Risk assessment plays a crucial role in ensuring safety and mitigating potential losses in highway tunnel construction. In response to the challenges commonly encountered in this domain, this paper presents a comprehensive risk assessment index system along with evaluation method to establish a risk assessment model based on the t-s fuzzy neural network. First, the WBS-RBS method was used to identify the risk assessment indices and enhanced by taking soil erosion factor into account. Then, the quantitative criteria of safety risk and risk assessment indices of highway tunnel construction were determined. And the principal component analysis (PCA) method was used to refine and process the quantified indices. As a result, a highway tunnel construction risk assessment model based on the T-S fuzzy neural network was developed and validated using specific construction cases in China. The findings demonstrate the model's validity and reliability, making it a useful reference for similar projects and future research.