Automatic driving automobile market game analysis method and system and storage medium

Abstract

The invention provides an automatic driving automobile market game analysis method and system and a storage medium, and the method comprises the steps: determining game participating groups as a government, an automobile enterprise and a consumer, and determining a game strategy set according to the government, the automobile enterprise and the consumer; constructing a perception income matrix according to the game strategy set; constructing an evolutionary game model of the government, the vehicle enterprise and the consumer, and solving the evolutionary game model according to the perception income matrix to obtain an original pure strategy equilibrium point; performing stability analysis on the evolutionary game model according to the original pure strategy equilibrium point to obtain a target pure strategy equilibrium point of the evolutionary game model; and performing analysis according to the target pure strategy equilibrium point to obtain an optimal strategy combination of the government, the vehicle enterprise and the consumer. The method provides a scientific basis for the government to make policies, improves the prediction accuracy of the purchase willingness of the consumer, and promotes the healthy and sustainable development of the automatic driving automobile market.

Description

Technical Field

[0001] The present invention mainly relates to the technical field of automobile market data analysis, and specifically to a method, system and storage medium for analyzing the market game of autonomous driving vehicles. Background Art

[0002] With the rapid development of autonomous driving technology, autonomous vehicles are gradually becoming an important part of future transportation. However, the existing market promotion of autonomous vehicles faces multiple challenges, including technical bottlenecks, legal and regulatory restrictions, and low consumer acceptance. In order to promote the research and development and marketization of autonomous vehicles, governments have introduced policies to support them, such as providing research and development funds, tax cuts, and car purchase subsidies. However, the effectiveness of these policies is still uncertain and lacks systematic analysis.

[0003] At present, the existing technologies mainly focus on the following aspects:

[0004] 1. Technology R&D and innovation: Most research focuses on the algorithms, hardware and system optimization of autonomous driving technology, and is committed to improving the safety and reliability of autonomous driving vehicles.

[0005] 2. Policy formulation and implementation: Governments around the world have introduced a variety of support policies, such as tax incentives, financial subsidies, and infrastructure construction, to promote the marketization of autonomous vehicles.

[0006] 3. Consumer behavior research: Some studies have analyzed consumers’ acceptance of and willingness to purchase self-driving cars, but most of them are based on traditional economic theories and fail to fully consider consumers’ decision-making behavior under uncertain conditions.

[0007] Although existing research has provided certain theoretical and practical support for the development of autonomous vehicles, there are still the following major shortcomings:

[0008] 1. Lack of systematic policy effect analysis: Existing research mostly focuses on the effect evaluation of a single policy, and fails to systematically analyze the comprehensive impact of multiple policy combinations on the autonomous driving vehicle market.

[0009] 2. Inadequate consumer behavior models: Traditional consumer behavior models fail to fully consider decision-making behavior under prospect theory, that is, the asymmetric response of consumers when faced with gains and losses, resulting in inaccurate predictions of consumer purchasing intentions.

[0010] 3. Lack of analysis on the interaction between government and enterprises: There is a lack of systematic analysis on the interactive relationship between government policies and the R&D and promotion behaviors of automobile enterprises, which fails to reveal the dynamic game process and its evolutionary stable state of all parties under different policy environments. Summary of the invention

[0011] The technical problem to be solved by the present invention is to provide a method, system and storage medium for analyzing the market game of autonomous vehicles in view of the shortcomings of the prior art.

[0012] The technical solution of the present invention to solve the above technical problem is as follows: A method for analyzing the market game of autonomous driving vehicles, comprising the following steps:

[0013] S1. Determine the game subjects as the government, car companies and consumers, and construct the game subject behavior strategy set based on the behaviors of the government, car companies and consumers;

[0014] S2. constructing a perceived benefit matrix according to the game subject behavior strategy set;

[0015] S3. Construct an evolutionary game model among the government, car companies and consumers, solve the evolutionary game model according to the perceived benefit matrix, and obtain the original pure strategy equilibrium point;

[0016] S4. Performing stability analysis on the evolutionary game model according to the original pure strategy equilibrium point to obtain a target pure strategy equilibrium point of the evolutionary game model;

[0017] S5. Analyze the target pure strategy equilibrium point to obtain the optimal strategy combination of the government, car companies and consumers.

[0018] On the basis of the above technical solution, the present invention can also be improved as follows:

[0019] Furthermore, in S1, a set of game subject behavior strategies is constructed based on the behaviors of the government, car companies and consumers, specifically:

[0020] Based on the government support behavior, a set of government support behavior strategies is constructed, expressed as α = {α1, α2}, where α1 is a high-intensity government support behavior and α2 is a low-intensity government support behavior. The high-intensity government support behavior means that the government supports the research and development of autonomous vehicles by providing incentive policies, and the low-intensity government support behavior means that no active measures are taken to interfere with the research and development of autonomous vehicles by car companies and the purchase of autonomous vehicles by consumers;

[0021] Based on the R&D behavior of automobile companies, a set of R&D behavior strategies for automobile companies is constructed, which is expressed as β = {β1, β2}, where β1 is the positive behavior of automobile companies and β2 is the negative behavior of automobile companies. The positive behavior of automobile companies means that automobile companies actively invest in R&D resources and vigorously introduce talents to carry out the R&D of autonomous driving technology. The negative behavior of automobile companies means that the R&D of autonomous driving vehicles takes negative measures or still adopts conventional methods to produce and sell vehicles.

[0022] A consumer purchase behavior strategy set is constructed based on the consumer purchase intention, which is expressed as γ = {γ1, γ2}, where γ1 is the consumer purchase behavior and γ2 is the consumer non-purchase behavior. The consumer purchase behavior indicates that the consumer chooses to buy an autonomous driving car instead of a traditional car when the consumer has the intention to buy a car. The consumer non-purchase behavior indicates that the consumer has not chosen to buy an autonomous driving car for the time being and maintains a wait-and-see attitude towards the purchase of an autonomous driving car, considering the potential safety risks, technical failures and possible losses of the autonomous driving car.

[0023] The government support behavior, the car enterprise R&D behavior and the consumer purchase behavior are arranged and combined to obtain a game subject behavior strategy set, wherein the game subject behavior strategy set includes: a first strategy combination: high-intensity government support behavior α1, car enterprise positive behavior β1, consumer purchase behavior γ1; a second strategy combination: high-intensity government support behavior α1, car enterprise positive behavior β1, consumer non-purchase behavior γ2; a third strategy combination: high-intensity government support behavior α1, car enterprise negative behavior β2, consumer purchase behavior γ1; a fourth strategy combination: high-intensity government support behavior α1, car enterprise negative behavior β2, consumer non-purchase behavior γ2; a fifth strategy combination: low-intensity government support behavior α2, car enterprise positive behavior β1, consumer purchase behavior γ1; a sixth strategy combination: low-intensity government support behavior α2, car enterprise positive behavior β1, consumer non-purchase behavior γ2; a seventh strategy combination: low-intensity government support behavior α2, car enterprise negative behavior β2, consumer purchase behavior γ1; an eighth strategy combination: low-intensity government support behavior α2, car enterprise negative behavior β2, consumer non-purchase behavior γ2.

[0024] Furthermore, in S2, a perception benefit matrix is ​​constructed according to the game subject behavior strategy set, specifically:

[0025] Construct a first matrix according to the first strategy combination, wherein the first matrix includes a government benefit expression -QPK*r+G1-Hs*L, a car company benefit expression P+V1-W+s*LF, and a consumer benefit expression H-C+M1+F;

[0026] Construct a second matrix according to the second strategy combination, wherein the second matrix includes a government benefit expression -QPK*r+G1-s*L, a car company benefit expression P+V1-W+s*L, and a consumer benefit expression M2;

[0027] Construct a third matrix according to the third strategy combination, wherein the third matrix includes a government benefit expression -Q-P+G1-Hs*L+N, a car company benefit expression P-N+V2-D, and a consumer benefit expression H-C+M1;

[0028] Construct a fourth matrix according to the fourth strategy combination, wherein the fourth matrix includes a government benefit expression -Q-P+G1-s*L+N, a car company benefit expression P-N+V2-D, and a consumer benefit expression M2;

[0029] Constructing a fifth matrix according to the fifth strategy combination, the fifth matrix including the government benefit expression 0, the car company benefit expression V1-WF and the consumer benefit expression -C+M1+F;

[0030] Constructing a sixth matrix according to the sixth strategy combination, the sixth matrix including a government benefit expression 0, a car company benefit expression V1-W and a consumer benefit expression M2;

[0031] Construct a seventh matrix according to the seventh strategy combination, wherein the seventh matrix includes a government benefit expression 0, a car company benefit expression V2-D, and a consumer benefit expression -C+M1;

[0032] Constructing an eighth matrix according to the eighth strategy combination, wherein the eighth matrix includes a government benefit expression 0, a car company benefit expression V2-D, and a consumer benefit expression M2;

[0033] Combining the first matrix, the second matrix, the third matrix, the fourth matrix, the fifth matrix, the sixth matrix, the seventh matrix, and the eighth matrix into a perceived benefit matrix;

