Analysis Of Urban Road Congestion Based On DBSCAN And Aprior

As the economy continues to develop and the speed of urbanization is accelerating,the number of motor vehicles is increasing year by year,and road congestion has become a huge problem that plagues most cities in China.However,to manage and alleviate road congestion,it is necessary to accurately analyze and accurately locate the road congestion laws and morphological characteristics.The data volume of urban road traffic situation is huge and the structure is complicated.It has been difficult to use traditional data analysis methods,and the unique advantages of processing big data with the help of spatiotemporal data mining can make up for this deficiency.In order to help relevant departments accurately grasp the macroscopic situation of road congestion in the entire city,so as to prevent and consolidate road congestion in advance,it is particularly important to analyze the spatiotemporal clustering and spatiotemporal correlation analysis of traffic congestion.The current DBSCAN cluster analysis and Apriori correlation analysis on road congestion often use the method of intercepting a certain time segment.This method of segmenting the time attribute will inevitably cause a certain deviation to the data mining results.Since the traditional DBSCAN algorithm and Apriori algorithm are difficult to apply to spatiotemporal data mining of road congestion,this paper proposes corresponding improvement strategies and methods for these two algorithms on the basis of drawing on the previous technology and experience.In order to verify the feasibility of the improved DBSCAN spatio-temporal clustering algorithm and Apriori spatio-temporal correlation algorithm for spatiotemporal data mining in the field of road congestion,this paper collected the road congestion data in the main urban area of Kunming for more than a month,and then used the improved The algorithm performs practical calculations,and finally excavates the time and area where congestion often occurs in the road network of the main urban area of Kunming,and the degree of mutual influence between the congested roads.At the same time,with the help of the powerful spatial data processing capabilities of GIS-related software,the mining results were visually displayed,and several feasible suggestions were made for how to alleviate and manage road congestion.The specific research content and results are as follows:(1)Using web crawler technology,collected the traffic situation data of the main urban area of Kunming for nearly a month,and developed an ArcGIS plug-in that can convert the traffic flow coordinate point data in the database into a road layer file based on ArcPy.The need for time-space mining visualization.(2)The time dimension of the DBSCAN algorithm has been expanded.By stacking and processing layers of congested road sections at multiple consecutive times,it was equivalent to ordinary three-dimensional spatial data,and the improved DBSCAN algorithm Apply to 3D clustering.After the space-time cluster excavation of the road congestion in the main urban area of Kunming,the time and area where road congestion often occurs were successfully analyzed.(3)The Apriori algorithm was merged in the time dimension.The attribute was merged into a new item by merging the road congestion time and the road number for the first time.At the same time,the Apriori algorithm was improved so that it can be split again when processing the operation results.Time attribute value and road number value,and finally get the time and space related information of each road congestion.After excavating the spatiotemporal correlation of traffic jams in the main urban area of Kunming,the correlation between road congestion was found.The improved DBSCAN spatiotemporal clustering algorithm and Apriori spatiotemporal correlation algorithm proposed in this paper can effectively mine the spatiotemporal laws of urban traffic roads.The mining methods and technical processes obtained by the study can provide a reference for similar research.At the same time,the mining results can also provide a scientific basis for relevant departments to carry out traffic control and road planning.