Evolutionary Game Model of Traffic Violations among Taxi Drivers
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摘要: 为研究违法成本对出租车驾驶员实施违法行为的影响，根据驾照管理方式，对交通违法成本构成及其累积过程进行研究. 通过设置警戒分数线，将出租车驾驶员分为一般和临界两个状态，构建了不同执法策略条件下，出租车驾驶员与交通执法者间的演化博弈模型，并采用仿真手段模拟不同执法及驾照管理条件下，出租车驾驶员的违法策略变化情况. 研究结果显示：执法水平和驾照分扣除程度直接影响违法成本，并决定双方的演化均衡；交通管理者对临界驾驶员采取低于一般驾驶员约30%的执法概率即可达到类似执法效果，临界驾驶员执法成本更低；相同执法水平下，临界驾驶员违法概率低于一般驾驶员；记分周期（1 a）内，每天相同人数更换驾照时，遭交通处罚的一般驾驶员人数相比不更换驾照条件多约10%，且随时间推移人数持续增加. 相关改善措施可考虑调整执法策略或改变驾照更新制度，促使出租车驾驶员驾照资格从一般转入临界状态，有助于遏制其交通违法行为，降低交通执法成本.Abstract: 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.
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Key words:
- taxicabs /
- game theory /
- costs /
- taxi driver /
- traffic violation /
- evolutionary game model /
- demerit point system
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图 1 出租车驾驶员驾照资格转化过程
Figure 1. Transformation process of taxi driver’s license qualification
图 2 3种初始概率下两类驾驶员违法策略演化
Figure 2. Traffic violation evolution of two types drivers based on different original strategies
图 3 3种初始概率下两类驾驶员遭3次及以上的处罚人数
Figure 3. Number of two types of drivers punished at or more than three times under three conditions
图 4 3种初始概率下两类驾驶员驾照分扣除的累计人数
Figure 4. Accumulated number of two types of drivers under three license points deduction conditions
图 6 驾照更换对每月遭处罚人数的影响
Figure 6. Influence of driving license replacement on monthly number of punished drivers
图 7 驾照更换对进入临界状态人数的影响
Figure 7. Effect of driving license replacement on the number of critical drivers
表 1 抽样调查结果
Table 1. Questionnaire Results
统计结果 日工作时间/h 月净收入/元 公司是否会二次罚款 1 a 内可接受罚金/元 1 a 内可接受累积扣分/分 最大值 14 6 500 1 3 000 12 最小值 7 2 000 0 100 1 均值 11.19 4 244 0.33 468 6.02 注：“公司是否会二次罚款”中的“1”表示会二次处罚，“0”表示不会二次处罚. 
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表 2 出租车驾驶员与交通执法者博弈矩阵
Table 2. Game matrix of taxi dirvers and traffic enforcement men
驾驶员 策略 交通执法者 执法 不执法 一般驾驶员 违法 $\left(\left(B - {C_{\rm{O}}} - r{C_{\rm{T}}} - r{C_{\rm{E}}} - r{C_{\rm{A}}}\right)\right)$，$\left. r{C_{\rm{E}}} - A - I\right)$ $\left(B - {C_{\rm{O}}}\right.$，$\left. - I\right)$ 不违法 $(0$，$ - A)$ $(0$，$0)$ 临界驾驶员 违法 $( B - {C_{\rm{O}}} - r{C_{\rm{T}}} - r{C_{\rm{E}}} - r\alpha {C_{\rm{Q}}} - r\alpha {C_{\rm{C}}} - r{C_{\rm{A}}}$，$r{C_{\rm{E}}}{\rm{ + }}r\alpha {C_{\rm{Q}}} - A - I)$ $(B - {C_{\rm{O}}}$，$ - I)$ 不违法 $(0$，$ - A)$ $(0$，$0)$
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