<p>To address the current gap in vehicle driving risk assessment, which often fails to fully account for the dynamic nature of risk fields, this study proposes a risk field model based on lane change intention recognition. The model quantifies the potential risks posed by the lane-changing intentions of surrounding vehicles and incorporates these predictions into the overall risk field. Additionally, it considers the impact of factors such as the speed and acceleration of other vehicles, enhancing the model’s ability to predict risks for the vehicle in question. This integrated approach improves the model’s applicability by accounting for various real-world driving scenarios. By combining the proposed risk field model with a simplified vehicle kinematics model, the study demonstrates that it can effectively support vehicle collision avoidance through simulation experiments. The trajectory planning simulation results further validate the reliability of the model’s safe driving recommendations.</p>