Research On Route Selection Algorithm Of Online Car Based On Game Theory

In recent years,with the rapid development of the city,as an important part of urban development,urban traffic road network has become more and more obvious.The "China Manufacturing 2025”report issued by the State Council clearly stated that intelligence,network integration,and low carbonization will be the main directions for the development of the automobile in the future.The use of intelligent transportation systems to solve the comprehensive problem of road network is a current trend.The dynamic path optimization method is the core of solving urban traffic congestion and reducing environmental pollution.Game theory is a mathematical theory and method for studying the phenomena of struggle or competition.It mainly studies how policymakers make decisions under a given information structure to maximize their utility,and the tactical equilibrium among different decision-making bodies,which also considering their actual behavior and predictive behavior.This article researches and analyzes based on the theory of game theory about the path selection and reduction of automobile losses of the networked vehicles,The main research results are as follows:Based on the game theory and using the Stackelberg game model,we propose an intelligent network-linked car routing(SINAER)algorithm based on game theory.Path selection for existing vehicles sometimes cannot be optimal,First of all,a model was established in which the traffic network is the "manager" and the driving vehicle is the "traveler",we catch the contradictory point of managers and travelers Want to Optimum,the managers are pursuing the maximum utilization of the traffic network.And the travelers consider the least comprehensive cost.Combining CPS and Intelligent Grid-linked Vehicles,an intelligent networked vehicle routing(SINAER)model based on Stackelberg game is constructed,the model combines the road networks,road monitoring systems,communication stations and travel vehicles with the CPS theory for path selection,taking into account the needs of the traffic network system and travel vehicles.The deep integration of computer technology,communication technology and control technology in the SINAER model can realize the real-time perception and dynamic control of the path selection process.Based on SINAER model and fuzzy theory,we design intelligent network-linked traffic diversion strategy.In order to increase the accuracy of the diversion of managers to travelers,optimize the structure of the road network.This paper proposes a fuzzy route diversion strategy based on road traffic flow control output based on road congestion degree and congestion change rate,which can optimize managers'manage-ment strategies,and use of genetic algorithms to make managers as optimal as possible.Path selection simulation model established in MATLAB,and simulated the path selection process without traffic diversion and traffic diversion.The simulation results show that the path selection model based on game theory can make the road network traffic flow more balanced in the presence of traffic diversion than without traffic diversion,travelers have less travel loss.This verifies the feasibility and effectiveness of the game model and the solution algorithm in this paper,and In line with the user's path selection needs and the economic benefits of both.