| Traffic congestion has become a problem that plagues major cities in the world,seriously polluting the environment,causing huge economic losses,and also endangering the physical and mental health of human beings.Traditional means of solving traffic congestion problems,such as new roads and optimization of nodes,have become ineffective and unsustainable when urban land is becoming increasingly tight.Intelligent transportation systems,such as route guidance and vehicle-road coordination,adjust the distribution of traffic flow in the road network from a comprehensive perspective to maximize the service capabilities of the road network.It is one of the research focuses in the field of traffic engineering at this stage.However,due to the lack of understanding of traffic congestion transmission laws and the scope of traffic congestion transmission,it is difficult to formulate reasonable traffic control methods,making it difficult for intelligent transportation to play the true role of the urban brain.Therefore,it is necessary to study the propagation of traffic congestion in urban road networks.This paper first obtains the actual urban road network parameters and analyzes the data scale range through the Gaode Map API interface and Open Street Map to construct a simulated road network.Then analyze the discontinuous flow characteristics of the signalized intersections and the operating conditions of the intersection entrance roads with different queuing lengths,clarify the influence of the queuing length on the capacity of the intersection entrance roads,and analyze the continuous congestion situation of the regional intersection group in combination with big data.Then analyze the topological structure characteristics of the urban road network,analyze and select the appropriate impedance model,and consider the node delay in the shortest path algorithm and traffic assignment algorithm to reflect the true traffic characteristics to the maximum.Then based on the congestion process of the basic sections in the urban road network,a cascading failure model suitable for the urban road network is selected and its parameters and assumptions are calibrated.Finally,the improved cascading failure model and traffic distribution algorithm combined with the established road network are used to carry out simulation research on traffic congestion propagation,and analyze its propagation process,consequences and influencing factors.The main results of this paper are as follows: 1.Established an improved Dijkstra algorithm and traffic assignment algorithm(UE,SUE,and SO)that take into account node delays and complete coding based on MATLAB.The results show that the route selection and traffic assignment results after considering delays at nodes.Considering the situation,the difference is large;2.Select the load-capacity model to fit the two-level model of the urban transportation network,and determine the key parameters and assumptions of the cascading failure model applied to the urban road network by analyzing the signalized intersections,Including load,capacity,failure determination conditions,load redistribution principle,impedance update principle,etc.,and introduce the time dimension in cascading failure analysis,solving the traditional cascading failure analysis can only analyze the road network status and not its time Defects of change.3.Based on the assumption that road network users choose the shortest path to divert traffic after the road ahead is impassable,a simulation study of traffic congestion propagation is performed,and the results show that the improved model in this paper can well analyze the traffic state in the time and space dimensions.The evolution relationship of the model and the status evaluation of the road network at different times have proved the practicability and effectiveness of the improved model. |
