Study On Governance Strategy Of Road Traffic Recessive Illegal Behavior Based On Game Theory

With the rapid growth of the number of motor vehicles and drivers,road traffic illegal behavior presents diversity,and traffic law enforcement is facing great challenges.At present,a series of illegal behaviors still occur frequently that cannot be completed online law enforcement through video surveillance facilities,such as drunk driving,driving without a license,etc.,which has brought huge hidden dangers to road traffic safety and seriously affected the orderly and smooth road traffic.Such illegal acts often require traffic law enforcement officers to go to the scene to enforce the law and investigate,but the enforcement effect is often unsatisfactory.This paper defines this kind of traffic illegal behavior as road traffic recessive illegal behavior.In view of the frequent occurrence of hidden illegal behaviors in road traffic and the low detection rate of them by law enforcement,based on the game theory,the modeling of traffic participants,actions and other elements is carried out to study the contradiction,conflict and strategic confrontation mechanism between drivers and law enforcement,and put forward constructive suggestions on the governance of hidden illegal behaviors in road traffic.First of all,according to the overall characteristics of current urban traffic law enforcement management,the definition,characteristics and causes of road traffic recessive illegal behavior are analyzed.For related parameters involved in the driver and law enforcers earnings make reasonable assumptions,the signal game model is applied to the enforcers of the recessive illegal traffic investigation process,by solving the model,it is concluded that an effective separation equilibrium and the existence of Nash equilibrium conditions,illuminates the recessive illegal acts on road traffic and the difficulty.Secondly,based on the problem that the signal game model is difficult to separate the equilibrium solution,the detector mechanism is introduced to improve the signal game model,so that the law enforcement officers can update their beliefs and choose actions according to the trust degree and the signal of the driver.The confusion equilibrium and semi-separation equilibrium of the signal game model are obtained,which reveal the probability of driver and enforcer choosing each strategy under different prior probability.Example simulation shows that the tendency of the enforcer to form two kinds of trust degree and the quality of trust degree have important influence on the prior probability interval of the pure strategy for the driver to choose,the probability of the driver to show their own actual type and the equilibrium utility of the enforcer.Then,in order to describe the evolutionary stability results of the continuous game between groups over time,a tripartite evolutionary game model was constructed,including the detector enterprise,the driver and the traffic law enforcement.The equilibrium point and stability of the dynamic equation of replication were analyzed,and six evolutionary stability strategies and their existence conditions were obtained.The simulation results show that the change of relevant benefit parameters can affect the evolution process of the stability strategy,and some parameters can significantly accelerate the evolution convergence rate.Finally,based on the analysis results of the signal game model and the evolutionary game model,the paper puts forward some specific suggestions on the governance of road traffic recessive illegal behaviors from the perspective of the decision-making mechanism of law enforcement and the long-term behavior evolution of each subject.