The evolutionary game of enterprise and driver fatigue regulation in the intelligent networked environment-A case study in Jiaozuo city, China

Abstract

To give full play to the role of fatigue supervision of intelligent monitoring platforms, We consider the shortage of the traditional management model of enterprises. The management game model of enterprises and drivers is built from the benefits of drivers. Taking 79 drivers of enterprise A in Jiaozuo City as an example, the number of fatigue violations of each driver in each of the six consecutive months was counted. Combined with the system clustering method, the drivers are classified according to the trend of the number of violations. Finally, different regulatory measures were proposed for different categories of drivers according to the evolution of the regulatory game system. The model evolution simulation results show that when the cost paid by the driver for violating the law (c) is greater than the additional benefit generated by the violation (d), the driver will choose not to drive fatigued to protect his benefits. The classification results show that drivers can be divided into four categories:① class no fatigue violation records; ② class fatigue violation records show a downward trend; ③ class fatigue violation records show wavy changes, indicating repeated violations; ④ class fatigue violation records show an upward trend. The number of violations varies for different categories of drivers. The d increases as the number of violations increases. Therefore, different management measures are proposed to increase c for the 4-type drivers so that the parameters of each type of driver satisfy the range of values of c>d. Thus, the driver evolves in the direction of no-fatigue driving. It can effectively regulate fatigue driving and improve driving safety.

Keywords

• Intelligent network
• Fatigue warning
• System clustering
• Regulatory game
• Evolutionary simulation
• Classification management