The short-term traffic flow prediction and modeling of highways are the core content and important foundation of highway management decision-making support systems. It is of great significance to improving the level of highway management. Based on the macrodynamic traffic flow model, this article establishes a method for establishing a highway traffic flow prediction model based on the BP neural network theory and gray theory. We collected and carry out modeling and prediction of highway traffic flow data near a certain station. It is learned from the prediction results that the traffic flow prediction model based on the BP neural network and gray theory has a high degree of reliability.

With the construction of road infrastructure in China, the rapid development of expressways has provided great convenience for human travel and cargo transportation. Asphalt concrete pavement is widely used in highway construction because of its characteristics of good flatness, high strength, and convenient maintenance. But the water damage of asphalt concrete pavement is the main factor affecting the stability of highway subgrade and flatness of pavement, as well as the main cause of deformation and collapse of pavement. In view of the water damage problem of asphalt concrete pavement, this paper investigates the overall condition and water damage situation of asphalt concrete pavement with different immersed states and carries out indoor simulation test of asphalt concrete samples without water, dry and wet cycle, and saturated water. The quality, loss rate and Marshall stability of the samples under different times of cyclic rolling were obtained through the statistics of cyclic rolling pressure of the samples. The influencing factors of water loss, water resistance and failure forms of highway under different impregnation environments were analyzed, and the prevention measures of water loss of asphalt concrete were put forward. The test results show that the mass loss rate of the sample is water-free, dry-wet cycle, and water-saturated, and the Marshall stability of the sample is water-free, dry-wet cycle, and water-saturated from high to low. Under the action of rolling and friction forces, the fine aggregates in the asphalt concrete are worn off, which leads to the expansion of cracks on the surface of the sample and the formation of fissure network. Small holes appear on the surface of water-saturated sample, and the coarse aggregate is broken and disintegrated under pore water pressure. Traffic flow (cyclic rolling times) and immersion state have become the main factors of asphalt concrete pavement failure. This study has specific and important theoretical guiding significance for reducing and preventing water damage of asphalt concrete pavement of expressway, delaying road service life, and enhancing road safety.