Simulation-Based Analysis of Lateral Overturning in an Unmanned Remote-Controlled Crawler Tractor Based on Roll Angular Velocity: Influence of Log Loading Conditions

In this study, the effects of log loading on the lateral overturning of an unmanned, remote-controlled forestry crawler tractor were analyzed through simulation-based analysis. A 3D model was constructed and validated in terms of actual dimensions, static sidelong falling angle, and turning area radius. The errors in both actual dimensions and turning area radius were below 5%, and the static sidelong falling angle was consistent with test results, thereby confirming the model’s reproducibility. Simulations combined three loading levels (0, 50, and 100%), 11 ground slope angles (0 to 50° at 5° intervals), four obstacle heights (0 to 300 mm at 100 mm intervals), and two driving speeds (3.6 and 5.8 km/h). The maximum roll angular velocity within the obstacle contact zone, taken as a safety indicator, was derived for each loading condition. The results showed that lateral overturning occurred before reaching the obstacle, at lower ground slope angles under log loading than without loading. This shows that loading conditions affect lateral discharge safety. Roll angular velocity increased rapidly at high ground slope angles regardless of loading condition, confirming that ground slope angle is key for lateral overturning. Four-way ANOVA results showed that ground slope angle and obstacle height had the greatest impact on roll angular velocity. Although the main effect of loading was relatively small compared to environmental factors, its interaction with ground slope angle was significant, redefining the tractor’s stability limits. Thus, while loading is not a primary factor causing lateral overturning, it influences the sensitivity of roll angular velocity to ground slope angle. These results can be interpreted within a quasi-static framework under low-speed operating conditions, and by using roll angular velocity as an indicator of transient response during obstacle interaction, they provide foundational data for establishing load-dependent safety standards and determining optimal loading limits to prevent lateral overturning in forestry operations.