Car-following Cloud Model For The Driving Cycle Simulation

In recent years, with the development of economy and the rapid increase of urban carownership in china, the car following behavior has become one of the most common trafficphenomenon on urban road. Research on adjacent traffic laws and car theory have aroused theinterest of many researchers, they have proposed successively to describe car-following ruleof propagation model, linear model, nonlinear model, car safety spacing model and so on.Car-following model is one of the basic model of the driving cycle simulation, The existingcar-following model can not meet the requirements of the driving cycle simulation.The driver in the car-following process showed a vague and uncertain behaviorcharacteristics, It is difficult for the driver’s behavior accurately described with mathematicalmodel. Most of the existing car-following model are used explicit function to describe thedriver’s behavior. In fact the driver’s response to the stimulation of preceding vehicle is notexplicit one-to-one relationship. It is based on a set of rules of driving derived of theexperience. At present has not been found a car-following model to meet the requirements ofthe driving cycle simulation. The research results of the driver and vehicle characteristics canbe used for driving safety analysis, the vehicle operation simulation as well as to the future ofintelligent vehicle technology development aspects.According to the analysis of the car-following model research status, in order to meet therequirements of driving cycle simulation under actual car-following condition of the vehicleoperation simulation, in this thesis, the cloud model proposed by Academician Li Deyiintroduced to the following model.To express uncertainty and asymmetric driving behavior inthe car-following process.The purpose of this thesis is to provide a car-following behavior model for the drivingcycle simulation, based on the international advanced theories of artificial intelligence withuncertainty and study the general form of the domestic and foreign existing car-followingmodel for reference, The relative velocity at time t, inter-vehicular distance at time t, thefollowing vehicle speed at time t plus T (T for the driver’s reaction time) and the followingvehicle acceleration at time t plus T are introduced into the car-following modle, expressedthrough the cloud model, mainly in the following aspects of the work:1. Through analysis of previous data obtained by radar and analysis the limitations of the method that measuremented data by radar, adjust the test system, moreover, real vehicletest has been done on the section from Cai Yu square south plaza to ring expressway inchangchun city, jilin province. Establishment of a database, through the two test sections ofthe test data analysis the impact of the relative velocity at time t, inter-vehicular distance attime t and the following vehicle speed at time t plus T on the following vehicle acceleration attime t plus T.2. Through compiling car-following data analysis program and designing the GUIinterface with MATLAB platform, checked and analysised the validity of the results of thecar-following test data and established calculation interface according to the general form ofthe car-following model.3. This thesis calculated the driver’s response time and reaction intensity coefficientsby applied system parameter identification to car-following velocity transfer function, and theresult analysised.4. Using cloud transform theory proposed by academician Li Deyi, mining the conceptof the relative velocity, the inter-vehicular distance, the following vehicle speed and thefollowing vehicle acceleration contained in the data.Established a car-following cloud model,which use the cloud model of operating speed established by our institute (vehicle operatingsimulation group) for reference, moreover, adjusted and improved the model.5. Realized the automatically extraction of rule-base from regulations by using Anfistraining data, reduced the workload of the establishment of the rule-base.6. Verified the car-following cloud model established in this thesis through test dataand the results are analyzed.