[0034] Among them, Q represents the additional cost when the government implements high-intensity support behavior compared with low-intensity support behavior, P represents the financial subsidies provided to car companies when the government implements high-intensity support behavior, H represents the car purchase subsidies provided to consumers when the government implements high-intensity support behavior, L represents the government's tax incentives for car companies with positive behavior, s represents the government's preference coefficient for car companies' technological innovation, N represents the economic penalty for environmental and other losses caused by companies without positive behavior under the government's high-intensity support behavior, K represents the losses caused by the negative impact of car companies' positive behavior on autonomous driving car accidents under the government's high-intensity support behavior, r represents the negative impact coefficient, and G1 represents the government's high-intensity support behavior due to the implementation of high-intensity support behavior. is the additional perceived benefit obtained from low-intensity support behavior, G2 represents the perceived benefit obtained by the government from implementing low-intensity support behavior, W represents the cost for automakers to actively produce and sell self-driving cars, D represents the cost for automakers to passively produce and sell self-driving cars, F represents the additional discount given to consumers by automakers for actively selling self-driving cars, V1 represents the perceived benefit obtained by automakers from actively selling self-driving cars, V2 represents the perceived benefit obtained by automakers from maintaining the original car production, C represents the additional cost of consumer purchasing behavior compared to traditional driving cars, M1 represents the perceived benefit obtained by consumers from purchasing behavior, and M2 represents the perceived benefit obtained by consumers from not purchasing self-driving cars.

[0035] Furthermore, in S3, an evolutionary game model among the government, car companies and consumers is constructed, and the evolutionary game model is solved according to the perceived benefit matrix to obtain the original pure strategy equilibrium point, which is specifically:

[0036] According to the perceived benefit matrix, the expected benefits and average expected benefits of the government, car companies and consumers under different game strategy combinations are calculated;

[0037] The replication dynamic equation is obtained according to the expected return and the average expected return;

[0038] The replication dynamic equation is solved to obtain the original pure strategy equilibrium point.

[0039] Furthermore, the expected benefits and average expected benefits of the government, car companies and consumers under different game strategy combinations are calculated based on the perceived benefit matrix, which are as follows:

[0040] The expected return of constructing a high-intensity government support behavior strategy based on the government's game strategy is U 11 , the expected benefit of the government's low-intensity support behavior strategy is U 12 , the average expected return is U1, then:

[0041] U 11 =(-QP-Kr+G1-H-sL)yz+(-QP-Kr+G1-sL)y(1-z)+(-Q-P+G1-H-sL+N)(1-y)z+(-Q-P+G1-sL+N)(1-y)(1-z) (1)

[0042] U 12 =0 (2)

[0043] U1=xU 11 +(1-x)U 12 (3)

[0044] The expected return of constructing the active behavior strategy of the car company based on the game strategy of the car company is U 21 、The expected benefit of the auto company's passive behavior strategy is U 22 , the average expected return is U2, then:

[0045] U 11 =(P+V1-W+sL-F)xz+(P+V1-W+sL)x(1-z)+(V1-WF)(1-x)z+(V1-W)(1-x)(1-z)(4)

[0046] U 22=(P-N+V2-D)xz+(P-N+VD)x(1-z)+(V2-D)(1-x)z+(V2-D)(1-x)(1-z) (5)

[0047] U2=yU 21 +(1-y)U 22 (6)

[0048] The expected return of building a consumer purchasing behavior strategy based on the consumer's game strategy is U 31 , the expected benefit of the consumer's non-purchase behavior strategy is U 32 , the average expected return is U3, then:

[0049] U 31 =(H-C+M1+F)xy+(H-C+M1)x(1-y)+(-C+M1+F)(1-x)y+(-C+M1)(1-x)(1-y) (7)

[0050] U 32 =M2xy+M2yx(1-x)+M2(1-y)x+(M2(1-y)(1-x) (8)

[0051] U3=zU 31 +(1-z)U 32 (9)

[0052] Among them, Q represents the additional cost when the government implements high-intensity support behavior compared with low-intensity support behavior, P represents the financial subsidies provided to car companies when the government implements high-intensity support behavior, H represents the car purchase subsidies provided to consumers when the government implements high-intensity support behavior, L represents the government's tax incentives for car companies with positive behavior, s represents the government's preference coefficient for car companies' technological innovation, N represents the economic penalty for environmental and other losses caused by companies without positive behavior under the government's high-intensity support behavior, K represents the loss caused by the negative impact of the positive behavior of car companies on autonomous driving car accidents under the government's high-intensity support behavior, r represents the negative impact coefficient, G1 represents the additional perceived benefits obtained by the government from implementing high-intensity support behavior compared with low-intensity support behavior, G2 represents the perceived benefits obtained by the government from implementing low-intensity support behavior, and x represents represents the probability of high government support, 1-x represents the probability of low government support, W represents the cost of car companies actively producing and selling self-driving cars, D represents the cost of car companies passively producing and selling self-driving cars, F represents the additional discount given to consumers by car companies actively selling self-driving cars, V1 represents the perceived benefit obtained by car companies from actively selling self-driving cars, V2 represents the perceived benefit obtained by car companies from maintaining the original car production, y represents the probability of positive behavior of car companies, 1-y represents the probability of negative behavior of car companies, C represents the additional cost of consumer purchasing behavior compared to traditional driving cars, M1 represents the perceived benefit obtained by consumer purchasing behavior, M2 represents the perceived benefit obtained by consumers not purchasing self-driving cars, z represents the probability of consumer purchasing behavior, 1-z represents the probability of consumer non-purchasing behavior.

[0053] Furthermore, the replication dynamic equation is constructed based on the expected return and the average expected return and solved to obtain the original pure strategy equilibrium point, specifically:

[0054] Based on the expected returns and average expected returns of the government, automakers and consumers, the replication dynamic equations of the government's high-intensity support behavior, automakers' positive behavior and consumers' purchasing behavior are constructed as follows:

[0055]

[0056] Among them, Q represents the additional cost when the government implements high-intensity support behavior compared with low-intensity support behavior, P represents the financial subsidies provided to car companies when the government implements high-intensity support behavior, H represents the car purchase subsidies provided to consumers when the government implements high-intensity support behavior, L represents the government's tax incentives for car companies with positive behavior, s represents the government's preference coefficient for car companies' technological innovation, N represents the economic penalty for environmental and other losses caused by companies without positive behavior under the government's high-intensity support behavior, K represents the loss caused by the negative impact of the positive behavior of car companies on autonomous driving car accidents under the government's high-intensity support behavior, r represents the negative impact coefficient, G1 represents the additional perceived benefits obtained by the government from implementing high-intensity support behavior compared with low-intensity support behavior, G2 represents the perceived benefits obtained by the government from implementing low-intensity support behavior, and x represents = represents the probability of high government support, 1-x represents the probability of low government support, W represents the cost of car companies actively producing and selling self-driving cars, D represents the cost of car companies passively producing and selling self-driving cars, F represents the additional discount given to consumers by car companies actively selling self-driving cars, V1 represents the perceived benefit obtained by car companies from actively selling self-driving cars, V2 represents the perceived benefit obtained by car companies from maintaining the original car production, y represents the probability of car companies' active behavior, 1-y represents the probability of car companies' passive behavior, C represents the additional cost of consumer purchase behavior compared to traditional driving cars, M1 represents the perceived benefit obtained by consumers' purchase behavior, M2 represents the perceived benefit obtained by consumers not purchasing self-driving cars, z represents the probability of consumer purchase behavior, 1-z represents the probability of consumer non-purchase behavior, U 11 represents the expected return of the government's high-strength support behavior strategy, U1 represents the average expected return of the government's high-strength support behavior strategy, and U 21 represents the expected return of the car company's active behavior strategy, U2 represents the average expected return of the car company's active behavior strategy, and U 31 represents the expected benefit of the consumer's purchasing behavior strategy, and U3 represents the average expected benefit of the consumer's purchasing behavior strategy;

[0057] According to the stability of the differential equations, if F(x)=0, F(y)=0, F(z)=0, the entire dynamic system will tend to be stable, and the replicated dynamic equation is as follows:

[0058]

[0059] The simultaneous equations (10)-(12) are used to solve the dynamic replication equations of the three-party evolutionary game, and the eight original pure strategy equilibrium points of the evolutionary game model are obtained: E1(0,0,0), E2(1,0,0), E3(0,1,0), E4(0,0,1), E5(1,1,0), E6(1,0,1), E7(0,1,1) and E8(1,1,1).

[0060] Another technical solution of the present invention to solve the above-mentioned technical problems is as follows: A self-driving car market game analysis system, comprising: a model initialization module, used to determine that the game subjects are the government, car companies and consumers, and construct a game subject behavior strategy set according to the behaviors of the government, car companies and consumers; construct a perception benefit matrix according to the game subject behavior strategy set; a model construction and calculation module, used to construct an evolutionary game model of the government, car companies and consumers, and solve the evolutionary game model according to the perception benefit matrix to obtain the original pure strategy equilibrium point; a model analysis module, used to perform stability analysis on the evolutionary game model according to the original pure strategy equilibrium point to obtain the target pure strategy equilibrium point of the evolutionary game model; a model strategy output module, used to analyze according to the target pure strategy equilibrium point to obtain the optimal strategy combination of the government, car companies and consumers.

