[0059] When the i link exists to let W.sub.LS-i≤W.sub.LS-0, the i link is selected to transmit the non-safety-critical information message, and if W.sub.LS-i>W.sub.LS-0 for any link i, the 802.11p link is selected to transmit the non-safety-critical information message.

[0060] When it is determined that the non-safety-critical information message is transmitted on the 802.11p link, entering step 6. If the non-safety-critical information message is transmitted on a link rather than 802.11p, transmitting according to the transmission mechanism of the underlying layer of the link. For example, congestion waiting and the like are handled according to the original link strategy. The present invention is not excessively limited in this portion.

Step 6. Calculating the Distribution Frequency of Non-Safety-Critical Data Message.

[0061] After the above two steps, if the data message p is distributed to the IEEE 802.11p link, it is required to calculate the maximum distribution frequency f.sub.u max of non-WSM of the IEEE 802.11p link by (6), and then the two latest non-safety-critical messages arriving on the IEEE 802.11p link are used to calculate the instantaneous distribution frequency f.sub.u of non-safety-critical information on the IEEE 802.11p link at this time.

[00018]$\begin{array}{cc}{f}_u=\frac{1}{t_2-t_1}& \left(9\right)\end{array}$

[0062] wherein t.sub.1, t.sub.2, are the arrival time of two adjacent non-safety-critical information messages on the link; when f.sub.u≤f.sub.u max, the non-safety-critical message can be transmitted in the 802.11p link, and when f.sub.u>f.sub.u max, the non-safety-critical information message is discarded to ensure the normal transmission of safety-critical messages.