Evaluation Of Economy Driving Strategy Based On The Simulation Of Driver's Game Behavior

The development of vehicular networking technology provides the possibility for the realization of intelligent transportation system.In the process of popularization of the car networking,how to use the car Networking provides information to help the driver to improve traffic efficiency and reduce fuel consumption become a hot research topic in the field of automobile.From the vehicle characteristics to study energy-saving driving has matured;this kind of research is mainly based on the engine power and economy to adjust the speed and acceleration of the vehicle.This method is often difficult to achieve the desired driving efficiency and energy saving due to the interference of the surrounding vehicles.The study of energy saving driving from the driver's behavior and traffic conditions can avoid the situation that other vehicles do not conform to the actual situation.But,it is necessary to carry out experimental verification on the effectiveness of the proposed strategy.However,the actual road or test field experiment based on real vehicle usually has the problems of high cost,long cycle,complex scene and poor repeatability.The traditional vehicle traffic simulation technology and system simulation technology has the advantage of low cost and high repeatability,but also unable to realize the simulation of the information sharing under the vehicle to vehicle networking.Therefore,this paper studies the evaluation method of economy driving strategy under the the vehicle to vehicle networking.The driver game simulation system for vehicle simulation based on vehicle network is established,which is used to evaluate the driver's driving strategyThe main work and achievements of this paper are summarized as follows:1.The driver game simulation system is analyzed and the simulation platform is designed.The platform mainly includes road generation and signal lamp module,driver behavior simulation module,human-computer interaction module and data analysis module.The road model and signal timing scheme reference the actual road conditions.The driver behavior simulation module includes the GM following model and the improved Gipps lane changing model.The driver behavior parameters are selected according to the actual survey results.The man-machine interaction module can display the position of the vehicle and the real-time state of the signal lamp in the simulation process.The data analysis module can be used to calculate the corresponding driving index and save the result.2.The performance of the simulation platform is evaluated.The evaluation index of driver game simulation platform is studied.The performance of the simulation platform is evaluated by using the average travel speed,the distribution uniformity,the velocity distribution,the idling ratio and the velocity time series.The simulation experiment is carried out,and the platform is verified according to the certain indexes.3.The selection of simulation parameters in typical traffic conditions is studied.The simulation experiments were carried out to determine the number of vehicles representing free flow,flat peak flow and peak flow,respectively 100,300 and 800.The simulation experiment under different simulation time is obtained,and the convergence of statistical data is obtained when the simulation is up to 5400 s.4.The evaluation index and reference value of economy driving strategy are studied.The indicators used to evaluate economy driving strategy are analyzed,and the time and fuel consumption revenue are determined.By using the method of intermediate value,these two indexes are unified into the gross profit as an index to evaluate the economy driving strategy.5.The experiment of the fixed strategy is designed to simulate the energy saving effect under different vehicle numbers,different driver type proportional distribution and single driver type.The results of various types of drivers under different conditions are analyzed,which are used as the reference value for evaluating driving strategies.According to the pure strategy game and mixed strategies game,this paper analyzes the driving income of each type of driver.Comparison of the theoretical value and the simulation value,conclude that in actual traffic environment,the income difference of different driving strategies is relatively small,and the overall income presents a state of equilibrium.6.This paper analyzes the actual effect of three driving strategies of learning strategies,such as follow strategy,average strategy and combination strategy.The simulation experiments are carried out under different driver types proportional distribution and different number of vehicles.The actual revenue of the following strategies,the average strategy and the combination strategy are calculated respectively.According to the statistical results,the actual effect and application scope of various types of economy driving strategies are evaluated.According to the analysis results,the various types of drivers are not in any traffic environment and traffic density under the continued dominance,only according to the road traffic environment and traffic density adjust driving strategy can achieve better energy-saving effect.