[0061] Another technical solution of the present invention to solve the above-mentioned technical problem is as follows: a market game analysis system for autonomous driving vehicles, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor; when the processor executes the computer program, the market game analysis method for autonomous driving vehicles as described above is implemented.

[0062] Another technical solution of the present invention to solve the above-mentioned technical problem is as follows: a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the autonomous driving car market game analysis method as described above is implemented.

[0063] The beneficial effects of the present invention are: determining the game participants as the government, car companies and consumers, determining the game strategy set according to the government, car companies and consumers; constructing a perceived benefit matrix according to the game strategy set; constructing an evolutionary game model of the government, car companies and consumers, solving the evolutionary game model according to the perceived benefit matrix, and obtaining the original pure strategy equilibrium point; performing stability analysis on the evolutionary game model according to the original pure strategy equilibrium point, and obtaining the target pure strategy equilibrium point of the evolutionary game model; analyzing according to the target pure strategy equilibrium point to obtain the optimal strategy combination of the government, car companies and consumers. The present invention provides a scientific basis for the government to formulate policies, improves the accuracy of predicting consumer purchasing intentions, and promotes the healthy and sustainable development of the autonomous driving car market. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 A schematic diagram of a process flow of a method for analyzing the market game of autonomous driving vehicles provided by an embodiment of the present invention;

[0065] Figure 2 A module block diagram of the autonomous driving car market game analysis system provided by an embodiment of the present invention;

[0066] Figure 3 A structural diagram of a three-party evolutionary game model for an autonomous driving vehicle provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0067] The principles and features of the present invention are described below in conjunction with the accompanying drawings. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0068] like Figure 1 As shown, an embodiment of the present invention provides a method for analyzing the market game of autonomous driving vehicles, comprising the following steps:

[0069] S1. Determine the game subjects as the government, car companies and consumers, and construct the game subject behavior strategy set based on the behaviors of the government, car companies and consumers;

[0070] S2. constructing a perceived benefit matrix according to the game subject behavior strategy set;

[0071] S3. Construct an evolutionary game model among the government, car companies and consumers, solve the evolutionary game model according to the perceived benefit matrix, and obtain the original pure strategy equilibrium point;

[0072] S4. Performing stability analysis on the evolutionary game model according to the original pure strategy equilibrium point to obtain a target pure strategy equilibrium point of the evolutionary game model;

[0073] S5. Analyze the target pure strategy equilibrium point to obtain the optimal strategy combination of the government, car companies and consumers.

[0074] Beneficial effects: by determining the game participants as the government, car companies and consumers, the game strategy set is determined according to the government, car companies and consumers; the perceived benefit matrix is ​​constructed according to the game strategy set; an evolutionary game model of the government, car companies and consumers is constructed, and the evolutionary game model is solved according to the perceived benefit matrix to obtain the original pure strategy equilibrium point; the stability of the evolutionary game model is analyzed according to the original pure strategy equilibrium point to obtain the target pure strategy equilibrium point of the evolutionary game model; the optimal strategy combination of the government, car companies and consumers is obtained by analyzing the target pure strategy equilibrium point. The present invention provides a scientific basis for the government to formulate policies, improves the accuracy of predicting consumer purchasing intentions, and promotes the healthy and sustainable development of the autonomous driving car market.

[0075] Optionally, in S1, a game subject behavior strategy set is constructed according to the behaviors of the government, car companies and consumers, specifically:

[0076] Based on the government support behavior, a set of government support behavior strategies is constructed, expressed as α = {α1, α2}, where α1 is a high-intensity government support behavior and α2 is a low-intensity government support behavior. The high-intensity government support behavior means that the government supports the research and development of autonomous vehicles by providing incentive policies, and the low-intensity government support behavior means that no active measures are taken to interfere with the research and development of autonomous vehicles by car companies and the purchase of autonomous vehicles by consumers;

[0077] Based on the R&D behavior of automobile companies, a set of R&D behavior strategies for automobile companies is constructed, which is expressed as β = {β1, β2}, where β1 is the positive behavior of automobile companies and β2 is the negative behavior of automobile companies. The positive behavior of automobile companies means that automobile companies actively invest in R&D resources and vigorously introduce talents to carry out the R&D of autonomous driving technology. The negative behavior of automobile companies means that the R&D of autonomous driving vehicles takes negative measures or still adopts conventional methods to produce and sell vehicles.

[0078] A consumer purchase behavior strategy set is constructed based on the consumer purchase intention, which is expressed as γ = {γ1, γ2}, where γ1 is the consumer purchase behavior and γ2 is the consumer non-purchase behavior. The consumer purchase behavior indicates that the consumer chooses to buy an autonomous driving car instead of a traditional car when the consumer has the intention to buy a car. The consumer non-purchase behavior indicates that the consumer has not chosen to buy an autonomous driving car for the time being and maintains a wait-and-see attitude towards the purchase of an autonomous driving car, considering the potential safety risks, technical failures and possible losses of the autonomous driving car.

[0079] The government support behavior, the car enterprise R&D behavior and the consumer purchase behavior are arranged and combined to obtain a game subject behavior strategy set, wherein the game subject behavior strategy set includes: a first strategy combination: high-intensity government support behavior α1, car enterprise positive behavior β1, consumer purchase behavior γ1; a second strategy combination: high-intensity government support behavior α1, car enterprise positive behavior β1, consumer non-purchase behavior γ2; a third strategy combination: high-intensity government support behavior α1, car enterprise negative behavior β2, consumer purchase behavior γ1; a fourth strategy combination: high-intensity government support behavior α1, car enterprise negative behavior β2, consumer non-purchase behavior γ2; a fifth strategy combination: low-intensity government support behavior α2, car enterprise positive behavior β1, consumer purchase behavior γ1; a sixth strategy combination: low-intensity government support behavior α2, car enterprise positive behavior β1, consumer non-purchase behavior γ2; a seventh strategy combination: low-intensity government support behavior α2, car enterprise negative behavior β2, consumer purchase behavior γ1; an eighth strategy combination: low-intensity government support behavior α2, car enterprise negative behavior β2, consumer non-purchase behavior γ2.

