Research On The Identification And Facilitation Of Urban Road Traffic Congestion

With the gradual development of cities and the increasing number of cars in recent years,traffic congestion on urban roads has become increasingly serious.This phenomenon not only reduces the capacity of local road sections,but also affects the efficiency of the overall road network.Traffic congestion identification is a key step in relieving traffic congestion,while congestion mitigation is a necessary tool to reduce traffic congestion.In this context,it is of great practical importance to conduct research on traffic congestion discrimination and decongestion with the aim of alleviating the overall road network congestion.The main work of this paper is as follows:(1)Using the four-stage approach as the entry point,traffic demand forecasts are carried out for 13 traffic cells in the study area.The traffic generation and attraction calculations are based on the land use planning of the road network coverage area,combined with the sharing rate and the standard car conversion factor,and then the traffic impedance matrix,traffic distribution matrix,road network traffic flow data and traffic congestion are calculated with the help of TransCAD software.(2)In terms of traffic congestion discrimination,FCM,as an unsupervised learning algorithm,is flexible to fuzziness and can better reflect the traffic status between roads compared to single indicator evaluation.Based on this,this paper combines quantitative and qualitative principles,selects road flow and average travel time as congestion discriminating parameters,and establishes a traffic congestion discriminating model.(3)Traffic distribution is the main research content for congestion relief,aiming to provide travel reference for travellers through road flow distribution to avoid further congestion;provide information support for managers to understand the possibility of congestion and make timely decisions.In this paper,the genetic algorithm is combined with the FW algorithm to solve the traffic distribution model,and the genetic-FW algorithm is proposed to solve the optimal discrete distribution model of the system to complete the traffic distribution.MATLAB software is used to simulate the above algorithm,and the results are compared with TransCAD demand forecasting results for the overall road network and local road sections.The results show that the allocation using the Genetic-FW algorithm can better relieve the road sections above moderate congestion with an optimum optimisation rate of 5.6%,which has a certain improvement on the overall congestion of the road network.In addition,the genetic-FW algorithm takes into account global factors more than the two allocation methods,diverting some traffic to secondary roads and slip roads.Based on the idea of global optimum to alleviate road network congestion,not only can road utilisation and traffic efficiency be improved,but also provide different information references for different players in the traffic system.For travellers,the overall road network situation can be provided to optimise their route choice;for traffic managers,the overall efficiency of the road network can reflect the overall traffic service level,so that they not only have a more accurate grasp of the current traffic situation in the city,but also For traffic managers,the overall efficiency of the road network can reflect the overall level of traffic service,enabling them to have a more accurate grasp not only of the current traffic situation in the city,but also of future changes and to react more quickly and effectively to congestion.