Research On Freeway Traffic Flow Modeling Based On Continuous Cellular Automata

Under the situation that the car ownership has increased sharply and continues to show an upward trend,the traffic load of Chinese expressway has increased sharply and the traffic congestion is serious.The study of expressway traffic flow model can reasonably reduce the problem of road congestion and release the capacity of expressway.The study of road traffic flow theory aims to accurately depict the general characteristics of real vehicle traffic flow in the process of running,reproduce the complex traffic phenomenon,alleviate the problem of traffic congestion,improve the capacity of the road section,and become the theoretical basis for guiding the reasonable and effective operation of the traffic system.In this paper,a new type of continuous cellular automata(Cellular Automata)is used as a modeling method to construct an improved expressway traffic flow model,describe the microscopic traffic flow characteristics of expressway vehicles and analyze the influence of its related parameters,so as to provide a theoretical basis for alleviating road traffic problems.The main contents of this paper are as follows:(1)Before building the model,this paper firstly summarizes the development system of vehicle following model,then introduces the definition,composition and characteristics of cellular automata and simulates some classical cellular automata models.Then,continuous cellular automata is introduced to illustrate its differences and advantages compared with traditional cellular automata models.(2)On the basis of the safe distance-based cellular automata model,the slow start rule of vehicles is introduced and the possible influence of surrounding vehicles is considered to improve the following rules of vehicles,and the improved continuous cellular automata model of traffic flow based on the safe distance is constructed.The improved model was numerically simulated to verify its fitting degree with the actual traffic flow characteristics,and the influence of the change of traffic flow characteristic parameters and random slowing probability on traffic flow was analyzed.(3)On the basis of improving the single-lane model,the two-lane model is extended,and the F-STCA lane changing rule and the lane changing rule under the intelligent network environment are respectively used to construct the two-lane model,on the premise that human drivers are prone to psychological and physiological factors during the lane changing process.Will improve lane,ordinary double car lanes and intelligent snatched two-lane lane changing environment model for numerical analysis and comparison of characteristic parameters change rule and the number of lane changing impact on traffic flow,and found that the use of environment perception system help traffic lane changing double driveway model can effectively avoid the human pilot lane changing are susceptible to interference problems,at the same time also more effective ability of lane changing,It is conducive to improving the capacity of the road.The experimental results show that the lane changing model in the intelligent network environment can effectively reduce the proportion of traffic jams.