Research On The Spatial And Temporal Characteristics Of Road Network Structure And Traffic Flow

The large-scale and rapid urbanization process in China has promoted urban economic growth and raised the material living standards of the people.However,it has also resulted in urban diseases such as air pollution,traffic congestion,shortage of public service facilities,etc.Among them,traffic congestion not only affects the operational efficiency,economic and ecological benefits of the city,but also affects the daily travel and quality of life of urban residents.Urban road data and taxi trajectory data contain rich traffic information and are important perceptual data for analyzing urban traffic status.Based on methods such as complex network,this thesis uses road data to analyze the characteristics of road network structure,and uses taxi trajectory data to analyze the spatial and temporal characteristics of traffic flow.Moreover,it takes road intersections as the research object to evaluate the matching between road network structure and traffic flow,so as to discover the areas where there is a mismatch between road planning and traffic demand.Finally,this thesis conducts an empirical study using the urban area within the second ring road of Wuhan as the study area to verify the validity of the research method.More specifically,the contents and results of this thesis are as follows:(1)Analyzing the characteristics of urban road network structure by using some centrality indexes.Based on the topological and functional attributes of the road data,a directed weighted road network model incorporating various attributes such as direction,functional class and number of lanes is designed.The road network is constructed by using this model.And the multi-centrality index is proposed by integrating directed weighted degree centrality,directed weighted betweenness centrality,directed weighted closeness centrality,directed weighted Page Rank centrality to comprehensively evaluate characteristics of the road network structure.By using some simple centrality indexes and the multi-centrality index,the characteristics of the road network structure are analyzed in terms of numerical distribution and spatial distribution.And the critical nodes of the road network are identified by applying the multi-centrality index.It is found that the road network in the study area is a scale-free network,and the critical nodes are mostly distributed on the main roads such as Jiefang Avenue,Wuhan Avenue and Jianshe Avenue.(2)Analyzing the spatial and temporal characteristics of urban traffic flow.Based on taxi trajectory data,the traffic flow of road intersections is measured respectively during four peak periods: weekday morning peak,weekday evening peak,weekend morning peak and weekend evening peak.And the spatial and temporal characteristics of traffic flow are analyzed in terms of numerical distribution and spatial distribution based on them.Specifically,the numerical changes of the total amount of traffic flow and the distribution of traffic flow in descending order under different peak periods are analyzed.Moreover,the spatial and temporal distribution patterns of traffic flow,as well as the spatial and temporal distribution patterns of critical intersections,are also analyzed in the four peak periods.And the characteristics of intersection ranking volatility in all peak periods are analyzed as well.It is found that the total traffic flow on the road network in the study area reaches a maximum during the weekday morning peak and drops to a minimum during the weekend evening peak.And only a small number of intersections have small fluctuations in traffic flow,and most of the intersections with high traffic flow in all peak periods are located on Jiefang Avenue and Wusheng Road.(3)Evaluating the matching between road network structure and traffic flow.Based on the multi-centrality index and traffic flow of road intersections,the matching evaluation method of urban road network structure and traffic flow is designed.This method includes a global matching measure based on the correlation of the multicentrality index and traffic flow of road intersections,and a local matching measure based on the comparison of road network structure level and traffic flow level.By applying this method,the global and local matching of the road network is measured under the four peak periods.Further,the numerical variation of global correlations,as well as the numerical variation and spatial distribution patterns of local matching types under the four peak periods,are analyzed.Moreover,the number of intersections that have experienced mismatches in each peak period is counted,and the spatial distribution of intersections with different degrees of mismatch types is analyzed.It is found that the matching between road network structure and traffic flow in the study area is good,and the global matching correlation reaches the highest in weekday evening peak and drops to the lowest in weekday morning peak.In each peak period,the percentage of intersections for level matching is higher than 80%;those for level mismatch are mainly shown as a shortage of road supply,mostly distributed in the northwest and southeast areas of the study area,located on roads such as Pengliuyang Road,Minzhu Road and Dingziqiao Road.In summary,this thesis can provide relevant departments with scientific and practical reference in road planning and traffic management to a certain extent,which is conducive to planning and resource allocation to optimize urban spatial structure,alleviate urban traffic pressure and promote the sustainable and benign development of urban traffic.