[0080] It should be understood that before constructing the set of behavioral strategies of the game subject, the following basic assumptions should be made for the evolutionary game model: Assumption 1 Game subject. The three parties in the game are consumers, car companies, and relevant government departments. In the game process, each subject is limited rational. There is information asymmetry between them. They will make judgments based on limited knowledge and information, and adjust their strategies based on the behavioral feedback provided by other game parties. Finally, they evolve into a specific stable strategy to maximize their own interests. Decision-making choices are based on their own value perception rather than actual utility results. Behavioral choices conform to the value perception function U constructed based on prospect theory. Assumption 2 Game subject behavior strategy. The strategy set of government support behavior α = {α1 high support, α2 low support}. "High support" means that the government supports the research and development of autonomous vehicles by providing incentive policies, such as tax incentives, research and development subsidies, and other measures. And by formulating regulations, clarifying technical standards and safety requirements, etc., to regulate the landing and driving of autonomous vehicles. "Low support" means that no active measures are taken to interfere with the research and development of autonomous vehicles by car companies and the purchase of autonomous vehicles by consumers. The behavior strategy set of car companies is β = {β1 positive, β2 negative}. "Positive" means that car companies actively invest in R&D resources and vigorously introduce talents to develop autonomous driving technology. "Negative" means taking negative measures on the development of autonomous driving cars or still using conventional methods to produce and sell vehicles. The behavior strategy set of consumers is γ = {γ1 purchase, γ2 wait and see}. "Purchase" means that consumers choose to buy autonomous driving cars instead of traditional cars when they have the intention to buy cars. "Wait and see" means that considering the potential safety risks, technical failures and possible losses of autonomous driving cars, they have not chosen to buy autonomous driving cars for the time being and maintain a wait-and-see attitude towards buying autonomous driving cars. Hypothesis 3 The probability of behavioral strategy selection. When the government, car companies and consumers are playing games, the proportion of the government choosing the strategy of "high support" is x, and the proportion of choosing the strategy of "low support" is 1-x, x∈[0,1]; the proportion of car companies choosing the strategy of "active" is y, and the proportion of choosing the strategy of "passive" is 1-y, y∈[0,1]; the proportion of consumers choosing the strategy of "purchase" is z, and the proportion of consumers choosing the strategy of "wait and see" is 1-z, z∈[0,1]. Assumption 4 The promotion of autonomous vehicles requires perfect infrastructure support, including but not limited to the construction of 5G networks, intelligent transportation systems, charging piles and other facilities. These infrastructure constructions are the prerequisites for ensuring the safe and efficient operation of autonomous vehicles. Therefore, when the government implements high-intensity policy support, it mainly manifests itself in increasing investment in new infrastructure. The additional cost (including new infrastructure) when the government implements high-intensity policy support is Q compared with low-intensity. In addition to the investment in new infrastructure, the government also needs to provide appropriate financial subsidies to car companies to promote the development of autonomous vehicles.Fiscal subsidies P are an important part of the government's high-intensity policy support, and play a key role in reducing the R&D costs of enterprises, stimulating technological innovation and accelerating market promotion. Under the government's high-intensity policy support, the car purchase subsidy H provided to consumers is an important measure to promote the popularization of the autonomous driving car market. Car purchase subsidies directly reduce consumers' car purchase costs and increase consumers' willingness and ability to purchase autonomous driving cars. In the process of promoting the development of the autonomous driving car industry, the government provides tax incentives L to car companies that actively develop, which can encourage companies to invest more resources in technological innovation and R&D. In the government's support policy for the autonomous driving car industry, the technology innovation preference coefficient s (0<s≤1) is an important indicator to measure the R&D enthusiasm and innovation ability of enterprises. Under the government's high-intensity support policy, enterprises with high technology innovation preference coefficients are given priority support, including priority approval of projects and priority tax incentives. At the same time, in order to ensure the efficient use of policy resources and encourage enterprises to actively develop, the government imposes economic penalties N on environmental and other losses caused by enterprises that do not actively develop. Although policy support helps the rapid development of technology, the immaturity of technology may cause accidents. These accidents will not only bring direct economic losses K, but may also damage the public's trust in autonomous driving technology and delay market promotion. The negative impact and loss impact coefficient r caused by accidents in the process of car companies actively developing autonomous vehicles are key indicators to measure the extent of these negative impacts. Under the implementation of low-intensity policy support, the government can still obtain certain benefits G1 in terms of economy, society and environmental ecology. When the government implements high-intensity policy support for autonomous vehicles, it will obtain additional perceived effects G2 compared with low-intensity policies. When the government implements high-intensity policy support for autonomous vehicles, it can obtain additional perceived benefits compared with low-intensity support. These additional benefits are not only reflected in the public and enterprises' confidence in technological development, but also include the overall society's high recognition and support for the government's science and technology policies. Assumption 5 The cost of car companies actively producing and selling autonomous vehicles is W. At the same time as actively selling, they will also give consumers additional discounts F to stimulate market demand and improve sales performance. The cost of passively producing and selling autonomous vehicles is D (WD>F). The perceived benefits V1 obtained by car companies that actively sell autonomous vehicles are not only short-term market returns, but also long-term brand value and market competitiveness. The perceived benefit that car companies gain from maintaining the original car production for the sake of stable market performance, lower operating risks, and continued brand recognition and customer satisfaction is V2 (V1>V2). Assumption 6: The core technologies of self-driving cars require a lot of R&D investment, which makes the cost of the whole vehicle significantly higher than that of traditional vehicles. In addition, the maintenance and update of the self-driving system also add additional costs. The additional cost that consumers pay for buying self-driving cars over traditional driving cars is C.When consumers buy self-driving cars, they can obtain corresponding perceived benefits M1, which include not only improved driving safety and driving convenience, but also improved driving experience and social satisfaction. Consumers who do not buy self-driving cars can also obtain perceived benefits M2, which include economic savings, psychological comfort, and expectations of stability and reliability.

[0081] Optionally, in S2, a perception benefit matrix is ​​constructed according to the game subject behavior strategy set, specifically:

[0082] Construct a first matrix according to the first strategy combination, wherein the first matrix includes a government benefit expression -QPK*r+G1-Hs*L, a car company benefit expression P+V1-W+s*LF, and a consumer benefit expression H-C+M1+F;

[0083] Construct a second matrix according to the second strategy combination, wherein the second matrix includes a government benefit expression -QPK*r+G1-s*L, a car company benefit expression P+V1-W+s*L, and a consumer benefit expression M2;

[0084] Construct a third matrix according to the third strategy combination, wherein the third matrix includes a government benefit expression -Q-P+G1-Hs*L+N, a car company benefit expression P-N+V2-D, and a consumer benefit expression H-C+M1;

[0085] Construct a fourth matrix according to the fourth strategy combination, wherein the fourth matrix includes a government benefit expression -Q-P+G1-s*L+N, a car company benefit expression P-N+V2-D, and a consumer benefit expression M2;

[0086] Constructing a fifth matrix according to the fifth strategy combination, the fifth matrix including the government benefit expression 0, the car company benefit expression V1-WF and the consumer benefit expression -C+M1+F;

[0087] Constructing a sixth matrix according to the sixth strategy combination, the sixth matrix including a government benefit expression 0, a car company benefit expression V1-W and a consumer benefit expression M2;

[0088] Construct a seventh matrix according to the seventh strategy combination, wherein the seventh matrix includes a government benefit expression 0, a car company benefit expression V2-D, and a consumer benefit expression -C+M1;

[0089] Constructing an eighth matrix according to the eighth strategy combination, wherein the eighth matrix includes a government benefit expression 0, a car company benefit expression V2-D, and a consumer benefit expression M2;

[0090] Combining the first matrix, the second matrix, the third matrix, the fourth matrix, the fifth matrix, the sixth matrix, the seventh matrix, and the eighth matrix into a perceived benefit matrix;

[0091] Among them, Q represents the additional cost when the government implements high-intensity support behavior compared with low-intensity support behavior, P represents the financial subsidies provided to car companies when the government implements high-intensity support behavior, H represents the car purchase subsidies provided to consumers when the government implements high-intensity support behavior, L represents the government's tax incentives for car companies with positive behavior, s represents the government's preference coefficient for car companies' technological innovation, N represents the economic penalty for environmental and other losses caused by companies without positive behavior under the government's high-intensity support behavior, K represents the losses caused by the negative impact of car companies' positive behavior on autonomous driving car accidents under the government's high-intensity support behavior, r represents the negative impact coefficient, and G1 represents the government's high-intensity support behavior due to the implementation of high-intensity support behavior. is the additional perceived benefit obtained from low-intensity support behavior, G2 represents the perceived benefit obtained by the government from implementing low-intensity support behavior, W represents the cost for automakers to actively produce and sell self-driving cars, D represents the cost for automakers to passively produce and sell self-driving cars, F represents the additional discount given to consumers by automakers for actively selling self-driving cars, V1 represents the perceived benefit obtained by automakers from actively selling self-driving cars, V2 represents the perceived benefit obtained by automakers from maintaining the original car production, C represents the additional cost of consumer purchasing behavior compared to traditional driving cars, M1 represents the perceived benefit obtained by consumers from purchasing behavior, and M2 represents the perceived benefit obtained by consumers from not purchasing self-driving cars.

[0092] It should be understood that Table 1 shows the symbols and meanings of the perceived benefit matrix parameters. As shown in Table 1, the parameters of the perceived benefit matrix should be defined before constructing it.

[0093] Table 1

[0094]

[0095] It should be understood that Table 2 is a perceived benefit matrix, as shown in Table 2:

[0096] Table 2

[0097]

[0098] Optionally, in S3, an evolutionary game model among the government, car companies and consumers is constructed, and the evolutionary game model is solved according to the perceived benefit matrix to obtain the original pure strategy equilibrium point, which is specifically:

[0099] According to the perceived benefit matrix, the expected benefits and average expected benefits of the government, car companies and consumers under different game strategy combinations are calculated;

[0100] The replication dynamic equation is obtained according to the expected return and the average expected return;

[0101] The replication dynamic equation is solved to obtain the original pure strategy equilibrium point.

[0102] Optionally, the expected benefits and average expected benefits of the government, car companies and consumers under different game strategy combinations are calculated based on the perceived benefit matrix, specifically:

[0103] The expected return of constructing a high-intensity government support behavior strategy based on the government's game strategy is U 11 , the expected benefit of the government's low-intensity support behavior strategy is U 12 , the average expected return is U1, then:

[0104] U 11 =(-QP-Kr+G1-H-sL)yz+(-QP-Kr+G1-sL)y(1-z)+(-Q-P+G1-H-sL+N)(1-y)z+(-Q-P+G1-sL+N)(1-y)(1-z) (1)

[0105] U 12 =0 (2)

[0106] U1=xU 11 +(1-x)U 12 (3)

[0107] The expected return of constructing the active behavior strategy of the car company based on the game strategy of the car company is U 21 、The expected benefit of the auto company's passive behavior strategy is U 22 , the average expected return is U2, then:

[0108] U 11 =(P+V1-W+sL-F)xz+(P+V1-W+sL)x(1-z)+(V1-WF)(1-x)z+(V1-W)(1-x)(1-z)(4)

[0109] U 22 =(P-N+V2-D)xz+(P-N+VD)x(1-z)+(V2-D)(1-x)z+(V2-D)(1-x)(1-z) (5)

[0110] U2=yU 21 +(1-y)U 22 (6)

[0111] The expected return of building a consumer purchasing behavior strategy based on the consumer's game strategy is U 31 , the expected benefit of the consumer's non-purchase behavior strategy is U32 , the average expected return is U3, then:

