基于演化博弈的高速公路共谋逃费行为分析

高速公路联网收费的实现使车辆单次收费里程增长，逃费者在节省更高额过路费的诱惑下，增加了对现有联网收费系统的作弊动机.本文以减少公路运营企业因逃费造成的经济损失为目标，利用演化博弈的方法，将监管者(收费稽查员)看成博弈的一方，被监管者（司机和收费站员工）看成博弈的另一方，探讨收费稽查员监管、司机与收费站员工共谋逃费的问题，得到了稽查员选择不监管策略及司机与收费站员工选择共谋逃费策略时的复制动态方程，分析了在司机逃费罚款的机会成本等因素影响下双方的行为演化和演化稳定策略.结果表明，增强对监管者的监管和处罚力度、增加司机逃费成本、降低司机逃费少缴金额的可能性是遏制共谋逃费现象的有效途径.

Defraud Behavior of Network Toll Highway Based on Evolutionary Game Model

Expressway networking toll has been largely achieved, and as a result of the increase of mileage charges, the temptation of the higher toll saving increases the cheating motivation of drivers. This paper, aiming to reduce economic losses of highway enterprises caused by escaped toll, using the method of evolutionary game theory, considering inspectors, drivers and toll collectors as two party of game, explores the issue that supervision of inspectors and toll collectors choosing complicity with drivers to escape charges. The following are the replication dynamic equations of inspector rejecting monitor, and toll collectors choosing complicity with drivers to escape charges respectively, which analyzes the escape charges of driver under the influence of factors such as the opportunity cost of both evolution and evolutionary stable strategies. The results show that enhancing supervision of inspectors and penalties is an effective way to improve the phenomenon of complicity escaped toll between toll collectors and drivers.