Rollover Prevention and Motion Planning for an Intelligent Heavy Truck

Abstract

Abstract It is very necessary for an intelligent heavy truck to have the ability to prevent rollover independently. However, it was rarely considered in intelligent vehicle motion planning. To improve rollover stability, a motion planning strategy with autonomous anti rollover ability for an intelligent heavy truck is put forward in this paper. Considering the influence of unsprung mass in the front axle and the rear axle and the body roll stiffness on vehicle rollover stability, a rollover dynamics model is built for the intelligent heavy truck. From the model, a novel rollover index is derived to evaluate vehicle rollover risk accurately, and a model predictive control algorithm is applicated to design the motion planning strategy for the intelligent heavy truck, which integrates the vehicle rollover stability, the artificial potential field for the obstacle avoidance, the path tracking and vehicle dynamics constrains. Then, the optimal path is obtained to meet the requirements that the intelligent heavy truck can avoid obstacles and drive stably without rollover. In addition, three typical scenarios are designed to numerically simulate the dynamic performance of the intelligent heavy truck. The results show that the proposed motion planning strategy can avoid collisions and improve vehicle rollover stability effectively even under the worst driving scenarios.

Keywords

• Rollover prevention
• Intelligent heavy truck
• Motion planning
• Path tracking
• Artificial potential field