[0112] U 31 =(H-C+M1+F)xy+(H-C+M1)x(1-y)+(-C+M1+F)(1-x)y+(-C+M1)(1-x)(1-y) (7)

[0113] U 32 =M2xy+M2yx(1-x)+M2(1-y)x+(M2(1-y)(1-x) (8)

[0114] U3=zU 31 +(1-z)U 32 (9)

[0115] Among them, Q represents the additional cost when the government implements high-intensity support behavior compared with low-intensity support behavior, P represents the financial subsidies provided to car companies when the government implements high-intensity support behavior, H represents the car purchase subsidies provided to consumers when the government implements high-intensity support behavior, L represents the government's tax incentives for car companies with positive behavior, s represents the government's preference coefficient for car companies' technological innovation, N represents the economic penalty for environmental and other losses caused by companies without positive behavior under the government's high-intensity support behavior, K represents the loss caused by the negative impact of the positive behavior of car companies on autonomous driving car accidents under the government's high-intensity support behavior, r represents the negative impact coefficient, G1 represents the additional perceived benefits obtained by the government from implementing high-intensity support behavior compared with low-intensity support behavior, G2 represents the perceived benefits obtained by the government from implementing low-intensity support behavior, and x represents represents the probability of high government support, 1-x represents the probability of low government support, W represents the cost of car companies actively producing and selling self-driving cars, D represents the cost of car companies passively producing and selling self-driving cars, F represents the additional discount given to consumers by car companies actively selling self-driving cars, V1 represents the perceived benefit obtained by car companies from actively selling self-driving cars, V2 represents the perceived benefit obtained by car companies from maintaining the original car production, y represents the probability of positive behavior of car companies, 1-y represents the probability of negative behavior of car companies, C represents the additional cost of consumer purchasing behavior compared to traditional driving cars, M1 represents the perceived benefit obtained by consumer purchasing behavior, M2 represents the perceived benefit obtained by consumers not purchasing self-driving cars, z represents the probability of consumer purchasing behavior, 1-z represents the probability of consumer non-purchasing behavior.

[0116] It should be understood that a three-party evolutionary game model including car companies, government and consumers is constructed, and the profit function and strategy set of each party are defined, specifically:

[0117] The government’s game strategy: The expected return of choosing the “high support” strategy is U11 , the expected return of choosing the "low support" strategy is U 12 , the average expected return is U1, then:

[0118] U 11 =(-QP-Kr+G1-H-sL)yz+(-QP-Kr+G1-sL)y(1-z)+(-Q-P+G1-H-sL+N)(1-y)z+(-Q-P+G1-sL+N)(1-y)(1-z)

[0119] U 12 =0

[0120] U1=xU 11 +(1-x)U 12

[0121] Game strategy of car companies: The expected return of choosing the "active" strategy is U 21 , the expected return of choosing the "passive" strategy is U 22 , the average expected return is U2, then:

[0122] U 11 =(P+V1-W+sL-F)xz+(P+V1-W+sL)x(1-z)+(V1-WF)(1-x)z+(V1-W)(1-x)(1-z)

[0123] U 22 =(P-N+V2-D)xz+(P-N+VD)x(1-z)+(V2-D)(1-x)z+(V2-D)(1-x)(1-z)

[0124] U2=yU 21 +(1-y)U 22

[0125] Consumer’s game strategy: The expected benefit of choosing the “buy” strategy is U 31 , the expected return of choosing the "wait and see" strategy is U 32 , the average expected return is U3, then:

[0126] U 31 =(H-C+M1+F)xy+(H-C+M1)x(1-y)+(-C+M1+F)(1-x)y+(-C+M1)(1-x)(1-y)

[0127] U 32 =M2xy+M2yx(1-x)+M2(1-y)x+(M2(1-y)(1-x)

[0128] U3=zU 31 +(1-z)U32

[0129] It should be understood that the replication dynamic equation of each game participant group is constructed according to the expected benefits of each game participant group, including:

[0130] The replication dynamic equation for the government's choice of a high-intensity support strategy is:

[0131]

[0132] The replication dynamic equation for car companies choosing an active R&D strategy is:

[0133]

[0134] The replication dynamic equation for consumers to choose purchasing strategies is:

[0135]

[0136] According to the stability of the differential equations, if F(x) = 0, F(y) = 0, F(z) = 0, the entire dynamic system will tend to be stable. The simultaneous equations (10)-(12) are used to solve the dynamic replication equation of the three-party evolutionary game as follows:

[0137]

[0138] After solving the equations jointly, we can find that there are 8 pure strategy equilibrium points in the evolutionary game system: E1(0,0,0), E2(1,0,0), E3(0,1,0), E4(0,0,1), E5(1,1,0), E6(1,0,1), E7(0,1,1) and E8(1,1,1).

[0139] All stakeholders adopt pure strategies at each equilibrium point. When the conditions F(x)=0, F(y)=0, F(z)=0 are met, there is also an equilibrium point of mixed strategies in the equilibrium solution domain, namely E9(x*,y*,z*).

[0140]

[0141] Optionally, the replication dynamic equation is constructed according to the expected return and the average expected return and solved to obtain the original pure strategy equilibrium point, specifically:

[0142] Based on the expected returns and average expected returns of the government, automakers and consumers, the replication dynamic equations of the government's high-intensity support behavior, automakers' positive behavior and consumers' purchasing behavior are constructed as follows:

[0143]

[0144] Among them, Q represents the additional cost when the government implements high-intensity support behavior compared with low-intensity support behavior, P represents the financial subsidies provided to car companies when the government implements high-intensity support behavior, H represents the car purchase subsidies provided to consumers when the government implements high-intensity support behavior, L represents the government's tax incentives for car companies with positive behavior, s represents the government's preference coefficient for car companies' technological innovation, N represents the economic penalty for environmental and other losses caused by companies without positive behavior under the government's high-intensity support behavior, K represents the loss caused by the negative impact of the positive behavior of car companies on autonomous driving car accidents under the government's high-intensity support behavior, r represents the negative impact coefficient, G1 represents the additional perceived benefits obtained by the government from implementing high-intensity support behavior compared with low-intensity support behavior, G2 represents the perceived benefits obtained by the government from implementing low-intensity support behavior, and x represents = represents the probability of high government support, 1-x represents the probability of low government support, W represents the cost of car companies actively producing and selling self-driving cars, D represents the cost of car companies passively producing and selling self-driving cars, F represents the additional discount given to consumers by car companies actively selling self-driving cars, V1 represents the perceived benefit obtained by car companies from actively selling self-driving cars, V2 represents the perceived benefit obtained by car companies from maintaining the original car production, y represents the probability of car companies' active behavior, 1-y represents the probability of car companies' passive behavior, C represents the additional cost of consumer purchase behavior compared to traditional driving cars, M1 represents the perceived benefit obtained by consumers' purchase behavior, M2 represents the perceived benefit obtained by consumers not purchasing self-driving cars, z represents the probability of consumer purchase behavior, 1-z represents the probability of consumer non-purchase behavior, U 11 represents the expected return of the government's high-strength support behavior strategy, U1 represents the average expected return of the government's high-strength support behavior strategy, and U 21 represents the expected return of the car company's active behavior strategy, U2 represents the average expected return of the car company's active behavior strategy, and U 31 represents the expected benefit of the consumer's purchasing behavior strategy, and U3 represents the average expected benefit of the consumer's purchasing behavior strategy;

[0145] According to the stability of the differential equations, if F(x)=0, F(y)=0, F(z)=0, the entire dynamic system will tend to be stable, and the replicated dynamic equation is as follows:

[0146]

[0147] The simultaneous equations (10)-(12) are used to solve the dynamic replication equations of the three-party evolutionary game, and the eight original pure strategy equilibrium points of the evolutionary game model are obtained: E1(0,0,0), E2(1,0,0), E3(0,1,0), E4(0,0,1), E5(1,1,0), E6(1,0,1), E7(0,1,1) and E8(1,1,1).

[0148] It should be understood that whether the equilibrium point obtained by replicating the dynamic equation is an ESS (evolutionary stable strategy) needs further verification. Since the mixed strategy equilibrium in the asymmetric dynamic game is definitely not an evolutionary stable equilibrium, and E9 is a mixed strategy, it cannot be an evolutionary stable system. Therefore, only the pure strategy equilibrium points (E1~E8) of the evolutionary game system are analyzed.

[0149] According to the assumptions and settings of the parameters in this paper, through simple judgment and elimination, among the above eight strategies, the first five strategies do not meet the requirements for stability. In the E6 (1, 0, 1) and E8 (1, 1, 1) strategies, when the evolutionary stability strategy is met, the value of λ2 is the opposite value. In the E7 (1, 0, 1) and E8 (1, 1, 1) strategies, when the evolutionary stability strategy is met, the value of λ1 is the opposite value. However, according to the actual situation and assumptions 4 and 5, the active and passive values ​​of the two are difficult to determine. Therefore, the analysis of this paper considers four cases.

