Modelling and analysis on bearing capacity of asphalt pavement in dense traffic flow of urban areas

Aiming at the problems of low fitting degree and high complexity between the research results and the actual situation, the bearing capacity model of asphalt pavement in dense traffic flow area based on combination forecasting is put forward. Cellular automata is used to calculate the relative position and speed change of vehicles in the popularisation process. According to Orkut model, the relative position and speed change of each vehicle on the road is calculated and analysed. Through calculation and analysis, the vehicle load concentration value is obtained. The experimental results show that the SSE, MAE, MSE and complexity coefficient of the bearing capacity model for asphalt pavement in heavy flow area based on combined prediction are lower than 0.05, lower than 0.15, lower than 0.16 and lower than 0.2, which are the minimum values in the comparison method, indicating that the model has high accuracy, low complexity and good reliability. Copyright © 2021 Inderscience Enterprises Ltd.