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To quantitatively analyze the road congestion around primary and secondary schools and improve the congestion around schools, the traffic congestion data in school season and non-school season were compared. The congestion index of the road around school was established, and the congestion evaluation function was constructed. The influence degree of each road by school travel was analyzed, and the key congested roads were identified. An algorithm for obtaining traffic big data based on the map open platform was proposed. The roads around 79 primary and secondary schools in the main urban area of Nanjing were analyzed, and the congestion value of each road affected by school travel was given. The results show that the overall congestion degree in school season is higher than that in non-school season, and the average congestion index is 1.973 in school season, which is 18.57% higher than that of 1.664 in non-school season. [ABSTRACT FROM AUTHOR]