Examenspresentation av Xie Shengting och Pei Sixuan

Examinator: Jonas Fredriksson

Opponents: Qinghuan Liu and Jingkai Zhou

Abstract:
This thesis explores the motion prediction of articulated heavy vehicles (AHV), specifically focusing on the scenario of jackknifing instability, a leading cause of severe traffic accidents. Jackknifing occurs when the towing unit of the vehicle loses lateral tire grip, resulting in severe yaw instability. This research focuses on developing a comprehensive prediction algorithm to anticipate and mitigate jackknifing events. The investigation begins with modelling AHV using a single and a two track model with load transfer. The study critically assesses the applicability of these models in capturing AHV jackknifing. These models' correctness and limitations are identified by comparing the simulation results using the Volvo Transport Model (VTM). The motion prediction algorithm is devised to predict the motion of the AHV. It employs a discrete state space model and driver input prediction methods, enabling timely prediction for potential jackknifing scenarios. The algorithm's effectiveness is validated through high-fidelity simulations using VTM. Furthermore, the study introduces a jackknifing indicator and a trailer braking strategy, together with the motion prediction algorithms to form a safety system that capable of preventing jackknifing. In conclusion, the thesis presents a safety system that can predict, prevent, and mitigate the risks associated with jackknifing.

Welcome!

Qinghuan, Jingkai and Jonas