Rollover Prevention and Motion Planning for an Intelligent Heavy Truck

Zhilin Jin,Chaosheng Huang,Jun Li,Jingxuan Li,Hong Wang

doi:10.1186/s10033-021-00605-z

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.

Highlights

1.1 Motivation In the past few decades, the autonomous driving technology has rapidly developed
The main contributions are as follows: (1) A rollover dynamic model is built and a novel rollover index is defined for the intelligent heavy truck, by considering the influence of unsprung mass in the front axle and the rear axle and the body roll stiffness on vehicle rollover stability
(2) The motion planning strategy with active anti rollover ability based on model predictive control is proposed, which integrates the active rollover prevention, the obstacle avoidance and the path tracking with multiple dynamic constraints

Summary

Introduction

1.1 Motivation In the past few decades, the autonomous driving technology has rapidly developed. The LSCACS obtained the reference values of yaw angle and side deflection angle through the linear vehicle model, determined the working mode of the system by combining with Time to Collision (TTC), and obtained the corresponding tire force based on the MPC control He assessed the risk related to collision and instability using the dynamic risk assessment model based on genetic algorithm and used the fifth order polynomial equation to generate the path without collision and with high lateral stability [30]. A motion planning strategy considering autonomous anti rollover ability for an intelligent heavy truck based on V2V communications is proposed in this study. (2) The motion planning strategy with active anti rollover ability based on model predictive control is proposed, which integrates the active rollover prevention, the obstacle avoidance and the path tracking with multiple dynamic constraints. It is assumed that the data of obstacle vehicles and the global path have been obtained from the perception module, V2V communications and the global planning module

Framework of the Intelligent Heavy Truck Motion Planning

Motion Planning Strategy of the Intelligent Heavy Truck

40 Lane 1

Findings

Conclusions