Dynamic Modelling And Stability Analysis Of Traffic Flow Based On Intelligent Transportation System

In recent years,the problem of traffic congestion has become a major problem faced by many cities,and the study of traffic flow theory is undoubtedly very necessary to guide and solve this problem more scientifically.At present,with the rapid development of 5G,AI,Internet of things and other technologies,the intelligent transportation system(for short,ITS)has become the development direction of intelligent transportation in the future.The wide application of ITS will have an important impact on the traffic flow.Therefore,the dynamic modelling and stability analysis of traffic flow in ITS environment has important practical significance and engineering application value for alleviating traffic congestion.Based on the existing microscopic and macroscopic traffic models,and vehicle networking communication technologies(e.g.,V2V: Vehicle to Vehicle),we consider some significant traffic information such as the multi-anticipative average velocity effect,average flux effect and average density effect of preceding vehicles group,several improved traffic flow models are established,and the corresponding theoretical analysis and numerical simulation are performed.Moreover,the stability of the traffic system,traffic density waves and various nonlinear phenomena are also investigated.All of these studies can provide useful theoretical basis and decision-making reference for the traffic control department.The main contents of the thesis are as follows:?.From the microscopic point of view,an extended car-following model is proposed to simulate traffic flow by considering multi-anticipative average velocity effect(including the average velocity and the mean expected velocity field effect of preceding vehicles group)under V2 V environment.The influence of multi-anticipative average velocity effect on the stability of traffic flow is investigated,and the nonlinear characteristics of traffic flow are also discussed in detail.The results show that considering the multi-anticipative average velocity effect can effectively improve the stability of the traffic system and alleviate traffic congestion.This research can provide a certain theoretical basis for the research of vehicle-to-vehicle communication technology.?.From macroscopic point of view,two improved lattice hydrodynamic models are established by considering the multi-anticipative average flow effect and the average optimized flow difference effect under the ITS environment,respectively.The influences of different flow effects on the stability of traffic flow are studied.Through linear and nonlinear analysis,we found that both the multi-anticipative average flow effect and the average optimized flow difference effect have a stabilizing effect on the traffic flow.When more information of traffic flow in front of the road is considered,the traffic system would become more stable and traffic congestion would be more easily suppressed.The above research can provide certain theoretical basis for the research of the feedback and control of flow information in intelligent transportation system.?.Based on the application of the ITS,two two-lane lattice hydrodynamic models of traffic flow are established by considering the average density effect and the multilattice average density difference effect,respectively.The influence of two kinds of density-related information feedback on the stability of the traffic system is discussed in detail.Through linear stability analysis,the stability conditions of two models are obtained,respectively.Through nonlinear analysis,the m Kd V equations are derived to describe the evolution characteristics of traffic density waves,respectively.The simulation results show that these two effects have a stabilizing effect on the traffic system,and the more information about the density of the lattice numbers in front,the more stable the traffic flow.In a word,in the ITS environment,considering the effects of multi-anticipative average velocity,average flow and average density difference can effectively suppress traffic congestion and improve the stability of traffic flow.Our research can provide a certain theoretical basis for the development planning of intelligent transportation system and the design of intelligent vehicle autonomous driving control strategy.The final chapter of this thesis is devoted to an analysis and prospect of further study of the road traffic flow.