Evaluation Method Of Urban Road Traffic Data Flow Quality Based On Grey Correlation

With the acceleration of urbanization and the continuous growth of car ownership,urban transportation is facing increasing challenges.Traditional way of road traffic management methods can no longer meet the needs of urban development,and the application of information technology has become an inevitable choice to improve the refinement,efficiency,and intelligence of urban road traffic management.In order to achieve intelligent traffic management,a large amount of traffic flow data is needed as its foundation.In reality,the frequent occurrence of missing,abnormal and repeated traffic flow data has brought great inconvenience to transportation planning,traffic management,traffic control,so it is urgent to evaluate the data quality of traffic flow data.To achieve a comprehensive evaluation of the quality of traffic flow data,this paper takes urban road traffic flow data as the research object,analyzes its data characteristics,determines the evaluation index of traffic flow data by the factors of data quality,and proposes an optimized comprehensive evaluation method for evaluation index.The main work of this paper is as follows:(1)According to fully describe the characteristics of traffic flow data,the evaluation index of traffic flow data based on the microwave detector data is established in this paper.By analyzing the characteristics of data and summarizing the influencing factors of data quality,four evaluation indexes of integrity,validity,mean relative error and mean absolute error are constructed,the evaluation order of each evaluation index is determined,and corresponding evaluation criteria are established for each index.(2)In order to fully describe the relationships and differences between data,a grey relation comprehensive evaluation method based on technique for order preference by similarity to ideal solution is proposed in this paper.The positive and negative ideal solutions of each evaluation index are calculated,and the comprehensive evaluation results are obtained by the grey relation degree between the evaluation index and the positive and negative ideal solutions.Through the validation of the experimental results,this method better reflects the difference between the evaluation index values and the highest and lowest values than the traditional grey relation comprehensive evaluation method.This method can effectively reduce the impact of sudden and drastic fluctuations in data on the comprehensive evaluation results,and improve the accuracy and stability of the comprehensive evaluation.(3)In order to strengthen the discrimination of comprehensive evaluation results,a grey relational comprehensive evaluation method based on particle swarm optimization and technique for order preference by similarity to ideal solution is proposed.This method is used to calculate the relation degree of each evaluation index,the maximum comprehensive evaluation mean objective function is constructed.The particle swarm optimization algorithm is used to optimize the weight distribution of each evaluation index The experimental results show that this method can effectively improve the distinction between the comprehensive evaluation results compared with the grey relation method and the grey relational evaluation method based on technique for order preference by similarity to ideal solution.