[0150] (1) Case 1: V1<F-D+V2+W-sL

[0151] In this case, the perceived benefits of actively selling self-driving cars by automakers are not enough to offset their costs and the benefits provided, even with government tax incentives. This suggests that existing market conditions, cost structures, or government support are not sufficient to drive automakers to actively promote self-driving cars. To change this situation, government support can be strengthened, market acceptance can be improved, technology costs can be reduced, and cooperation between automakers can be promoted, thereby improving the market prospects of self-driving cars and automakers' profit expectations.

[0152] (2) Case 2: V1>F-D+V2+W(-sL)

[0153] This shows that with government support, the strategy of automakers to actively sell self-driving cars is economically feasible and beneficial. Despite the high production and sales costs, automakers' high profit expectations for the self-driving car market and the incentives of tax incentives make them more inclined to actively sell this new type of vehicle. Tax incentives increase the net profit of automakers' active sales of self-driving cars by reducing their actual costs, further promoting the implementation of this strategy. With government support, automakers are more motivated to actively promote and sell self-driving cars. First, when this condition is met, automakers are more inclined to choose an active research and development strategy.

[0154] (3) Case 3: G1<H+Q+sL+Kr+P

[0155] In this case, the additional perceived benefits of the government's high-intensity policy support for autonomous vehicles are not enough to offset all the costs and subsidies it bears. In order to make high-intensity policies economically feasible, the government needs to optimize the subsidy structure, strengthen risk management, increase policy benefits, and consider implementing policies gradually. Through these measures, costs can be effectively reduced, benefits can be increased, and the development of the autonomous vehicle market can be promoted.

[0156] (4) Case 4: G1>H+Q+sL+Kr+P

[0157] In this case, the additional perceived benefits of the government's implementation of high-intensity policy support for autonomous vehicles exceed all related costs and expenditures, indicating that high-intensity policies are economically feasible and have positive effects. The government can continue to strengthen policy support, optimize subsidy structure, expand the scope of support, and strengthen risk management and public education, thereby further promoting the development of the autonomous vehicle market and improving overall economic and social benefits.

[0158] From the above four situations, it can be seen that when V1>F-D+V2+W-sL and G1>H+Q+sL+Kr+P is established, it is the only choice for the government to maximize its benefits, minimize risks, achieve mutual benefit and win-win results, and achieve sustainable economic and social development in the autonomous driving car market. At this time, the system reaches an evolutionary stable state. Among the above eight pure strategy equilibrium points, only point E8(1,1,1) meets the conditions, so the system can only evolve towards the equilibrium point E8(1,1,1), and the corresponding evolutionary strategy at this equilibrium point is {high support, active research and development, purchase}.

[0159] It should be understood that the simulation step includes:

[0160] (1) MATLAB numerical analysis: MATLAB is used to perform numerical simulations to verify the evolutionary stability of automobile companies and government strategies under different policy support intensities.

[0161] (2) Simulation steps:

[0162] Initialize model parameters, including the strategy set and profit function of car companies, governments, and consumers.

[0163] Set up policy combinations (tax incentives, car purchase subsidies, infrastructure construction costs, fiscal subsidies, etc.) and market conditions.

[0164] Run the evolutionary game model to calculate the benefits of car companies and the government and analyze the stability of their strategic choices.

[0165] Based on the simulation results, the optimal policy combination is determined to ensure that automakers actively promote self-driving cars, the government obtains maximum benefits, and consumers' willingness to purchase is improved.

[0166] Based on the model assumptions and stability conditions, the parameters are assigned values, and the equilibrium point of the three-party evolutionary game of the ESSS evolutionary strategy is numerically simulated. The parameter settings are mainly the gains and losses of government measures, followed by the gains and losses of different entities with different parameter settings and their significance, as shown in the table below. Combined with relevant data, the parameter values ​​given in the table below are finally sorted out. The parameter values ​​only represent an approximate proportion, mainly to verify the model and related parameters of the willingness to purchase autonomous vehicles.

[0167] Table 3 is a simulation parameter assignment table, as shown in Table 3:

[0168] Table 3

[0169] parameter Q P H L s N K r <![CDATA[G1]]> G2 W D F <![CDATA[V1]]> V2 C <![CDATA[M1]]> <![CDATA[M2]]> Assignment 10 3.5 1 4 0.5 3 30 0.5 40 15 25 18 1 30 50 5 50 10

[0170] It should be understood that optimization strategies include:

[0171] (1) Dynamically adjust tax incentive strategies.

[0172] Strategy description: The government should dynamically adjust tax incentive policies based on the R&D investment and market promotion of automobile companies.

[0173] Specific measures: ① Provide higher tax incentives to automakers that actively develop and promote self-driving cars. ② Regularly evaluate the market performance of automakers and flexibly adjust the tax incentive ratio to ensure the maximum incentive effect of the policy.

[0174] Expected effect: Increase the enthusiasm of car companies and encourage more car companies to invest in the research and development and market promotion of autonomous vehicles.

[0175] (2) Implement car purchase subsidies in stages.

[0176] Strategy description: The government should implement car purchase subsidies in stages and gradually adjust the subsidy intensity according to market demand and technological maturity.

[0177] Specific measures: ① Provide higher car purchase subsidies in the early stage of the market to attract early users. ② As the technology matures and the market expands, gradually reduce car purchase subsidies to encourage spontaneous growth of the market.

[0178] Expected effect: Promote the rapid development of the early market while avoiding market distortion caused by long-term reliance on subsidies.

[0179] (3) Optimize infrastructure construction.

[0180] Strategy description: The government should rationally plan and optimize infrastructure construction investment Q to provide a good environment support for the popularization of self-driving cars.

[0181] Specific measures: ① Strengthen the construction of transportation networks and intelligent infrastructure to improve the operating efficiency and safety of self-driving cars. ② According to market demand and technological development, gradually improve the layout of infrastructure to avoid over-investment and waste of resources.

[0182] Expected results: Improve the operating efficiency and safety of self-driving cars, and increase user acceptance and willingness to purchase.

[0183] (4) Targeted financial subsidies.

[0184] Strategy description: The government should provide targeted financial subsidies P based on the market performance and technological innovation of automobile companies.

[0185] Specific measures: ① Provide additional financial subsidies to automakers with leading technology and outstanding market performance to encourage technological innovation and market promotion. ② Provide special subsidies to small and medium-sized automakers and emerging enterprises to support their entry into the market and promote market diversification and competition.

[0186] Expected results: Encourage technological innovation, support emerging enterprises, and promote market competition and healthy development.

[0187] (5) Risk management and negative impact control.

[0188] Strategy description: The government should formulate and implement effective risk management and negative impact control strategies to reduce the negative impact Kr of car companies' research and development of autonomous vehicles under high-intensity policy support.

[0189] Specific measures: ① Establish a sound accident emergency response mechanism to improve the efficiency of handling accidents involving autonomous vehicles and reduce negative impacts. ② Formulate strict technical standards and safety specifications to improve the safety and reliability of autonomous vehicles.

[0190] Expected effects: Reduce the risk of accidents involving autonomous vehicles, increase the confidence of automakers and consumers, and promote stable market development.

[0191] (6) Comprehensive policy evaluation and feedback mechanism.

[0192] Strategy description: Establish a comprehensive policy evaluation and feedback mechanism to ensure the scientific and effective implementation of policies.

[0193] Specific measures: ① Regularly evaluate the policy effects and analyze the actual impact of various policy measures on the market. ② According to the evaluation results, timely adjust and optimize the policy combination to ensure the maximum policy effect. ③ Establish a multi-party feedback mechanism to listen to the opinions and suggestions of automakers, consumers and other stakeholders, and continuously improve the policy system.

[0194] Expected effect: Improve the scientific nature and effectiveness of policy implementation and ensure the healthy and sustainable development of the autonomous driving vehicle market.

[0195] Figure 2 An autonomous driving car market game analysis system provided for an embodiment of the present invention includes a model initialization module, which is used to determine that the game subjects are the government, car companies and consumers, and construct a game subject behavior strategy set according to the behaviors of the government, car companies and consumers; construct a perception benefit matrix according to the game subject behavior strategy set; a model construction and calculation module, which is used to construct an evolutionary game model of the government, car companies and consumers, and solve the evolutionary game model according to the perception benefit matrix to obtain an original pure strategy equilibrium point; a model analysis module, which is used to perform stability analysis on the evolutionary game model according to the original pure strategy equilibrium point to obtain a target pure strategy equilibrium point of the evolutionary game model; and a model strategy output module, which is used to analyze according to the target pure strategy equilibrium point to obtain the optimal strategy combination of the government, car companies and consumers.

[0196] Figure 3 The structure diagram of the three-party evolutionary game model of the autonomous driving car of the present invention includes: model design and simulation analysis, wherein the model design includes: problem description and model assumptions and model construction and analysis, the problem description and model assumptions include: problem description, model assumptions and perception benefit matrix, model construction and analysis include: model construction, path evolution analysis and stability analysis; simulation analysis includes: the influence of the initial value of the decision, the influence of the reference point, the influence of the intensity of rewards and punishments,

[0197] It should be understood that the three-party evolutionary game model of autonomous vehicles is based on prospect theory and evolutionary game theory, where prospect theory includes: potential losses (safety risks) and potential gains (technological innovation), and evolutionary game theory includes: government, car companies and consumers.

