Intelligent Driving Assistant of Heavy Trucks for Rollover Prevention and Lateral Stability

Intelligent driving assistance systems (I-DAS) play a significant role in enhancing road traffic safety. Accidents involving heavy trucks often result in high casualty rates and property damage, but the functionality and prevalence of I-DAS for heavy trucks are not as good as those for passenger cars. To fill this gap, we developed an I-DAS that focuses on heavy trucks, taking into account various loading conditions and road geometric characteristics. The proposed I-DAS assists drivers in achieving lateral stability and reducing rollovers. Firstly, by analyzing the critical dynamic states of rollover and sideslip, we propose safety assessment indicators. Subsequently, a safety speed classification model is introduced. Unlike existing safety speed calculation models, we transform the determination of safety speed into a binary classification problem, combining safety assessment indicators to judge whether driving at a certain speed in a given scenario is safe. Finally, to avoid aggressive acceleration and deceleration, a speed planning model with smooth optimization is proposed to generate an advanced safety speed curve for the entire transport route. The simulation results demonstrate that the current fixed speed limits on roads could potentially mislead the loaded heavy trucks, with a maximum discrepancy of 35km/h between the speed limit and the calculated safety speed. By comparing with typical existing models, only the proposed model can maintain that the stability indicator responses meet the designed thresholds throughout the driving process.