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

Authors: Minglei Song; Zhongwei Liu

Addresses: School of Civil and Transportation Engineering, Henan University of Urban Construction, Pingdingshan, Henan 467036, China ' School of Mechanical Engineering, Hunan University of Technology, Zhuzhou 412007, China

Abstract: 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.

Keywords: dense traffic flow area; asphalt pavement; bearing capacity; model construction.

DOI: 10.1504/IJISE.2021.116244

International Journal of Industrial and Systems Engineering, 2021 Vol.38 No.3, pp.378 - 392

Received: 12 Mar 2019
Accepted: 25 Jul 2019
Published online: 14 Jul 2021 *

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