[0198] An embodiment of the present invention provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the autonomous driving vehicle market game analysis method as described above is implemented.

[0199] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0200] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0201] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0202] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0203] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0204] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. For such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0205] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for analyzing the market game of autonomous vehicles, characterized in that: The steps include: S1. Determine the game subjects as the government, car companies and consumers, and construct the game subject behavior strategy set based on the behaviors of the government, car companies and consumers; S2. constructing a perceived benefit matrix according to the game subject behavior strategy set; S3. Construct an evolutionary game model among the government, car companies and consumers, solve the evolutionary game model according to the perceived benefit matrix, and obtain the original pure strategy equilibrium point; S4. Performing stability analysis on the evolutionary game model according to the original pure strategy equilibrium point to obtain a target pure strategy equilibrium point of the evolutionary game model; S5. Analyze the target pure strategy equilibrium point to obtain the optimal strategy combination of the government, car companies and consumers.

2. The method for analyzing the market game of autonomous driving vehicles according to claim 1, characterized in that: In S1, a set of game subject behavior strategies is constructed based on the behaviors of the government, car companies and consumers, specifically: Based on the government support behavior, a set of government support behavior strategies is constructed, expressed as α = {α1, α2}, where α1 is a high-intensity government support behavior and α2 is a low-intensity government support behavior. The high-intensity government support behavior means that the government supports the research and development of autonomous vehicles by providing incentive policies, and the low-intensity government support behavior means that no active measures are taken to interfere with the research and development of autonomous vehicles by car companies and the purchase of autonomous vehicles by consumers; Based on the R&D behavior of automobile companies, a set of R&D behavior strategies for automobile companies is constructed, which is expressed as β = {β1, β2}, where β1 is the positive behavior of automobile companies and β2 is the negative behavior of automobile companies. The positive behavior of automobile companies means that automobile companies actively invest in R&D resources and vigorously introduce talents to carry out the R&D of autonomous driving technology. The negative behavior of automobile companies means that the R&D of autonomous driving vehicles takes negative measures or still adopts conventional methods to produce and sell vehicles. A consumer purchase behavior strategy set is constructed based on the consumer purchase intention, which is expressed as γ = {γ1, γ2}, where γ1 is the consumer purchase behavior and γ2 is the consumer non-purchase behavior. The consumer purchase behavior indicates that the consumer chooses to buy an autonomous driving car instead of a traditional car when the consumer has the intention to buy a car. The consumer non-purchase behavior indicates that the consumer has not chosen to buy an autonomous driving car for the time being and maintains a wait-and-see attitude towards the purchase of an autonomous driving car, considering the potential safety risks, technical failures and possible losses of the autonomous driving car. The government support behavior, the car enterprise R&D behavior and the consumer purchase behavior are arranged and combined to obtain a game subject behavior strategy set, wherein the game subject behavior strategy set includes: a first strategy combination: high-intensity government support behavior α1, car enterprise positive behavior β1, consumer purchase behavior γ1; a second strategy combination: high-intensity government support behavior α1, car enterprise positive behavior β1, consumer non-purchase behavior γ2; a third strategy combination: high-intensity government support behavior α1, car enterprise negative behavior β2, consumer purchase behavior γ1; a fourth strategy combination: high-intensity government support behavior α1, car enterprise negative behavior β2, consumer non-purchase behavior γ2; a fifth strategy combination: low-intensity government support behavior α2, car enterprise positive behavior β1, consumer purchase behavior γ1; a sixth strategy combination: low-intensity government support behavior α2, car enterprise positive behavior β1, consumer non-purchase behavior γ2; a seventh strategy combination: low-intensity government support behavior α2, car enterprise negative behavior β2, consumer purchase behavior γ1; an eighth strategy combination: low-intensity government support behavior α2, car enterprise negative behavior β2, consumer non-purchase behavior γ2.

3. The method for analyzing the market game of autonomous driving vehicles according to claim 2, characterized in that: In S2, a perception benefit matrix is ​​constructed according to the game subject behavior strategy set, specifically: Construct a first matrix according to the first strategy combination, wherein the first matrix includes a government benefit expression -QPK*r+G1-Hs*L, a car company benefit expression P+V1-W+s*LF, and a consumer benefit expression H-C+M1+F; Construct a second matrix according to the second strategy combination, wherein the second matrix includes a government benefit expression -QPK*r+G1-s*L, a car company benefit expression P+V1-W+s*L, and a consumer benefit expression M2; Construct a third matrix according to the third strategy combination, wherein the third matrix includes a government benefit expression -Q-P+G1-Hs*L+N, a car company benefit expression P-N+V2-D, and a consumer benefit expression H-C+M1; Construct a fourth matrix according to the fourth strategy combination, wherein the fourth matrix includes a government benefit expression -Q-P+G1-s*L+N, a car company benefit expression P-N+V2-D, and a consumer benefit expression M2; Constructing a fifth matrix according to the fifth strategy combination, the fifth matrix including the government benefit expression 0, the car company benefit expression V1-WF and the consumer benefit expression -C+M1+F; Constructing a sixth matrix according to the sixth strategy combination, the sixth matrix including a government benefit expression 0, a car company benefit expression V1-W and a consumer benefit expression M2; Construct a seventh matrix according to the seventh strategy combination, wherein the seventh matrix includes a government benefit expression 0, a car company benefit expression V2-D, and a consumer benefit expression -C+M1; Constructing an eighth matrix according to the eighth strategy combination, wherein the eighth matrix includes a government benefit expression 0, a car company benefit expression V2-D, and a consumer benefit expression M2; Combining the first matrix, the second matrix, the third matrix, the fourth matrix, the fifth matrix, the sixth matrix, the seventh matrix, and the eighth matrix into a perceived benefit matrix; Among them, Q represents the additional cost when the government implements high-intensity support behavior compared with low-intensity support behavior, P represents the financial subsidies provided to car companies when the government implements high-intensity support behavior, H represents the car purchase subsidies provided to consumers when the government implements high-intensity support behavior, L represents the government's tax incentives for car companies with positive behavior, s represents the government's preference coefficient for car companies' technological innovation, N represents the economic penalty for environmental and other losses caused by companies without positive behavior under the government's high-intensity support behavior, K represents the losses caused by the negative impact of car companies' positive behavior on autonomous driving car accidents under the government's high-intensity support behavior, r represents the negative impact coefficient, and G1 represents the government's high-intensity support behavior due to the implementation of high-intensity support behavior. is the additional perceived benefit obtained from low-intensity support behavior, G2 represents the perceived benefit obtained by the government from implementing low-intensity support behavior, W represents the cost for automakers to actively produce and sell self-driving cars, D represents the cost for automakers to passively produce and sell self-driving cars, F represents the additional discount given to consumers by automakers for actively selling self-driving cars, V1 represents the perceived benefit obtained by automakers from actively selling self-driving cars, V2 represents the perceived benefit obtained by automakers from maintaining the original car production, C represents the additional cost of consumer purchasing behavior compared to traditional driving cars, M1 represents the perceived benefit obtained by consumers from purchasing behavior, and M2 represents the perceived benefit obtained by consumers from not purchasing self-driving cars.

4. The method for analyzing the market game of autonomous driving vehicles according to claim 1, characterized in that: In S3, an evolutionary game model among the government, car companies and consumers is constructed, and the evolutionary game model is solved according to the perceived benefit matrix to obtain the original pure strategy equilibrium point, which is specifically: According to the perceived benefit matrix, the expected benefits and average expected benefits of the government, car companies and consumers under different game strategy combinations are calculated; The replication dynamic equation is obtained according to the expected return and the average expected return; The replication dynamic equation is solved to obtain the original pure strategy equilibrium point.

