Research On Road Segment Traffic Flow Characteristics Based On The Cellular Automata Model

With the development of science and technology and the leapfrog progress of vehicle technology,more and more vehicles are equipped with L2 auxiliary driving system,and various vehicle enterprises actively develop and improve their semi-automatic driving technology,with a trend of gradual development to L3 driving mode.Although China’s automobile industry started later than the Western old industrial countries,but in the field of new energy vehicles is the most rapid development,the highest degree of technology integration of the country,the development of domestic new energy vehicles in recent years is obvious to all,among which auxiliary driving(semi-automatic driving)as a kind of car companies to buy publicity,a full popularity of L2 driving mode momentum.At present,many scholars and experts have conducted research on traffic flow of autonomous driving and intelligent networked vehicles,but the research on subdivided assisted driving vehicles is relatively limited.Although both belong to the research on characteristics of automatic-manual mixed traffic flow,there are also differences.At the same time,in the study of lane change rules,previous studies often use a probabilistic model to determine the conditions of lane change behavior.Such a probabilistic model will lead to the imprudence of lane change rules,so it is necessary to introduce a judgment threshold based on safety distance and speed to regularize lane change behavior.The objectives of this paper are as follows:Firstly,Understand the rules of cellular automata model,and update them to more suitable for the following evolution rules of actual L2 and L3 vehicles and human-driven vehicles.Besides,refine the rules of lane change model,introduce the dissatisfaction to establish lane change rules,optimize lane change from probabilistic events to threshold triggering events,and make lane change behavior more scientific.Secondly,On the basis of the established rules,the cellular automata model simulation experiment is carried out.First,the single lane is simulated and set.In order to eliminate the unstable state so as not to produce objective results,the last 3000 s of the evolution time is analyzed,and the three elements diagram and space-time diagram related to the traffic flow characteristics are drawn for analysis.The increase of the permeability of L2 and L3 vehicles will gradually reduce the random deceleration behavior and necessary deceleration behavior of traffic flow on the road section.When the permeability is 1,the traffic flow will be close to the ideal state.Combined with the analysis of congestion rate,the congestion rate will be lower under the high permeability.Finally,this paper simulates the three-lane traffic flow,and analyzes the characteristics of the stable traffic flow in the last 3000 s of the evolving 5000 s in order to eliminate the unstable state.The condition of the three-lane traffic flow is more in lane with the reality,because the lane changing rules are added,so that there will be the necessary deceleration behavior of lane changing vehicles in the space-time diagram.When the vehicle permeability of L2 and L3 is 1,it is impossible to reach the ideal state,which conforms to the objective phenomenon,but it still greatly reduces the deceleration area on the road.Meanwhile,the lane change relationship with different dissatisfaction is added,which reflects the accuracy of the introduced lane change dissatisfaction,and the permeability still significantly improves the reduction of congestion.