Based on the rutting depth index and driving quality index in the pavement evaluation index, the pavement damage was evaluated in this study. The association rules were used to mine the degree of association between influencing factors such as environment, traffic, and road surface and road surface conditions. Aiming at the shortcomings of the complexity and time-consuming of the association rule Apriori algorithm, an improved Apriori algorithm that does not generate candidate sets to generate frequent sets was proposed. The experiments show that the improved Apriori algorithm can effectively improve the speed and performance. The improved Apriori algorithm was used to analyze the strong association rules between evaluation indexes and influencing factors, and the main causes of pavement damage in different environments were obtained. The conclusion of this paper can provide scientific and reliable support for the pavement maintenance, reasonable maintenance suggestions, and data support for the pavement maintenance department.