5. The method for analyzing the market game of autonomous driving vehicles according to claim 4, characterized in that: The expected benefits and average expected benefits of the government, car companies and consumers under different game strategy combinations are calculated based on the perceived benefit matrix, which are as follows: The expected return of constructing a high-intensity government support behavior strategy based on the government's game strategy is U 11 , the expected benefit of the government's low-intensity support behavior strategy is U 12 , the average expected return is U1, then: U 11 =(-Q-P-Kr+G1-H-sL)yz+(-Q-P-Kr+G1-sL)y(1-z)+(-Q-P+G1-H-sL+N) (1-y)z+(-Q-P+G1-sL+N)(1-y)(1-z)(1) U 12 ＝0 (2) U1=xU 11 +(1-x)U 12 (3) The expected return of constructing the active behavior strategy of the car company based on the game strategy of the car company is U 21 、The expected benefit of the auto company's passive behavior strategy is U 22 , the average expected return is U2, then: U 11 =(P+V1-W+sL-F)xz+(P+V1-W+sL)x(1-z)+(V1-W-F)(1-x)z+(V1-W) (1-x)(1-z)(4) U 22 =(P-N+V2-D)xz+(P-N+V-D)x(1-z)+(V2-D)(1-x)z+(V2-D)(1-x)(1-z) (5) U2=yU 21 +(1-y)U 22 (6) The expected return of building a consumer purchasing behavior strategy based on the consumer's game strategy is U 31 , the expected benefit of the consumer's non-purchase behavior strategy is U 32 , the average expected return is U3, then: U 31 =(H-C+M1+F)xy+(H-C+M1)x(1-y)+(-C+M1+F)(1-x)y+(-C+M1) (1-x)(1-y)(7) HER 32 =M2xy+M2yx(1-x)+M2(1-y)x+(M2(1-y)(1-x) (8) U3=zU 31 +(1-z)U 32 (9) Among them, Q represents the additional cost when the government implements high-intensity support behavior compared with low-intensity support behavior, P represents the financial subsidies provided to car companies when the government implements high-intensity support behavior, H represents the car purchase subsidies provided to consumers when the government implements high-intensity support behavior, L represents the government's tax incentives for car companies with positive behavior, s represents the government's preference coefficient for car companies' technological innovation, N represents the economic penalty for environmental and other losses caused by companies without positive behavior under the government's high-intensity support behavior, K represents the loss caused by the negative impact of the positive behavior of car companies on autonomous driving car accidents under the government's high-intensity support behavior, r represents the negative impact coefficient, G1 represents the additional perceived benefits obtained by the government from implementing high-intensity support behavior compared with low-intensity support behavior, G2 represents the perceived benefits obtained by the government from implementing low-intensity support behavior, and x represents represents the probability of high government support, 1-x represents the probability of low government support, W represents the cost of car companies actively producing and selling self-driving cars, D represents the cost of car companies passively producing and selling self-driving cars, F represents the additional discount given to consumers by car companies actively selling self-driving cars, V1 represents the perceived benefit obtained by car companies from actively selling self-driving cars, V2 represents the perceived benefit obtained by car companies from maintaining the original car production, y represents the probability of positive behavior of car companies, 1-y represents the probability of negative behavior of car companies, C represents the additional cost of consumer purchasing behavior compared to traditional driving cars, M1 represents the perceived benefit obtained by consumer purchasing behavior, M2 represents the perceived benefit obtained by consumers not purchasing self-driving cars, z represents the probability of consumer purchasing behavior, 1-z represents the probability of consumer non-purchasing behavior.

6. The method for analyzing the market game of autonomous driving vehicles according to claim 5, characterized in that: The replication dynamic equation is constructed based on the expected return and the average expected return and solved to obtain the original pure strategy equilibrium point, specifically: Based on the expected returns and average expected returns of the government, automakers and consumers, the replication dynamic equations of the government's high-intensity support behavior, automakers' positive behavior and consumers' purchasing behavior are constructed as follows: Among them, Q represents the additional cost when the government implements high-intensity support behavior compared with low-intensity support behavior, P represents the financial subsidies provided to car companies when the government implements high-intensity support behavior, H represents the car purchase subsidies provided to consumers when the government implements high-intensity support behavior, L represents the government's tax incentives for car companies with positive behavior, s represents the government's preference coefficient for car companies' technological innovation, N represents the economic penalty for environmental and other losses caused by companies without positive behavior under the government's high-intensity support behavior, K represents the loss caused by the negative impact of the positive behavior of car companies on autonomous driving car accidents under the government's high-intensity support behavior, r represents the negative impact coefficient, G1 represents the additional perceived benefits obtained by the government from implementing high-intensity support behavior compared with low-intensity support behavior, G2 represents the perceived benefits obtained by the government from implementing low-intensity support behavior, and x represents = represents the probability of high government support, 1-x represents the probability of low government support, W represents the cost of car companies actively producing and selling self-driving cars, D represents the cost of car companies passively producing and selling self-driving cars, F represents the additional discount given to consumers by car companies actively selling self-driving cars, V1 represents the perceived benefit obtained by car companies from actively selling self-driving cars, V2 represents the perceived benefit obtained by car companies from maintaining the original car production, y represents the probability of car companies' active behavior, 1-y represents the probability of car companies' passive behavior, C represents the additional cost of consumer purchase behavior compared to traditional driving cars, M1 represents the perceived benefit obtained by consumers' purchase behavior, M2 represents the perceived benefit obtained by consumers not purchasing self-driving cars, z represents the probability of consumer purchase behavior, 1-z represents the probability of consumer non-purchase behavior, U 11 represents the expected return of the government's high-strength support behavior strategy, U1 represents the average expected return of the government's high-strength support behavior strategy, and U 21 represents the expected return of the car company's active behavior strategy, U2 represents the average expected return of the car company's active behavior strategy, and U 31 represents the expected benefit of the consumer's purchasing behavior strategy, and U3 represents the average expected benefit of the consumer's purchasing behavior strategy; According to the stability of the differential equations, if F(x)=0, F(y)=0, F(z)=0, the entire dynamic system will tend to be stable, and the replicated dynamic equation is as follows: The simultaneous equations (10)-(12) are used to solve the dynamic replication equations of the three-party evolutionary game, and the eight original pure strategy equilibrium points of the evolutionary game model are obtained: E1(0,0,0), E2(1,0,0), E3(0,1,0), E4(0,0,1), E5(1,1,0), E6(1,0,1), E7(0,1,1) and E8(1,1,1).

7. A self-driving car market game analysis system, characterized in that: include: The model initialization module is used to determine that the game subjects are the government, car companies and consumers, and to construct a game subject behavior strategy set according to the behaviors of the government, car companies and consumers; and to construct a perception benefit matrix according to the game subject behavior strategy set; The model building and calculation module is used to build an evolutionary game model among the government, car companies and consumers, solve the evolutionary game model according to the perceived benefit matrix, and obtain the original pure strategy equilibrium point; A model analysis module, used to perform stability analysis on the evolutionary game model according to the original pure strategy equilibrium point to obtain a target pure strategy equilibrium point of the evolutionary game model; The model strategy output module is used to analyze the target pure strategy equilibrium point to obtain the optimal strategy combination of the government, car companies and consumers.

8. The autonomous driving car market game analysis system according to claim 7, characterized in that: The game subject behavior strategy set is constructed based on the behavior of the government, car companies and consumers, specifically: Based on the government support behavior, a set of government support behavior strategies is constructed, expressed as α = {α1, α2}, where α1 is a high-intensity government support behavior and α2 is a low-intensity government support behavior. The high-intensity government support behavior means that the government supports the research and development of autonomous vehicles by providing incentive policies, and the low-intensity government support behavior means that no active measures are taken to interfere with the research and development of autonomous vehicles by car companies and the purchase of autonomous vehicles by consumers; Based on the R&D behavior of automobile companies, a set of R&D behavior strategies for automobile companies is constructed, which is expressed as β = {β1, β2}, where β1 is the positive behavior of automobile companies and β2 is the negative behavior of automobile companies. The positive behavior of automobile companies means that automobile companies actively invest in R&D resources and vigorously introduce talents to carry out the R&D of autonomous driving technology. The negative behavior of automobile companies means that the R&D of autonomous driving vehicles takes negative measures or still adopts conventional methods to produce and sell vehicles. A consumer purchase behavior strategy set is constructed based on the consumer purchase intention, which is expressed as γ = {γ1, γ2}, where γ1 is the consumer purchase behavior and γ2 is the consumer non-purchase behavior. The consumer purchase behavior indicates that the consumer chooses to buy an autonomous driving car instead of a traditional car when the consumer has the intention to buy a car. The consumer non-purchase behavior indicates that the consumer has not chosen to buy an autonomous driving car for the time being and maintains a wait-and-see attitude towards the purchase of an autonomous driving car, considering the potential safety risks, technical failures and possible losses of the autonomous driving car. The government support behavior, the car enterprise R&D behavior and the consumer purchase behavior are arranged and combined to obtain a game subject behavior strategy set, wherein the game subject behavior strategy set includes: a first strategy combination: high-intensity government support behavior α1, car enterprise positive behavior β1, consumer purchase behavior γ1; a second strategy combination: high-intensity government support behavior α1, car enterprise positive behavior β1, consumer non-purchase behavior γ2; a third strategy combination: high-intensity government support behavior α1, car enterprise negative behavior β2, consumer purchase behavior γ1; a fourth strategy combination: high-intensity government support behavior α1, car enterprise negative behavior β2, consumer non-purchase behavior γ2; a fifth strategy combination: low-intensity government support behavior α2, car enterprise positive behavior β1, consumer purchase behavior γ1; a sixth strategy combination: low-intensity government support behavior α2, car enterprise positive behavior β1, consumer non-purchase behavior γ2; a seventh strategy combination: low-intensity government support behavior α2, car enterprise negative behavior β2, consumer purchase behavior γ1; an eighth strategy combination: low-intensity government support behavior α2, car enterprise negative behavior β2, consumer non-purchase behavior γ2.

9. A self-driving car market game analysis system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the autonomous driving vehicle market game analysis method as described in any one of claims 1 to 6 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the autonomous driving vehicle market game analysis method as described in any one of claims 1 to 8 is implemented.

Images