出租车驾驶员交通违法行为演化博弈模型

In order to investigate the mechanism of violation costs on taxi drivers' traffic violation behavior, the composition and cumulation of traffic violation costs over time are explored with a demerit point system. To be specific, the taxi driver's license status were classified into two categories by setting warning score, i.e., ordinary driver and critical driver. An evolutionary game model was introduced to analyze the strategies adopted by taxi drivers and traffic policemen. Simulations were conducted to reveal the evolutionary outcomes of violation strategies under different enforcement and license management conditions. The results show that the violation costs, which impact the strategy equilibrium, is predominately determined by the level of law enforcement and deducted penalty points; for the numerical example, the administrative costsfor critical drivers are lower than those of the ordinary ones, revealing that police could use about 30% lower enforcement possibility to obtain the similar effectiveness; the violation probability of critical drivers is far lower as opposed to that of the ordinary drivers under the same enforcement; If there is equal number of drivers who daily reset their licenses, they would have 10% penalties than that of the driver whose licenses never reset in one cycle (1 a). Moreover, the penalty difference become much remarkable with time. The results demonstrate that turning the taxi driver's license qualification from ordinary into critical state through adjustable enforcement strategy will help to constrain the traffic violations and reduce the enforcement costs.